A multilevel analysis of short birth interval and its determinants among reproductive age women in developing regions of Ethiopia

Setognal Birara Aychiluhm; Abay Woday Tadesse; Kusse Urmale Mare; Mohammed Abdu; Abdusemed Ketema

doi:10.1371/journal.pone.0237602

. 2020 Aug 26;15(8):e0237602. doi: 10.1371/journal.pone.0237602

A multilevel analysis of short birth interval and its determinants among reproductive age women in developing regions of Ethiopia

Setognal Birara Aychiluhm ^1,^*, Abay Woday Tadesse ¹, Kusse Urmale Mare ², Mohammed Abdu ³, Abdusemed Ketema ³

Editor: Srinivas Goli⁴

PMCID: PMC7449410 PMID: 32845940

Abstract

Background

Short Birth Interval negatively affects the health of both mothers and children in developing nations, like, Ethiopia. However, studies conducted to date in Ethiopia upon short birth interval were inconclusive and they did not show the extent and determinants of short birth interval in developing (Afar, Somali, Gambella, and Benishangul-Gumuz) regions of the country. Thus, this study was intended to assess the short birth interval and its determinants in the four developing regions of the country.

Methods

Data were retrieved from the Demographic and Health Survey program official database website (http://dhsprogram.com). A sample of 2683 women of childbearing age group (15–49) who had at least two alive consecutive children in the four developing regions of Ethiopia was included in this study. A multilevel multivariable logistic regression model was fitted to identify the independent predictors of short birth interval and Akaike’s Information Criterion (AIC) was used during the model selection procedure.

Results

In this study, the prevalence of short birth interval was 46% [95% CI; 43.7%, 47.9%]. The multilevel multivariable logistic regression model showed women living in rural area [AOR = 1.52, CI: 1.12, 2.05], women attended secondary education and above level [AOR = 0.27, CI: 0.05, 0.54], have no media exposure [AOR = 1.35, CI: 1.18, 1.56], female sex of the index child [AOR = 1.13, CI:1.07,1.20], breastfeeding duration [AOR = 0.79, CI: 0.77, 0.82], having six and more ideal number of children [AOR = 1.14, CI: 1.09, 1.20] and having preferred waiting time to birth two years and above [AOR = 0.86, CI: 0.78, 0.95] were the predictors of short birth interval.

Conclusions

The prevalence of short birth intervals in the developing regions of Ethiopia is still high. Therefore, the government of Ethiopia should work on the access of family planning and education in rural parts of the developing regions where more than 90% of the population in these regions is pastoral.

Introduction

The World Health Organization (WHO) and Ethiopian Demographic and Health Survey (EDHS) reports on birth spacing recommended a birth to conception interval of at least 24 months in two consecutive births [1, 2].

Demographic and Health Survey (DHS) data from 18 developing countries (Africa, Asia, Latin America, and the Middle East) and an International comparison study of 77 countries using DHS data revealed that a birth interval of three or more years interval improves the survival status of mothers, under-five children and infants [3, 4].

Ethiopia is the second-most populous country in Africa, with a population size of more than 100 million and a fertility rate of 4.6 children per woman [2, 5]. Like many other African countries, Ethiopia has shown so far little change in fertility reduction because of socio-cultural and religious factors [6]. For instance, first marriage at an early age, desire for more children, and low contraceptive utilization related to religious issues influence the status of fertility[7, 8].

In developing nations, more than 200 million women either want to space or limit pregnancies and yet they lack access to modern family planning options [1, 9–12]. Demographic Health Survey (DHS) studies revealed a high level of Short birth intervals (SBIs) in the region (Rwanda: 20%, Uganda: 25.3%, and Cameroon: 21.3%) [13]. In Ethiopia, the prevalence of SBI (i.e. Birth interval < 24 months) ranges between 23.3% and 59.9% [14–17].

Globally, a birth interval of fewer than 18 months is associated with increased risk for neonatal mortality, infant mortality, under-five mortality, and maternal mortality [4, 6, 9, 15–21]. Similarly, Ethiopia has experienced a significant number of neonatal mortality and infant associated with short birth interval compared to the overall average rate of infant and neonatal mortality reported in Africa [18].

Studies conducted across the globe have identified various factors associated with SBI. These include; maternal age, maternal education level, husband education level, death of the index child, sex preference of the parents, no use of contraceptives, the ideal number of children, socio-cultural factors, religion, short breastfeeding duration (less than 24 months), and poor wealth index [14, 17, 22–27].

The Sustainable Development Goals (SDGs) of 2030, which combine multisystem strategies at global, regional, and national levels, have three focuses to ensure healthy lives and promote wellbeing for all at all ages. Of these goals, one main objective is to reduce the neonatal mortality rate to lower than 12 per 1,000 live births [28–30] which is at a steady stage in developing nations. According to the 2019 mini EDHS, infant mortality rate was 43 deaths per 1,000 live births and under-5 mortality rate was 55 deaths per 1,000 live births in Ethiopia [31]. By 2030, Ethiopia aiming to reduce neonatal mortality to at least as low as 12 per 1000 live births and under-five mortality to at least as low as 25 per1000 live births [32].

Despite the implementation of various strategies and interventions at global and national levels to decline burden of under-five children, infant and neonatal mortality rates [10, 33–36], short birth spacing remains one of the leading causes of child mortality [4, 37] in developing nations [18, 21]. In Ethiopia, still, 22% of women have an unmet need for family planning(FP) with 35% of contraceptive discontinuation rates [2]. Thus, this may contribute to the high level of SBI in the country. Besides, studies conducted in Ethiopia were limited to developed regions and inconclusive to show the determinants of short birth interval in developing regions. Moreover, previous studies conducted [12, 17, 27, 38] in the country had not been identified the community level determinants of short birth interval. Furthermore, using a single-level logistic regression analysis technique to analyze data that has a hierarchical structure nature (that is women nested within communities) violates the independence assumptions of regression [39, 40]. Hence, to address these limitations, and to further estimate the significant effect of individual and community-level factors in developing regions of Ethiopia, this study used multilevel logistic regression analysis.

The results of this study will offer crucial information for policymakers, program planners, and other stakeholders to plan and implement proper interventions to prevent short birth interval in developing regions of the country.

Therefore, this study was aimed to address both the individual and community-level determinants of short birth interval among women resided in the four developing regions (Afar, Somali, Benshandul-Gumz, and Gambella) of Ethiopia.

Methods and materials

Study area and data source

The study was conducted in developing regions of Ethiopia which are found mainly in lowland parts of the country. These regions are; Afar, Somali, Gambella, and Benishangul-Gumuz regions. These four regions are not well achieving most of the indicators related to health, human development and Millennium Development Goals compared to other developed regions of Ethiopia [41]. The main lifestyle of these regions depends on animal livestock and farming. Hence, the communities resided in these regions are nomadic ethnic groups and highly mobile which are not suited to the existing health system of the country [42–44]. Besides, in developing regions of the country, women in reproductive-age group are inaccessible to modern contraceptives, more over in these developing regions of the country, there are socio-cultural and religious barriers towards the utilization of birth control methods [43, 45, 46].

The data were retrieved from the Demographic and Health Survey (DHS) program official database website (http://dhsprogram.com), that was conducted in nine regions (Tigray, Afar, Amhara, Oromia, Somali, Benishangul-Gumuz, Southern Nations Nationalities and Peoples Region (SNNPR), Gambella, and Harari), and two city administrations (Addis Ababa and Dire-Dawa) of Ethiopia from January 18, 2016, to June 27, 2016.

To conduct the 2016 Ethiopian Demographic and Health Survey (EDHS), a two-stage stratified cluster sampling technique has been employed. Enumeration areas were selected in the first stage. In the second stage, 28 households per enumeration area were selected with an equal probability of systematic selection per Enumeration Area (EA). Nationally, a total of 645 EAs were selected with probability proportional to EA size, and nationally a total sample size of 16,515 women aged 15–49 years was collected.

The study populations for this study were 2683 (388 from Afar, 1706 from Somali, 489 from Benishangul-Gumuz, and 100 from Gambella) women who had at least two consecutive live births in the 5 years preceding the survey, nested within four developing regions of the country [2]. For this study, all women of childbearing age group (15–49) having at least two alive children in four developing regional state governments of Ethiopia were included for our analysis. Women who had never been married and those who have multiple births out of wedlock were excluded from the analysis.

Study variables

Dependent variable

Short Birth Interval. The outcome variable of this study was a short birth interval (SBI) which was dichotomized into “Yes = 1/ No = 0” form. A birth that occurred at less than 24 months following a previous birth in two successive births was classified as having SBI, according to WHO recommendation [1]. The birth interval was calculated as the time that elapsed between the birth date of the first child and the birth date of the second child [47].

Independent variables

All the independent variables were selected based on reviewed different literature [9, 12, 13, 15, 17, 23, 27, 37] and those independent variables were classified into individual-level variables and community-level variables. Individual-level variables were sex of index child, age at marriage, mother’s age at first birth, parity (number of live births), women’s education level, husband’s education level, husband’s occupation, wealth index, respondents occupation, religion, exposure to any mass media, survival status of the index child, ideal number of children, preferred waiting time to birth, number of living children, duration of breastfeeding (in months), and contraceptive utilization. Community-level were region, type of residence, and cluster.

Media exposure

To measure exposure to media in the 2016 EDHS, watching television (TV), listening to radio, and reading newspaper at least once a week were considered. The tree media channels have categories “all at least once a week”, “both at least once a week” and “no accesses at least once a week”. Therefore, a new variable called media exposure was generated by combining the three media sources (TV, Radio, and Newspaper), Then media exposure was labeled as “Yes” if respondents had exposure at least one of the media channel and labeled “No” if respondents did not have any exposure to either of the three media channels.

Multi-collinearity

The presence of multicollinearity among independent was checked using Variance Inflation Factor (VIF) taking cut off value of 10. Variables having a VIF value of less than 10 were considered as the absence of multicollinearity.

Data analysis

Descriptive statistics

Based on the recommendation of EDHS, proportions and frequencies were estimated after applying sample weights to the data to adjust for disproportionate sampling and non-responses. Since the allocation of the sample in the EDHS to different regions as well as urban and rural areas were non-proportional. A detailed clarification of the weighting process can be found in the 2016 EDHS report [48]. Categorization was done for continuous variables using information obtained from different literatures, and re-categorization was done for categorical variables accordingly to make suitable for analysis. The analysis was performed using Stata version 15.0.

Bivariable multilevel analysis

The effect of each independent variable (both individual and community-level) on the dependent variable was checked at a p value of 0.25. Variables in which p-value of less than 0.25 in the bivariable multilevel logistic regression analysis were considered as candidates for multivariable multilevel logistic regression analysis.

Multivariable multilevel analysis

Due to the hierarchical nature of the 2016 EDHS data (i.e., mothers are nested within clusters), to account this clustering effect, a multivariable multilevel logistic regression analysis was applied to determine the effects of each predictor of SBI.

Model building and comparison

Four models containing variables of interest were fitted for this study.

Model I (Empty model) was fitted without explanatory variables to test random variability in the intercept and to estimate the intra-class correlation coefficient (ICC) and Proportion Change in Variance (PCV).

Model II assessed the effects of individual-level predictors,

Model III assessed the effects of community-level predictors and

Model IV (Full model) examined effects of both individual and community-level characteristics simultaneously.

Akaike’s Information Criterion (AIC) was used to select the model and the model with low AIC value was considered as a best-fitted model. Based on AIC the full (model with individual and community-related variables) model has the smallest AIC value among the model considered, therefore the full model best fits the data. AOR with 95% Confidence interval in the multivariable model was used to select variables that have a statistically significant association with short birth interval.

Ethical consideration

The data were accessed from the Demographic and Health Survey (DHS) website (http://www.measuredhs.com) after getting registered and permission was obtained (AuthLetter_136950). The accessed data were used for this registered research only. The data were treated as confidential and no effort was made to identify any household or individual respondent.

Results

Descriptive statistics of the study variables

Out of the total respondents, 2,287 (84.2%) women were living in rural site, 2319 (86.4%) of the women were Muslim religion faith followers, 2281 (85.1%) were not attended formal education, 2141 (79.8%) of the women were agricultural workers, and 1695 (63.2%) of the respondents had poorest wealth index. In this study, the average breastfeeding duration for the preceding index child was 64 ± 0.03 standard deviation (SD) months. The study showed 2224 (82.9%) of the respondents did not have media exposure towards the short birth interval and 1651 (61.5%) of the women reported having more than six ideal numbers of children including the current birth. The study also revealed that 2508 (93.5%) of the women included in the study were not using any contraceptive methods (Table 1).

Table 1. Weighted socio-demographic, reproductive, behavioral and child status-related characteristics of study participants, EDHS,2016 [N = 2683].

Variable	Category	Frequency	Percent
Residence	Urban	396	14.8
Residence	Rural	2,287	85.2
Religion	Muslim	2319	86.4
Religion	Others+	364	13.6
Mothers age at first marriage	Less than 18 years	1674	62.5
Mothers age at first marriage	18 and above	1006	37.6
Respondent’s educational status	No education	2281	85.0
	Primary	323	12.0
	Secondary and above	79	3.0
Husband’s educational status	No education	1819	74.3
	Primary	382	15.6
	Secondary and above	247	10.1
Respondent’s occupation	Agriculture	2141	79.8
	Professional	412	15.3
	Others++	130	4.9
Husband’s occupation	Agriculture	1622	66.1
	Professional	470	19.1
	Others+++	357	14.6
Wealth Index	Poorest	1695	63.2
	Poorer	297	11.1
	Middle	191	7.1
	Richer	194	7.3
	Richest	305	11.4
Sex of child	Male	1377	51.3
Sex of child	Female	1306	48.7
Ideal number of Children	Less than 6	1032	38.5
Ideal number of Children	6+	1651	61.5
Survival of index child	Yes	2351	87.6
Survival of index child	No	332	12.4
Preferred waiting time to birth	Less than 2 years	1054	39.3
Preferred waiting time to birth	2 and above years	1629	60.7
Use contraceptive	Yes	175	6.5
Use contraceptive	No	2508	93.5
Media Exposure	Yes	459	17.1
Media Exposure	No	2224	82.9

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Key: Other+ = catholic, orthodox, protestant, other and traditional, Other++ = skilled manual, unskilled manual and other, Other+++ = Other EDHS category and laborer.

Prevalence of short birth interval

Overall, 967(46% (95% CI; 43.7%, 47.9%)) of the women had experienced short birth interval, of these, 518 (53.6%) women had SBI which age at birth ≤ 18 years, 372(38.4%) ranges from 19–24 years and the rest 69(6.1%) were 25 years and above. Besides, from those women who had experienced short birth interval, the majority (707) of them were from Somali regional state.

Determinants short birth interval

Empty multilevel logistic regression model (Null model)

From the null model variance of the random factor was 0.21 with a 95% confidence interval of (0.05, 0.84), showing heterogeneous areas. Since the variance estimate, which is greater than zero, it indicates that there are enumeration (cluster) area differences in short birth interval among women in four developing regional states in Ethiopia, and thus multilevel analysis should be considered as an appropriate approach for further analysis.

The intra-cluster correlation coefficient (ICC) which indicated that 6% of the total variability in short birth interval is due to differences across cluster areas, with the remaining unexplained 94% attributable to individual differences. The Proportion Change in Variance (PCV) indicated that 81% of the variation in short birth interval across communities was explained by both individual and community level factors included in the full model (Table 2).

Table 2. Community-level variance of two-level mixed-effect logit models predicting short birth interval, EDHS 2016.

Random effect	Null model	Full model
Community-level variance	0.21	0.04
ICC (%)	6	0.01
PCV (%)	Reference	0.81
Model fitness statistics (AIC)	2866	812

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Multilevel multivariable logistic regression model (Full model)

In the multilevel multivariable logistic regression model, both the individual and community level factors were fitted simultaneously. Thus, residence site, women’s educational status, media exposure, sex of the index child, breastfeeding duration, the ideal number of children and preferred waiting time to birth were statistically associated with a short birth interval at 95% confidence level.

After adjusting for covariates; the odds of the short birth interval among women in a rural area was 1.52 times higher compared to those living in an urban area (AOR = 1.52, CI: 1.12, 2.05).

This study revealed that while breastfeeding duration of the index child increase by one month, the odds of SBI among women decrease by 21% (AOR = 0.79, CI: 0.77, 0.82).

In this study, women having female sex of the index child had 1.13 times greater risk of short birth interval compared to those women having male index children (AOR = 1.13, CI:1.07,1.20).

Keeping other covariates constant, women who attended secondary education and above levels were 27% less likely to have SBI compared to women without formal education (AOR = 0.27, CI: 0.05, 0.54).

The odds of the short birth interval among women who did not have exposure to any media about short birth interval before or during the index child was 1.35 times greater compared to those women did have exposure to any media (AOR = 1.35, CI: 1.18, 1.56).

In this study, women who have preferred waiting time to birth two years and above were 14% less likely to have short birth interval compared to those who had preferred waiting time less than two years (AOR = 0.86, CI: 0.78, 0.95). Moreover, women who have a desire of six or more children had 1.14 times greater risk of short birth interval compared to those women having a desire of fewer than six children (AOR = 1.14, CI: 1.09, 1.20) (Table 3).

Table 3. Multilevel multivariable logistic regression of the individual and community-related variables associated with short birth interval, EDHS 2016.

Variables	Categories	Short Birth Interval Status		AOR (95%CI)
Variables	Categories	Yes	No	AOR (95%CI)
Residence site	Urban (ref)	122 (12.6)	171 (14.9)	1.00
	Rural	845 (87.4)	972 (85.1)	1.52 (1.12, 2.05) ^*
Wealth index	Poorest (ref)	653 (67.5)	705 (61.7)	1.00
	Poorer	96 (10.0)	138 (12.1)	0.94 (0.75, 1.17)
	Middle	70 (7.2)	77 (6.7)	1.40 (0.80, 2.43)
	Richer	58 (5.9)	93 (8.2)	1.06 (0.45, 2.47)
	Richest	91 (9.4)	129 (11.3)	1.69 (0.87, 3.28)
Women education	No education (ref)	870 (89.9)	971 (85.0)	1.00
	Primary	85 (8.8)	138 (12.1)	0.80 (0.63, 1.01)
	Secondary and above	13 (1.3)	33 (2.9)	1.27(1.05, 1.54) ^*
Media exposure	No (ref)	834 (86.4)	935 (81.8)	1.00
Media exposure	Yes	132 (13.6)	208 (18.2)	0.74 (0.64, 0.85) ^*
Husband occupation	Agriculture (ref)	600 (66.9)	701 (67.8)	1.00
Husband occupation	Professional	167 (18.6)	191 (18.5)	0.86 (0.65, 1.12)
	Others+	130 (14.5)	142 (13.8)	0.80 (0.64, 1.01)
Religion of respondent	Muslim	890 (92.0)	956 (83.7)	1.65 (0.85, 3.20)
Religion of respondent	Others++	78 (8.0)	186(16.3)	1.00
Age at marriage	Less than 18 years	588 (60.8)	734 (64.3)	1.05 (0.88, 1.24)
Age at marriage	18 and above years	379 (39.2)	408 (35.7)	1.00
Age at birth of index child	≤18 years	518 (53.6)	656 (57.5)	0.90 (0.64, 1.29)
	19–24 years	372 (38.4)	417 (36.5)	0.94 (0.75, 1.18)
	25 and above years	78 (8.0)	69 (6.1)	1.00
Sex of child	Male	495 (51.2)	584 (51.1)	1.00
Sex of child	Female	472 (48.8)	559 (48.9)	1.13 (1.07, 1.20) ^*
Number of live births				1.10(0.22, 1.18)
Number of living children				0.95(0.91, 1.00)
Ideal number of Children	Less than 6 (ref)	329 (34.0)	457 (40.0)	1.00
Ideal number of Children	6+	638 (66.0)	685 (60.0)	1.14 (1.09, 1.20) ^*
Survival of index child	No (ref)	155 (16.1)	91 (8.0)	1.00
Survival of index child	Yes	812 (83.9)	1052 (92.0)	0.52 (0.42, 1.62)
Preferred waiting time to birth	Less than 2 years (ref)	414 (42.8)	409 (35.8)	1.00
Preferred waiting time to birth	2 and above years	554 (57.2)	733 (64.2)	0.86 (0.78, 0.95) ^*
Use contraceptive	No	934 (96.6)	1058 (92.6)	1.36 (0.61, 3.04)
Use contraceptive	Yes (ref)	33 (3.4)	84 (7.4)	1.00
Breastfeeding duration (months)				0.79 (0.77, 0.82) ^*

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ref = reference

* statistically significant variables at 95% confidence interval, Other+ = Other EDHS category, Other++ = catholic, other and traditional.

Discussion

Women’s physiological regression is the only hypothetical causal mechanism that has been proposed to explain the association between short birth spacing and maternal health and adverse birth outcomes [49]. This study aimed to determine the prevalence and determinants of short birth interval among women in developing regions of Ethiopia using the EDHS 2016 dataset. This study revealed that residence site, women’s educational status, media exposure, sex of the index child, breastfeeding duration, ideal number of children, and preferred waiting time were the independent predictors of short birth interval in the four developing regions of Ethiopia.

In this study, the prevalence of short birth interval in the four developing regions of Ethiopia is 46% [95% CI; 43.7%, 47.9%]. This finding is higher than a study conducted in Northern Ethiopia (23.3%) [14], a study done in Jimma, Southwest Ethiopia (27%) [15], Dabat district, Northwest Ethiopia (39.1%) [23], Arsi Zone, Ethiopia (17.3%) [24], Northern Ethiopia (40.9%) [50], and rural Bangladesh (24.6%) [37]. This discrepancy could be due to the fact that the current study is carried out in the developing regions of the country, where women in the reproductive-age group are inaccessible to modern contraceptives. Besides, there are also socio-cultural barriers [51, 52] upon the utilization of birth controls in the developing community compared to the other parts of Ethiopia.

However, the prevalence is lower than a study conducted in Lemo district, Southern Ethiopia (57%) [12], Jimma Zone, Southwest Ethiopia (59.9%) [16], Tanzania (48.4%) [9], and Kassala, Eastern Sudan (60.6%) [53]. This could be explained by small sample size in the previous studies and the difference in study designs. In addition, this variation could be explained by a difference in cut-off values used to determine SBI. Those previous studies considered SBI if birth interval less than 36 months, while our study defined it as less than 24 months.

In this study, the odds of short birth interval among women in reproductive-age group living in the rural area is 1.44 times higher compared to those women living in an urban area. This is similar to a study conducted in Lemo district, Southern Ethiopia [12], and a study done in the Democratic Republic of Congo [13]. This could be justified by women living in the rural sites are socio-economically disadvantaged [37] and inaccessible to modern contraceptive methods. Thus, they are more likely to experience a short birth interval compared to women residing in an urban area of the country.

This study revealed that as breastfeeding duration of the index child increase by one month, the odds of SBI among childbearing women decrease by 79%. This finding is similar to a study done in Serbo Town, Southwest Ethiopia [16], a systematic review of 58 observational studies [49], Northern Ethiopia [14], Dodota district, Southern Ethiopia [24], Northern Ethiopia [50], and Egypt [54]. Optimal breastfeeding prolongs the length of time between two consecutive births. women’s physiological regression is the causal mechanism that has been proposed to explain the association between birth spacing and prolonged breastfeeding [49]. Consequently, the longer the duration of breastfeeding the women practicing for the index child, the lesser the risk of being short birth interval for the succeeding birth.

In this study, women having female sex of the index child had 1.13 times greater risk of short birth interval compared to those women having male index children. This finding is consistent with study done in Serbo Town, Southwest Ethiopia [16], rural developing communities of Southern Ethiopia [17], Arba Minch district, Ethiopia [27], and Northern Ethiopia [50]. In the developing community of Ethiopia, parents and their community members have male preference than female children. This sex preference is usually related to the families’ interest in being safeguarded from enemies by their young male children. In addition, since the parents’ lifestyle is related to livestock, they need more male children for the sake of keeping their cattle. Thus, the preceding index child being female has been contributed to the risk of a short birth interval to get more male children.

Women who attended secondary education and above levels were 0.27 less likely to have SBI compared to women without formal education. This finding is consistent with the study done in Tanzania (48.4%) [9], Democratic Republic of Congo [13], rural developing communities of Southern Ethiopia [17], Serbo Town, Southwest Ethiopia [16], Arba Minch district, Ethiopia [27], and Kassala, Eastern Sudan [53]. When the education status of the women increased, the knowledge and awareness of the women upon the consequences of short birth interval on maternal and child health will also be optimized. Thus, women attending secondary education level and above have a lower risk of short birth interval compared to women who have no education.

The odds of short birth interval among women who did not have exposure to any media about short birth interval before or during the index child was 1.35 times higher compared to those women who had exposure to any media. This finding is in line with the studies conducted in Bangladesh [55, 56]. Therefore, women who have information about short birth interval through any media channel are expected to have a better understanding of the negative impact of short birth interval on maternal and children’s health. As a result, women who have no exposure for any media are more likely to experience short birth interval than those have any media exposure.

In this study, women with two years and above preferred waiting time to birth were 14% less likely to have short birth interval compared to those who had preferred waiting time less than two years. Moreover, women who have a desire to have six or more children had 1.14 times greater risk of short birth interval compared to those with a desire of fewer than six children. In the developing community of Ethiopia, parents and their community members have a desire for more children because of socio-cultural and religious interests. For instance, the majority of the community in the four developing regions of Ethiopia are Muslim religious faith followers, in which the use of modern contraceptives for child spacing does not have been practiced yet [52]. This finding is also consistent with a study conducted in Northern Ethiopia [14], Jimma Zone, Southwest Ethiopia [15], rural developing communities of Southern Ethiopia [17] and Kassala, Eastern Sudan [53]. Furthermore, the lifestyle of the community in the developing regions is purely dependent on livestock, in which having more children is considered as advantageous to get more keeper for their cattle. Thus, this perception of the developing community towards more children has been one of the contributors to short birth interval in these regions of the country. In this study, there was no significant association between wealth index of the household and birth interval of women.

Conclusion

The prevalence of short birth interval in the developing regions of Ethiopia is still optimally high. In the multilevel multivariable logistic regression model; residence site, women’s educational status, media exposure, sex of the index child, breastfeeding duration, ideal number of children, and preferred waiting time were the independent predictors of short birth interval in the four developing regions of Ethiopia. Therefore, the government of Ethiopia should work on the access to family planning and education in rural parts of the developing regions where more than 90% of the population in these regions is pastoral. Besides, the federal and regional governments should give attention to local means of communication channels to promote the health of women and their children where most of the community has not access to television, radio, and other modern media channels. Additional systematic review and meta-analysis study is recommended to have a pooled estimation of a short birth interval and its determinants at the national level.

Strengths and limitations of the study

This study was based on the most recent EDHS with a nationally representative large sample size. Moreover, this study applied multilevel modeling to handle the hierarchical nature of the EDHS data. Despite the above strengths, the study might have recall bias since the participants were asked about the events that took place 5 years or more preceding the survey. The study also shares the limitations of cross-sectional studies.

Acknowledgments

The authors acknowledge the ICF International for Granting access to the use of the 2016 Ethiopian Demographic and Health Survey (EDHS) data for this study.

Data Availability

Data underlying this study can be found at https://dhsprogram.com/data/dataset/Ethiopia_Standard-DHS_2016.cfm.

Funding Statement

The authors received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0237602.r001

Decision Letter 0

Srinivas Goli

Transfer Alert

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10 Jun 2020

PONE-D-20-07800

A Multilevel Analysis of Short Birth Interval and Its Determinants among Women in Pastoral Regions of Ethiopia

PLOS ONE

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Reviewer #1: Adequate birth spacing fetches great health benefits to both Mother and Child. The topic of the present study is of great interest for improving the Maternal and Child health in pastoral region of Ethiopia. The authors have used data from Demographic and Health Survey, 2016 on women in reproductive age-group 15-49 years. The present study aimed to address both the individual and community-related factors for short birth interval on four pastoral regions of Ethiopia using multilevel logistic regression technique. The manuscript does not contain line or page numbers which makes it difficult to point out observations. Therefore, I am mentioning the observations by sections in the manuscript.

Title

As the study is focused only on women in Child-bearing ages 15-49 years and not all women, the present title, "A Multilevel Analysis of Short Birth Interval and Its Determinants among Women in Pastoral Regions of Ethiopia" needs to be modified.

Abstract

" Avoid use of abbreviations in the abstract section.

" Please mention the four pastoral regions where the study was based.

" What is the sample size included in the study?

" Replace "independent predictor" with "predictor".

" The statement "The statistical significance level was declared at a 95% confidence interval" can be dropped from the abstract.

" The conclusion section needs to be strengthened, as the present one looks vague.

" The statement, "government should encourage local communication channels to promote the health of women and children" is ambiguous in interpretation. What measures are suggested by the authors to promote the health of women and children.

Introduction

" Paragraph 3 gives data related to Nigeria. Please provide similar data for Ethiopia.

" Also, total fertility rate is given per 1000 women. Please mention the units.

" In view of the statement "Like many other African countries, Ethiopia has shown so far little change in fertility reduction because of socio-cultural and religious factors." Can author give instances or examples of the cultural practices and religious factors responsible for higher fertility rates.

" Please mention the full form of the abbreviation SBI when first mentioned in the Introduction section.

" In view of the statement, "The Sustainable Development Goals (SDGs) of 2030, which combine multisystem strategies at global, regional and national levels, have three focuses to ensure healthy lives and promote wellbeing for all at all ages. Of these goals, one main objective is to reduce the neonatal mortality rate to lower than 12 per 1,000 live births [32-34] which is at a steady stage in developing nations." Can authors mention the present level of Infant and under five mortality in Ethiopia and Country specific goals to reduce IMR and U5MR (set by government or SDG).

" In view of the statement "Moreover, studies conducted in Ethiopia were limited and inconclusive to show the determinants of short birth interval at the community level (i.e. they were assessed only individual related factors). Therefore, this study aimed to address both the individual and community-related factors for short birth interval on four pastoral regions of Ethiopia using multilevel logistic regression analysis which is the appropriate model to handle community-level factors of short birth interval" it would be better to re-write the need for the study by adding more literature stating the importance of studying SBI in pastoral regions and use of multi-level analysis.

" It is not mentioned anywhere what is the meaning of pastoral region and why is it important to study it. It is difficult to understand the use of the present study for international audience.

" Dedicate the last paragraph of the Introduction section to mention only the need for the study and study objectives

Methods

Data Source

" What was the total sample collected by DHS in Ethiopia?

" What are these nine regions and two city administrations included by the survey?

" The statements "All women of reproductive-age group were included in the first stage" and "The information was collected from a nationally representative sample of 16,515 women aged 15-49 years" can be combined.

" Is child birth outside of wed-lock is common in Ethiopia? If not, unmarried women sample needs to be removed from the analysis. Were any measures taken to do the same?

" The author has used the term Pastoral region throughout the manuscript. There are a few questions which arise in my mind: 1) What is a pastoral region? , 2) What four pastoral regions have been selected in the study and what are the reasons for specifically selecting these regions? 3) What are the sample sizes from each of the regions? It would be better if the authors can provide an elaborate description on the sample selection.

" How have the authors adjusted for "twins" birth?

Ethics Statement: Although the present study rests on a publically available dataset, still as the study included human subjects, it is advised to add a section of ethical consideration in the methods section after data source.

Study Variables-Dependent Variable

" Use either of the two terms: Short Birth Interval or Optimal Birth Interval.

" The authors have calculated the birth interval as the time that elapsed between the birth date of the first child and the birth date of the second child which I think is the standard procedure. It is however advisable to include a reference of the same. You can find a reference here: https://dhsprogram.com/pubs/pdf/CR28/CR28.pdf (section 1.2).

" I would recommend using "Croft, T. N., Marshall, A. M., Allen, C. K., Arnold, F., Assaf, S., & Balian, S. (2018). Guide to DHS statistics. Rockville: ICF" to check and revise the computation procedure of the variables included in the study.

Independent Variables

" I am concerned regarding the choice of predictor variables. The predictor variables can be clubbed into following sections, namely reproductive, behavioral, and child status. However, it is not clear that which conceptual framework has been utilized to select these predictor variables. Please mention the same.

" Also, the abstract suggests that a multilevel multivariable analysis has been used, it is not clear what are the levels included for the analysis and which variable was introduced at which level? Please provide a detailed description of the same.

" The explanatory variables included in the study can be correlated with each other. Are any measures taken to check for the same? If yes, include a section explaining the same in the methods section after variable description.

Analysis Plan

" Data Analysis section needs to be restructured as there are a lot of repetition.

" The section "In data with a nested structure……. mixed- effect logistic regression analysis was used in this study." needs to be re-written as the meaning is not clear.

" The statement "Data were weighted before analysis and merge and re-categorize to make suitable for analysis" looks ambiguous. Please elaborate.

" A section on Bivariate analysis needs to be added before proceeding to the multivariate analysis. It is evident that Table 4 provides a 2x2 contingency table for all the predictor variables, however, it would be great if you can include chi-square/unadjusted odds ratio, and p-values in the table.

" Authors state that they have utilized software R, it is not clear which part of the analysis or data visualization was done in R.

Results

" Table 1 and 2 provides the descriptive account of the variables included in the study. These two tables can be combined to form a single table using sub-headings in the table.

" In both Table 1 and 2 the authors have mentioned Weighted frequency and percentage (unweighted) which needs to be substituted with unweighted frequency and weighted percentages.

" Include a row "Total" for the Table 1 and 2 or mention total sample size (N) in the table.

" The categorization of the explanatory variables needs an urgent attention, for instance variables like Religion, Respondent's educational Status, Husband's Educational Status, Respondent Occupation, Husbands Education have very small frequencies for certain categories which needs to be corrected.

" Additionally, are there any specific reason for categorizing number of births, number of living children, and Survival of index child as they are presently. Can these variables be used as continuous?

" For Media Exposure the variable is not directly available in the DHS dataset. What is computation procedure of the variable "Media Exposure". Also, what is the meaning of the categories "no" and "yes". Does "Yes" includes partial exposure to media? Please add a section describing the computation and categorization procedure in methods.

" Variables like ethnicity and social segregation play a vital role in affecting the behaviors and decision related to child birth and spacing. Are these variables present in the dataset? If yes, why are these not included in the analysis.

" Prevalence is generally not reported in Percentage, it is therefore recommended that the authors report prevalence per 100 individual (denominator). Also, it is advised to mention the exact prevalence (count) in the figure.

" Figure 1 seems unnecessary. It can be deleted.

" Add the data source and year to the headings of all the Tables and Figures.

" The titles of all the Tables and Figures needs to be modified more meaningfully.

" In the section "Prevalence of Short Birth Interval" the statement, "From a total of 2111(weighted) women who had at least two consecutive live births in four pastoral regions of Ethiopia", the authors have mentioned 2111 as weighted women, which needs to be substituted for unweighted number of women.

" As the existing literature points out that birth spacing can vary across the reproductive age-group. It is therefore advised to use the age-adjusted prevalence rates in the analysis.

Discussion

" The statement "This finding is higher than ……and United States (35%)". As the population size, socio-economic and developmental levels of Ethiopia and United States is quite different, it is better not to compare the two in discussion section.

" Also, the word "This finding" is an unclear reference. Please modify as required.

" The statement "Thus, the prevalence of SBI is …..and non- pastoral regions of the country" looks repetitive.

" In reference to the statement, "This could be…….In addition, this variation could be explained by a difference in cut-off values used to determine SBI". What were the definitions of SBI previously used (cut-offs).

Limitations of the Study

Please add a section on the limitations of the study.

Conclusions

" What is Xaagu system? How will it improve the present scenario?

Style of tabulation and presentation: The manuscript will benefit with major changes in the style of presentation. I would recommend the following paper published in PloS One (which I personally find extremely structured), to help the authors improve the style of tabulation and presentation:

1. Goli, S., Moradhvaj, A. R., & Shruti, J. P. (2016). High spending on maternity care in India: What are the factors explaining it?. PloS one, 11(6).

2. McNay, K., Arokiasamy, P., & Cassen, R. (2003). Why are uneducated women in India using contraception? A multilevel analysis. Population studies, 57(1), 21-40.

Language Issues

It is quite understandable that the authors of the manuscript are not native English speakers. There are grammatical and English language errors throughout the manuscript. The manuscript can be benefitted from an extensive grammar and language check. It is advised to take help from a native English speaker in order to achieve the English standard of the article published in PloS One.

Plagiarism

Thirteen percent of the text matches 15 sources or archives of academic publications. It is, therefore, advised to change the wording of Introduction and Methods sections. In majority of the instances the references are provided, however, the wordings of the entire paragraph are similar in a couple of occasions, which needs to be revisited and changed. I am unable to mention the exact paragraph which needs revision as no line numbers are provided in the manuscript. Majority of the text is similar to the following articles and report:

1. Birhanu, B. E., Kebede, D. L., Kahsay, A. B., & Belachew, A. B. (2019). Predictors of teenage pregnancy in Ethiopia: a multilevel analysis. BMC public health, 19(1), 601.

2. https://dhsprogram.com/data/Guide-to-DHS-Statistics/Place_of_Delivery.htm

3. Kawo, K. N., Asfaw, Z. G., & Yohannes, N. (2018). Multilevel analysis of determinants of anemia prevalence among children aged 6-59 Months in Ethiopia: classical and bayesian approaches. Anemia, 2018.

4. Woday, A., & Ayesheshim Muluneh, C. S. D. (2019). Birth asphyxia and its associated factors among newborns in public hospital, northeast Amhara, Ethiopia. PloS one, 14(12).

Reviewer #2: Short Birth Interval is a critical determinant of both maternal and child health and is an issue of concern in the developing world. The topic of the paper is an interesting one. However, here are some review points that might help improve the present work.

1. Authors can leave out the data collection method of DHS from the abstract. More importance should be given in explaining the tools and techniques used in the present research paper.

2. Introduction lacks continuity and flow. First authors should address why SBI is an important issue, the global scenario and then discuss its pertinence to African countries and the study region. Discussion of explanatory variables either should be better placed or put in the methods part where explanatory variables are listed out.

3. The need for a community-level study in the pastoral regions should be highlighted.

4. Why have the authors given weighted frequencies? It is difficult to understand the actual sample number that was collected. Only weighted percentage estimates should be enough.

5. Table 1 and 2 are both of explanatory variables. They can be merged with some partition within the table.

6. Rather than elaborating the explanatory variables more emphasis should be given on prevalence of SBI.

7. Figure 1, 2 are not of publishable quality.

8. Results on multilevel regression needs to be rewritten narrowing it down to only the results the authors find pertinent to the objectives of the study.

9. Usually wealth index of the household, women’s education play a significant role in determining spacing and limiting decisions, why are these variables not significant in Table 4? Authors might want to add it in the discussion.

10. No ante-natal care variables are taken in the study. During ante-natal care, women are exposed to various materials on how to practice spacing and limiting for the next birth. The multilevel analysis has not controlled for this variable.

11. Sex of preceding birth might be a better explanatory variable for SBI, as many communities around the globe has a preference for male child. If the preceding birth was female, there might be a shorter birth interval for the next child.

12. Authors should revisit the variables they have taken for multilevel analysis based on multicollinearity. Eg: No. of live births and No. of living children capture similar aspects of reproductive choices. It will be advisable to generate a cumulative score that captures all these measures together or choose the more critical one for the analysis.

13. Breastfeeding duration variable needs further explanation to understand whether this is for the preceding birth or all births. Breastfeeding duration for the index birth might not explain SBI for the last 2 births.

14. Authors highlight all previous studies were individual level and their study considers community-level factors. It will be more effective if a few community level variables are taken in the multilevel analysis, such as health infrastructural support, sanitation and hygiene practices in the neighbourhood, etc.

15. In discussion, authors merely summarise their results and point them to be similar to other studies. Discussion should have more content on implications of their results and suggest some policy revisions based on the findings.

16. Tense of the manuscript needs critical revision. Grammatical errors need to be reviewed. English editing might be beneficial.

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PLoS One. 2020 Aug 26;15(8):e0237602. doi: 10.1371/journal.pone.0237602.r002

Author response to Decision Letter 0

25 Jul 2020

Dear Editors and reviewers,

Thank you for giving us the opportunity to revise our manuscript entitled “A Multilevel Analysis of Short Birth Interval and Its Determinants among Reproductive age Women in Developing Regions of Ethiopia” before decisions. The authors have intensively discussed and addressed the raised concerns of the editor, and reviewers using point-by-point response as stated below. The amendments made on the manuscript have been presented using track change in the second attachment titled “Revised Manuscript with Track Changes”

Point-by-point responses for the questions and suggestions raised by Reviewer #1

Adequate birth spacing fetches great health benefits to both Mother and Child. The topic of the present study is of great interest for improving the Maternal and Child health in pastoral region of Ethiopia. The authors have used data from Demographic and Health Survey, 2016 on women in reproductive age-group 15-49 years. The present study aimed to address both the individual and community-related factors for short birth interval on four pastoral regions of Ethiopia using multilevel logistic regression technique. The manuscript does not contain line or page numbers which makes it difficult to point out observations.

Therefore, I am mentioning the observations by sections in the manuscript.

Title

Q1. As the study is focused only on women in Child-bearing ages 15-49 years and not all women, the present title, "A Multilevel Analysis of Short Birth Interval and Its Determinants among Women in Pastoral Regions of Ethiopia" needs to be modified.

Response: We have revised it per raised constructive concerns of the reviewer.

Abstract

Q2. Avoid use of abbreviations in the abstract section.

Response: We have corrected it in the revised manuscript.

Q3." Please mention the four pastoral regions where the study was based.

Response: We have mentioned the four regions in the revised manuscript

Q4" What is the sample size included in the study?

Response: 2683 total sample size (388 from Afar, 1706 from Somali, 489 from Benishangul-Gumuz, and 100 from Gambella )

Q5 " Replace "independent predictor" with "predictor".

Response: We have replaced it.

Q6 " The statement "The statistical significance level was declared at a 95% confidence interval" can be dropped from the abstract.

Response: We have dropped as suggested by the reviewer.

Q7" The conclusion section needs to be strengthened, as the present one looks vague.

Response: We have revised it based on your important suggestion.

Q8" The statement, "government should encourage local communication channels to promote the health of women and children" is ambiguous in interpretation. What measures are suggested by the authors to promote the health of women and children.

Response: We have revised and incorporated in the revised manuscript.

Introduction

Q9" Paragraph 3 gives data related to Nigeria. Please provide similar data for Ethiopia.

Response: We have revised and incorporated data related to Ethiopia in the revised manuscript.

Q10" Also, total fertility rate is given per 1000 women. Please mention the units.

Response: We have revised and mentioned the units

Q11" In view of the statement "Like many other African countries, Ethiopia has shown so far little change in fertility reduction because of socio-cultural and religious factors." Can author give instances or examples of the cultural practices and religious factors responsible for higher fertility rates.

Response: We have addressed it in the revised manuscript.

Q12" Please mention the full form of the abbreviation SBI when first mentioned in the Introduction section.

Response: We have corrected it.

Q13" In view of the statement, "The Sustainable Development Goals (SDGs) of 2030, which combine multisystem strategies at global, regional and national levels, have three focuses to ensure healthy lives and promote wellbeing for all at all ages. Of these goals, one main objective is to reduce the neonatal mortality rate to lower than 12 per 1,000 live births [32-34] which is at a steady stage in developing nations." Can authors mention the present level of Infant and under five mortality in Ethiopia and Country specific goals to reduce IMR and U5MR (set by government or SDG).

Response: We have incorporated the required information based on your important suggestion.

Q14" In view of the statement "Moreover, studies conducted in Ethiopia were limited and inconclusive to show the determinants of short birth interval at the community level (i.e. they were assessed only individual related factors). Therefore, this study aimed to address both the individual and community-related factors for short birth interval on four pastoral regions of Ethiopia using multilevel logistic regression analysis which is the appropriate model to handle community-level factors of short birth interval" it would be better to re-write the need for the study by adding more literature stating the importance of studying SBI in pastoral regions and use of multi-level analysis.

Response: We have revised it in the revised manuscript per raised constructive concerns of the reviewer.

Q15" It is not mentioned anywhere what is the meaning of pastoral region and why is it important to study it. It is difficult to understand the use of the present study for international audience.

Response: We have revised this section in revised manuscript

Q16" Dedicate the last paragraph of the Introduction section to mention only the need for the study and study objectives

Response: We have revised this part as per the recommendation of the reviewer.

Methods

Data Source

Q17" What was the total sample collected by DHS in Ethiopia?

Response: a total sample size of 16,515 women aged 15–49 years was collected.

Q18" What are these nine regions and two city administrations included by the survey?

Response: We have corrected it in the revised manuscript. The nine regions are Tigray, Afar, Amhara, Oromia, Somali, Benishangul-Gumuz, Southern Nations Nationalities and Peoples Region (SNNPR), Gambella, and Harari), and the two city administrations are (Addis Ababa and Dire-Dawa).

Q19" The statements "All women of reproductive-age group were included in the first stage" and the information was collected from a nationally representative sample of 16,515 women aged 15-49 years" can be combined.

Response: We have corrected it as per suggested by the reviewer.

Q20" Is child birth outside of wed-lock is common in Ethiopia? If not, unmarried women sample needs to be removed from the analysis. Were any measures taken to do the same?

Response: We have revised it in the main document. Women who had never been married and those who have multiple births out of wedlock were excluded from the analysis.

" The author has used the term Pastoral region throughout the manuscript. There are a few questions which arise in my mind:

Q21 1) What is a pastoral region?

Response: we have revised this term and substituted pastoral region by developing region to make it clear for the audiences and we have briefly elaborated in the study area and data source section of the revised manuscript.

Q22 2) What four pastoral regions have been selected in the study and what are the reasons for specifically selecting these regions?

Response: We have revised this concern and incorporated all the required information in the revised manuscript.

Q23 3) What are the sample sizes from each of the regions? It would be better if the authors can provide an elaborate description on the sample selection.

Response: the authors corrected and incorporated the required data in the revised version of the manuscript. The sample sizes from each of the regions were 388 from Afar, 1706 from Somali, 489 from Benishangul-Gumuz, and 100 from Gambella

Q24 " How have the authors adjusted for "twins" birth?

Response: We have described in the revised version of the manuscript under study area and data source section.

Q25 Ethics Statement: Although the present study rests on a publically available dataset, still as the study included human subjects, it is advised to add a section of ethical consideration in the methods section after data source.

Response: We have revised this concern and included ethics statement in the main revised manuscript.

Study Variables-Dependent Variable

Q26" Use either of the two terms: Short Birth Interval or Optimal Birth Interval.

Response: We have corrected it in the revised manuscript

Q27" The authors have calculated the birth interval as the time that elapsed between the birth date of the first child and the birth date of the second child which I think is the standard procedure. It is however advisable to include a reference of the same. You can find a reference here: https://dhsprogram.com/pubs/pdf/CR28/CR28.pdf(section 1.2).

Response: we have cited the recommended reference in the revised version of the manuscript

Q28" I would recommend using "Croft, T. N., Marshall, A. M., Allen, C. K., Arnold, F., Assaf, S., & Balian, S. (2018). Guide to DHS statistics. Rockville: ICF" to check and revise the computation procedure of the variables included in the study.

Response: Thank you very much for your recommendation, we have considered this guideline for computation of this DHS dataset.

Independent Variables

Q29" I am concerned regarding the choice of predictor variables. The predictor variables can be clubbed into following sections, namely reproductive, behavioral, and child status. However, it is not clear that which conceptual framework has been utilized to select these predictor variables. Please mention the same.

Response: this concern is incorporated in the revised version of the manuscript under study variable section. we have developed the conceptual framework by reviewed literature published before. All the independent variables were selected based on those literature.

Q30" Also, the abstract suggests that a multilevel multivariable analysis has been used, it is not clear what are the levels included for the analysis and which variable was introduced at which level? Please provide a detailed description of the same.

Response: we have revised this issue and incorporated in the revised version of the manuscript under the independent variable section. Here in our study, independent variables were classified in to individual level variables and community level variables.

Q31" The explanatory variables included in the study can be correlated with each other. Are any measures taken to check for the same? If yes, include a section explaining the same in the methods section after variable description.

Response: we have corrected and included a section which describes this concern in the revised version of the manuscript.

Analysis Plan

Q32" Data Analysis section needs to be restructured as there are a lot of repetition.

Response: we have corrected this concern in the revised version of the manuscript

Q33" The section "In data with a nested structure……. mixed- effect logistic regression analysis was used in this study." needs to be re-written as the meaning is not clear.

Response: we have corrected this concern in the revised version of the manuscript

Q34" The statement "Data were weighted before analysis and merge and re-categorize to make suitable for analysis" looks ambiguous. Please elaborate.

Response: this concern is revised and incorporated in the revised version of the manuscript.

Q35" A section on Bivariate analysis needs to be added before proceeding to the multivariate analysis. It is evident that Table 4 provides a 2x2 contingency table for all the predictor variables, however, it would be great if you can include chi square/unadjusted odds ratio, and p-values in the table.

Response: we have addressed in the revised version of the manuscript. In this contingency table the frequency of each categories of predictors is putted to compute crude/unadjusted odds ratio, thus, including the crude/unadjusted odds ratio in this table will be redundancy. As we know all, to know statistically significant predictors in multivariable analysis, we can use either p value (i.e if the value less than 0.05) or confidence interval of adjusted odds ratio (i.e if the confidence interval not include unity or 1). Here in our case, we putted the AOR with its corresponding confidence interval to know statistically significant predictors. So, we believed that including the p value will not add any new information if the AOR with its confidence interval is given.

Q36" Authors state that they have utilized software R, it is not clear which part of the analysis or data visualization was done in R.

Response: We have used R for graphical presentation of data (i.e. Fig 1 and Fig 2), we have corrected this concern in the revised version of the manuscript.

Results

Q37" Table 1 and 2 provides the descriptive account of the variables included in the study. These two tables can be combined to form a single table using sub-headings in the table.

Response: we have revised it as suggested.

Q38" In both Table 1 and 2 the authors have mentioned Weighted frequency and percentage (unweighted) which needs to be substituted with unweighted frequency and weighted percentages.

Response: we have revised it as suggested. Based on the recommendation of the EDHS 2016 report, we have used sample weight for the frequency as well as for the percentage.

Q39" Include a row "Total" for the Table 1 and 2 or mention total sample size (N) in the table.

Response: we have corrected as suggested and we include total sample size(N) in the table.

Q40" The categorization of the explanatory variables needs an urgent attention, for instance variables like Religion, Respondent's educational Status, Husband's Educational Status, Respondent Occupation, Husbands Education have very small frequencies for certain categories which needs to be corrected.

Response: we have revised and recategorized those independent variables as suggested.

Q41" Additionally, are there any specific reason for categorizing number of births, number of living children, and Survival of index child as they are presently. Can these variables be used as continuous?

Response: we have revised this concern in the revised manuscript. We have used their continuous form for predictors number of births and number of living children based on your important suggestion but the predictor survival of index child is categorical by its nature ( i.e survived or not) in the EDHS data set, So we have used as it is.

Q42" For Media Exposure the variable is not directly available in the DHS dataset. What is computation procedure of the variable "Media Exposure ".

Also, what is the meaning of the categories "no" and "yes". Does "Yes" includes partial exposure to media? Please add a section describing the computation and categorization

procedure in methods.

Response: this concern is revised and incorporated in the revised version of the manuscript.

Q43" Variables like ethnicity and social segregation play a vital role in affecting the behaviors and decision related to child birth and spacing. Are these variables present in the dataset? If yes, why are these not included in the analysis.

Response: Social segregation was not present in the dataset; ethnicity is available in the dataset however there were no variability in respondents to the predictor ethnicity. Due to this we did not included it in the analysis.

Q44" Prevalence is generally not reported in Percentage, it is therefore recommended that the authors report prevalence per 100 individual (denominator). Also, it is advised to mention the exact prevalence (count) in the figure.

Response: The authors addressed this concern in the revised manuscript.

Q45" Figure 1 seems unnecessary. It can be deleted.

Response: we have deleted it as suggested

Q46" Add the data source and year to the headings of all the Tables and Figures.

Response: we have included the data source (i.e EDHS) and year (i.e 2016).

Q47" The titles of all the Tables and Figures needs to be modified more meaningfully.

Response: we have revised it as suggested.

Q48" In the section "Prevalence of Short Birth Interval" the statement, "From a total of 2111(weighted) women who had at least two consecutive live births in four pastoral regions of Ethiopia", the authors have mentioned 2111 as weighted women, which needs to be substituted for unweighted number of women.

Response: As we know, the allocation of the sample in the EDHS data to different regions as well as urban and rural areas were non-proportional, therefore based on the recommendation of EDHS 2016 report, all proportions and frequencies were estimated after applying sample weights to the data to adjust for disproportionate sampling and non-responses. We have explained the detail on data analysis section of the revised manuscript. Based on your suggestion we have included the unweighted number of women in the commented statement under “Prevalence of Short Birth Interval section” of the revised manuscript.

Q49" As the existing literature points out that birth spacing can vary across the reproductive age-group. It is therefore advised to use the age-adjusted prevalence rates in the analysis.

Response: we have revised it as suggested by the reviewer.

Discussion

Q50" The statement "This finding is higher than ……and United States (35%)". As the population size, socio-economic and developmental levels of Ethiopia and United States is quite different, it is better not to compare the two in discussion section.

Response: we have corrected it as suggested.

Q51" The statement "Thus, the prevalence of SBI is …..and non- pastoral regions of the country" looks repetitive.

Response: we have removed the repetition as suggested.

Q52" In reference to the statement, "This could be…….In addition, this variation could be explained by a difference in cut-off values used to determine SBI". What were the definitions of SBI previously used (cut-offs).

Response: Those previous studies considered SBI, if birth interval less than 36 months, whereas our study defined it as less than 24 months.

Q53 Limitations of the Study

Response: we have included limitation of study in the revised manuscript.

Conclusions

Q54" The statement, "government should encourage local communication channels to promote the health of women and children" is ambiguous in interpretation. What measures are suggested by the authors to promote the health of women and children.

Response: we have revised this section in the revised manuscript. The government should mobilize the community using health extension workers, women’s group like Women’s development Army (WDA).

Q55" What is Xaagu system? How will it improve the present scenario?

Response: we have revised this section in the revised manuscript. Xaagu or dagu system is a local means for news exchange. It is a social institution with particular purposes in the daily life of the Afar communities. It functions within a defined set of regulations and expectations, though the rules are necessarily unwritten. The law of dagu means that whenever you meet someone on the road who has travelled reasonably far, say from a nearby village, you are required to pause and

engage in a news exchange session.

Q56 Style of tabulation and presentation: The manuscript will benefit with major changes in the style of presentation. I would recommend the following paper published in PloS One (which I personally find extremely structured), to help the authors improve the style of tabulation and presentation:

1. Goli, S., Moradhvaj, A. R., & Shruti, J. P. (2016). High spending on maternity care in India: What are the factors explaining it?. PloS one, 11(6).

2. McNay, K., Arokiasamy, P., & Cassen, R. (2003). Why are uneducated women in India using contraception? A multilevel analysis. Population studies, 57(1), 21-40.

Response: Thank you very much for your recommendation, we have seen those recommended articles and revised the tabulation and presentation style of our manuscript in the revised version of the manuscript.

Language Issues

Q57 It is quite understandable that the authors of the manuscript are not native English speakers. There are grammatical and English language errors throughout the manuscript. The manuscript can be benefitted from an extensive grammar and language check. It is advised to take help from a native English speaker in order to achieve the English standard of the article published in PloS One.

Response: Thank you for your important suggestion. We have addressed in the revised version of the manuscript.

Plagiarism

Q58 Thirteen percent of the text matches 15 sources or archives of academic publications. It is, therefore, advised to change the wording of Introduction and Methods sections. In majority of the instances the references are provided, however, the wordings of the entire paragraph are similar in a couple of occasions, which needs to be revisited and changed. I am unable to mention the exact paragraph which needs revision as no line numbers are provided in the manuscript. Majority of the text is similar to the following articles and report:

1. Birhanu, B. E., Kebede, D. L., Kahsay, A. B., & Belachew, A. B. (2019). Predictors of teenage pregnancy in Ethiopia: a multilevel analysis. BMC public health, 19(1), 601.

2. https://dhsprogram.com/data/Guide-to-DHS-Statistics/Place_of_Delivery.htm

4. Woday, A., & Ayesheshim Muluneh, C. S. D. (2019). Birth asphyxia and its associated factors among newborns in public hospital, northeast Amhara, Ethiopia. PloS one, 14(12).

Response: Thank you for your crucial advice. The authors addressed this issue in the revised version of the manuscript.

Point-by-point responses for the questions and suggestions raised by Reviewer #2

Short Birth Interval is a critical determinant of both maternal and child health and is an issue of concern in the developing world. The topic of the paper is an interesting one. However, here are some review points that might help improve the present work.

1. Authors can leave out the data collection method of DHS from the abstract. More importance should be given in explaining the tools and techniques used in the present research paper.

Response: we have revised it as suggested

3. The need for a community-level study in the pastoral regions should be highlighted.

Response: we have addressed this issue in the revised manuscript.

4. Why have the authors given weighted frequencies? It is difficult to understand the actual sample number that was collected. Only weighted percentage estimates should be enough.

Response: Since, the allocation of the sample in the EDHS to different regions as well as urban and rural areas were non-proportional, therefore based on the recommendation of EDHS 2016 report, all proportions and frequencies were estimated after applying sample weights to the data to adjust for disproportionate sampling and non-responses. We have explained the detail on data analysis section of the revised manuscript.

5. Table 1 and 2 are both of explanatory variables. They can be merged with some partition within the table.

Response: we have merged it as suggested

6. Rather than elaborating the explanatory variables more emphasis should be given on prevalence of SBI.

Response: the authors have addressed this concern in the revised manuscript

7. Figure 1, 2 are not of publishable quality.

Response: we have corrected it based on the suggestions of you and reviewer #1 in the revised manuscript

8. Results on multilevel regression needs to be rewritten narrowing it down to only the results the authors find pertinent to the objectives of the study.

Response: we have tried to address it based on our objectives

9. Usually wealth index of the household, women’s education plays a significant role in determining spacing and limiting decisions, why are these variables not significant in Table 4? Authors might want to add it in the discussion.

Response: the authors addressed this concern. As you said that wealth index of the household, women’s education predictors of birth interval, in our study women’s education (category secondary education and above level) is significantly associated with short birth interval. But wealth index of the household not statistically significant.

Response: You are wright but this variable is not available in this data set.

Response: Thank you very much for your important concern. In our case sex of preceding birth is one of the important predictors of short birth interval that is women having female sex of the index child had 1.13 times greater risk of short birth interval compared to those women having male index children.

Response: we have considered the issue of multicollinearity in multivariable multilevel analysis and we have included a section described about this concern in the revised version of the manuscript.

Response: Breastfeeding duration is asked for the preceding index child and it is known that women who breastfeed their children for longer duration have a longer period of amenorrhea which results in postpartum infertility. So that it determines the birth interval of the next births of a woman.

Response: Thank you for your important suggestion, Variables like health infrastructural support, sanitation and hygiene practices in the neighbourhood not available in the EDHS dataset. However, variables like residence site, region, and cluster are available in the dataset. The authors included those available variables in the multilevel analysis. The detail is explained in the variables section of the revised manuscript.

Response: The authors tried to review this concern in the revised version of the manuscript

16. Tense of the manuscript needs critical revision. Grammatical errors need to be reviewed. English editing might be beneficial.

Response: Thank you for your important advice. The authors addressed this issue in the revised version of the manuscript.

Attachment

Submitted filename: Response to Reviwers.docx

Click here for additional data file.^{(35.2KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0237602.r003

Decision Letter 1

Srinivas Goli

30 Jul 2020

A Multilevel Analysis of Short Birth Interval and Its Determinants among Reproductive age Women in Developing Regions of Ethiopia

PONE-D-20-07800R1

Dear Dr. Birara,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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The revisions are satisfactory.

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0237602.r004

Acceptance letter

Srinivas Goli

14 Aug 2020

PONE-D-20-07800R1

A Multilevel Analysis of Short Birth Interval and Its Determinants among Reproductive age Women in Developing Regions of Ethiopia

Dear Dr. Aychiluhm:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Attachment

Submitted filename: Response to Reviwers.docx

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Data Availability Statement

Data underlying this study can be found at https://dhsprogram.com/data/dataset/Ethiopia_Standard-DHS_2016.cfm.

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PERMALINK

A multilevel analysis of short birth interval and its determinants among reproductive age women in developing regions of Ethiopia

Setognal Birara Aychiluhm

Abay Woday Tadesse

Kusse Urmale Mare

Mohammed Abdu

Abdusemed Ketema

Roles

Abstract

Background

Methods

Results

Conclusions

Introduction

Methods and materials

Study area and data source

Study variables

Dependent variable

Independent variables

Media exposure

Multi-collinearity

Data analysis

Descriptive statistics

Bivariable multilevel analysis

Multivariable multilevel analysis

Model building and comparison

Ethical consideration

Results

Descriptive statistics of the study variables

Table 1. Weighted socio-demographic, reproductive, behavioral and child status-related characteristics of study participants, EDHS,2016 [N = 2683].

Prevalence of short birth interval

Determinants short birth interval

Empty multilevel logistic regression model (Null model)

Table 2. Community-level variance of two-level mixed-effect logit models predicting short birth interval, EDHS 2016.

Multilevel multivariable logistic regression model (Full model)

Table 3. Multilevel multivariable logistic regression of the individual and community-related variables associated with short birth interval, EDHS 2016.

Discussion

Conclusion

Strengths and limitations of the study

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Srinivas Goli

Roles

Transfer Alert

Author response to Decision Letter 0

Decision Letter 1

Srinivas Goli

Roles

Acceptance letter

Srinivas Goli

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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