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. 2020 Jan 14;15(1):e0227218. doi: 10.1371/journal.pone.0227218

Determinants of change in long-acting or permanent contraceptives use in Ethiopia; A multivariate decomposition analysis of data from the Ethiopian demographic and health survey

Gedefaw Abeje Fekadu 1,2,*, Akinyinka O Omigbodun 3, Olumuyiwa A Roberts 3, Alemayehu Worku Yalew 4
Editor: Kannan Navaneetham5
PMCID: PMC6959602  PMID: 31935224

Abstract

Background

There has been an increase in the uptake of long-acting or permanent contraceptive methods (LAPMs) in Ethiopia. Identifying the factors associated with this change is important for designing interventions that will further accelerate the uptake. This study was done to identify components of, and factors associated with, changes in the use of LAPMs in Ethiopia.

Methods

Information about 16,336 married or in-union reproductive-age women were extracted from the 2005 and 2016 Ethiopian Demographic and Health Surveys (EDHS). Normalized weighting was used to compensate for disproportionate sampling and non-response in the survey. The two data sets were merged and analyzed using multivariate decomposition analysis.

Result

From 2005 to 2016, the use of LAPMs increased by 12.0 percentage points. Changes in the characteristics of women (compositional factors) were responsible for nearly 7.0% of the observed difference. Most of the change (92.0%) was attributable to differences in the effects of characteristics. Age, working status, woman’s occupation, concordance on the desired number of children between women and their partners, and a visit by health workers in the 12 months before the survey were all significantly associated with the change.

Conclusion

The contribution of variation in the survey population structure was not significant for the observed change. The change in the use of LAPMs was mainly due to behavioral changes among older, educated and working women, and women visited by health workers.

Introduction

Unintended pregnancy is a major global problem causing health, social and economic challenges among sexually active women. Globally, about 44% of pregnancies were unintended [1]. A multi-country analysis of DHS data from Sub-Saharan counties identified that 29% of married women had unintended pregnancy ranging from 10.8% in Nigeria to 54. 5% in Namibia [2]. The 2016 Ethiopian demographic and health survey (EDHS) report identified that 25% of births in Ethiopia were unintended (8% unwanted and 17% mistimed)[3]. The main reason for high level of unintended pregnancy in Africa is low contraceptive use. In addition, contraception in Africa is dominated by short-acting methods [4, 5]. The long-acting and permanent methods (LAPMs) such as intrauterine devices (IUD), implants, vasectomy, and tubal ligation, are known to be efficient and cost-effective interventions for reducing unintended pregnancies. LAPMs can be used for 3 or more years without visiting health facilities. But these methods are underutilized in developing countries [6–8].

The trend in LAPMs use is increasing slowly in sub-Saharan Africa (SSA) [4, 9–11]. Lack of knowledge among women, dependence on the provider for information and provider-bias were among the reasons cited for low utilization of these methods [9]. Contraceptive uptake increased up to nine-fold during the last three decades in Ethiopia [4, 12]. However, similar to other African countries, it is dominated by short-acting methods [1, 3, 13]. The 2016 EDHS report identified that only 10.0% of married or in-union reproductive-age women were using LAPMs [3]. Majority of these women were using implants [3]. On the other hand, studies in various parts of the country indicated that there is high demand for LAPMs [14–16].

The Ethiopian government targeted contraceptive prevalence (CPR) of 55% at the end of 2020. Long acting or permanent methods are expected to constitute 50% of the CPR [17]. The government and many other non-governmental organizations are implementing different interventions to increase LAPMs uptake. Reports indicate that most health facilities have the basic infrastructure to provide LAPMs. All contraceptives, including LAPMs are provided free [17]. Yet, LAPMs uptake is lagging behind the national target. Identifying the factors or drivers of the change is important to formulate appropriate policies and strategies important to accelerate the uptake. But there are no studies to identify whether changes in LAPMs use are due to change in population structure or due to public health interventions. Therefore, this analysis was done to identify factors associated with change in long acting or permanent contraceptives method use.

Methods

Data source

We analyzed the 2005 and 2016 EDHS data collected by the Central Statistics Agency (CSA). The surveys used a list of enumeration areas, used for the 2007 housing and population census, as the sampling frame. The surveys were designed to provide key indicators at the national and regional levels. The surveys used a two-stage stratified sampling technique. In both surveys, women aged 15–49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were interviewed. An interviewer-administered questionnaire was used to collect data. The details of the methodology; sampling technique, data collection, and data quality assurance are available from EDHS reports [3, 18].

A total of 29,753 reproductive-age women (women aged 15–49 years) were included in the two EDHS (14,070 in 2005 and 15,683 in 2016). From these, 18,468 (8,644 in the 2005 EDHS and 9,824 in the 2016 EDHS) were married or in-union. Women who were pregnant at the time of the survey (2,191), single, divorced and widowed women were excluded from the analysis. The reason for this is that information about contraceptive use among unmarried (never married, widowed or divorced) women is less reliable due to social desirability bias. The reason for this bias is that sexual activity among these women is taboo in Ethiopia. Unmarried women in Ethiopia are also less likely to use LAPM. Finally, 16,336 married or in-union reproductive-age women were included in the final model (Fig 1).

Fig 1. Schematic presentation of the selection of women included in the analysis to identify factors associated with change in LAPM contraceptive methods use in Ethiopia.

Fig 1

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Measurement

Outcome variable

The dependent variable for this study was long-acting or permanent contraceptive method use. In both surveys, women were asked if they were using contraceptives and they type of contraceptive. Based on that response, the outcome variable has two categories; using long-acting or permanent contraceptive methods (implant, IUD, vasectomy and tubal ligation), coded as “1” and not using long-acting or permanent methods (using short-acting methods or not using any method), coded as “0”.

Independent variables

Socio-Demographic Characteristics: Mothers’ age at the time of interview, residence, religion, educational status, mothers’ working status, sex of head of the household, occupation, wealth index and frequency of reading newspapers, listening to the radio and watching television (TV).

Fertility and Decision-Making Variables: Age at first cohabitation, the ideal number of children, number of living children, knowledge of ovulatory period, desire for more children and knowledge of fertility period.

Family Planning Program Exposure: Exposure to family planning messages on mass media and decision maker to seek health care. A woman was considered as “exposed to family planning messages on mass media” if she had read family planning messages in newspapers or magazines, or heard family planning messages on radio or TV in the preceding few months.

Data analysis

The study employed standard (two-component) multivariate decomposition analysis technique, which can be used to analyze differences between two groups or differences between two points in time [19]. Many public health studies used this technique of analysis to identify components of a change over time and identify factors associated with change [20–25]. The analysis decomposes the differences in two points of time into two components. The first component is the change due to variation in the survey population structure and the second component is the change due to change in public health and/or changes in the behavior of the survey population [26, 27]. The decomposition analysis is based on the standard procedure of decomposing differences in which the dependent variable is a function of predictors and regression coefficients, graphically represented as Y = F (Xβ).

For this analysis, the 2016 EDHS data was appended to the 2005 EDHS data using the “append” command in STATA. Since the variables in the two data sets were similar, no recoding of variables was done before merging. But after the two data sets were appended, some variables were recoded to create new categories using the recode command. Normalized weight was used to correct for disproportionate sampling and non-response in the DHS. Multicollinearity was checked using the correlation coefficient. Finally, multivariate decomposition analysis was done using the “mvdcmp” command of STATA 15.1. Before the multivariable decomposition analysis, chi-square test was done to check the presence of statistically significant difference in the distribution of women in the two surveys.

Ethical considerations

The 2005 and 2016 EDHS protocols were reviewed and approved by the National Ethics Review Committee of the Federal Democratic Republic of Ethiopia, Ministry of Science and Technology and the Institutional Review Board of ICF International. The data sets in STATA format were downloaded from the DHS Program after obtaining permission.

Results

Characteristics of married or in-union women

In both surveys, the majority of the respondents (88.6% in 2005 and 83.3% in 2016) were rural residents. Most women were not working at the time of the survey and had no formal education. There were significant differences in age at first marriage, ideal number of children and concordance on number of children among women in the two surveys (Table 1).

Table 1. Percentage distribution of selected characteristics of married or in-union reproductive-age women in Ethiopia from the 2005 and 2016 Ethiopian Demographic and Health Surveys.

Characteristics of women Percent of women in
2005 2016
Age*
    • 15–24
    • 25–34
    • 35–49
24.038.937.0
21.142.836.1
Place of residence***
    • Urban
    • Rural
11.488.6
16.583.5
Religion
    • Orthodox
    • Muslim
    • Other
46.331.821.9
41.633.624.8
Education status***
    • No formal education
    • Primary
    • Secondary or higher
78.115.26.7
62.127.610.3
Working status**
    • Working
    • Not working
74.225.8
68.531.5
Age at first cohabitation***
    • Less than 20
    • 20 or more
84.615.4
79.120.9
Ideal number of children**
      No child
      1–5
      6 or more
11.8
48.9
39.3
9.0
54.3
36.7
Concordance on number of children***
    • Both wants the same
    • Husband wants more
    • Husband wants fewer
    • Do not know
32.717.14.74.5
39.225.67.228.0
Visit by health worker
    • No
    • Yes
91.88.2
70.529.5
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Note: Chi-square significant at

*Significant at 0.05

**Significant at 0.01

***Significant at<0.001

Long-acting or permanent contraceptive methods use by selected characteristics

The use of long-acting and permanent contraceptive methods varied by socio-demographic characteristics of married or in-union reproductive age women in the two surveys. The change in long-acting and permanent contraceptive method use was positive in all categories of women. The use of long-acting and permanent contraceptive methods varied according to the fertility-related characteristics. Generally, a higher proportion of women in 2016 used long-acting and permanent contraceptive methods compared to 2005 (Table 2).

Table 2. Long-acting and permanent contraceptive methods use among married or in union reproductive-age women in Ethiopia and percent change by selected characteristics, 2005 and 2016 Ethiopian Demographic and Health Survey.

Characteristics of women Percent of women using LAPMs in Percent change
2005 (n = 7,918) 2016 (n = 9,127)
Age
    • 15–24
    • 25–34
    • 35–49
0.30.31.2
10.613.89.6
10.313.58.4
Place of residence
    • Urban
    • Rural
4.10.2
17.70.4
13.60.2
Religion
    • Orthodox
    • Muslim
    • Other
1.00.30.6
15.35.413.8
14.35.113.2
Education status
    • No education
    • Primary
    • Secondary or higher
0.30.93.7
10.910.917.2
10.610.013.5
Working status
    • Working
    • Not working
0.60.7
10.414.2
9.815.5
Age at first cohabitation
    • Less than 20
    • 20 or more
0.61.1
11.511.8
10.910.7
Ideal number of children
    • No child
    • 1–5
    • 6 or more
0.40.90.4
6.315.29.0
5.914.38.6
Concordance on number of children
    • The same
    • The husband wants more
    • The husband wants less
0.7 0.51.3
14.310.110.7
13.69.69.4
Visited by health worker in the last 12 months
    • No
    • Yes
0.5
1.7
10.913.3
10.411.6
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Decomposition analysis

Overall, the use of long acting and permanent contraceptive methods changed significantly by 12.0 percentage points from 2005 to 2016. About 7.0% of the observed difference could be ascribed to the characteristics of the women in the two surveys (compositional factors).

After controlling for the compositional change, 93.0% of the change in LAPMs use was due to the differences in the effects of specific characteristics rather than the structural composition of the two cohorts. The effects of age, working status, concordance by husband and wife on the desired number of children, and visit by health workers in the 12 months preceding the survey were significant contributors to the change in LAPMs use. Keeping all other factors constant, about 10.0% of the increase in LAPMs use was due to behavioral change among older women (aged 35–49 years). The effect of having higher education was also significant on LAPMs use, although this effect was small. Receiving higher education was responsible for about 1.5% of the change in LAPMs use.

The effect of the difference in number of children that the woman and her husband wanted was significant for the change in LAPMs use. A greater desire for more children by the man than the woman increased LAPMs use by 1.3%. Working at the time of the survey affected LAPMs use in 2016. Compared with working mothers, non-working mothers showed a significant contribution to the observed change in LAPMs use over the decade. Visit by health worker was the other variable whose effect was responsible for the change in long-acting and permanent contraceptive methods use. The effect of visit by health workers was found associated with 2.7% change in long-acting and permanent contraceptive methods use (Table 3).

Table 3. Decomposition of the change in long-acting and permanent contraceptive methods use among married or in union reproductive-age women in Ethiopia by selected characteristics, 2005 to 2016.

Characteristics of women Percent difference in LAPMs use due to
Characteristics (E) Coefficients (C) Total
Age (in years) at the time of the survey
    • 15–24
    • 25–34
    • 35–24
    • Overall
Ref.
-0.70.44.4
Ref.6.8–10.0*-43.9*
Ref.6.1–9.6–39.5
Age (in years) at first cohabitation
    • <20
    • 20 or more
    • Overall
Ref.0.50.3
Ref.-0.9–1.4
Ref.-0.4–1.1
Religion
    • Orthodox
    • Muslim
    • Other
    • Overall
Ref.2.60.34.3
Ref.-9.4*7.3*13.1
Ref. -6.87.6 17.4
Education status
    • No education
    • Primary
    • Secondary
    • Above secondary
    • Over all
Ref.1.5–0.1–1.6–6.1
Ref.-8.4**-4.6***-1.5***-10.7***
Ref.-6.94.73.1–16.8
Working status
    • Working
    • Not working
    • Overall
Ref.-0.7–3.9
Ref.4.25.2
Ref.3.51.3
The ideal number of children
    • No child
    • 1–5
    • 6 or more
    • Overall

  • Ref.-2.40.2
Ref.10.85.8–0.5
Ref.8.46.00.2
Concordance on the number of children
    • Both want the same
    • Husband want more
    • Husband want fewer
    • Overall
Ref.1.40.57.5
Ref.-1.3–2.2–15.8
Ref.0.1–1.7–8.3
The desire for more children
    • Want within two years
    • Want after two years
    • Other
    • Overall
Ref.-0.3–1.2–3.7
Ref.
-2.7
-3.7
-7.1
Ref.
3.0
4.9
-10.8
Visited by health worker
    • No
    • Yes
    • Over all
Ref.-0.5–5.4
Ref.-2.7–2.7*
Ref.3.2–8.1
Total 7.5 92.5 100.0
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Note

*Significant at 0.05

**Significant at 0.01

***Significant at<0.001

ref: reference, LAPM: long acting and permanent methods

Discussion

This analysis identified the presence of a significant change in LAPMs use in Ethiopia from 2005 to 2016. This finding was consistent with findings from DHS data in other sub-Saharan African countries which showed that long-acting reversible method use increased in Malawi and Zimbabwe from 2004 to 2016 [28]. The 2015 UN estimate for trends of contraceptive use identified that LAPMs use in East Africa increased from 0.1% in 1994 to 8.6% in 2015 [4]. Increased political will, donor support, activities of non-governmental organizations, public-private partnerships and the health extension programs may all have contributed to the increase in LAPMs use in Ethiopia [12, 29].

The change in LAPMs use due to compositional factors was not significant. The reason for this may be associated with the insignificant change in the structural composition of the population of women involved in the two surveys. For example, the proportion of women who attended secondary or higher education was almost the same in the two surveys. The reports on the two EDHS also support this observation [18, 30].

Most of the changes in LAPMs use were due to the change in the effect of different characteristics of the women. The effect of age, working status, concordance between the male and female partners on the number of children, and visit by a health worker in the 12 months before the survey were significantly associated with the change in LAPMs use. About 10.0% of the increase in LAPMs use was attributable to changes in LAPMs use by women aged 35 to 49 years, a finding in agreement with other recent reports from Ethiopia [31, 32]. This might be due to a desire by older women to limit the number of children they give birth to, making them more likely to use LAPMs rather than short-acting methods. These women may have reached the planned level of fertility.

We also found that having secondary education contributed 5.0% of the observed change in LAPMs use, similar to what had been reported from other studies in Ethiopia and Kenya [13, 33–35]. Information related to LAPMs may be more accessible to women with secondary-level education, or formal education may have enabled them to develop better information processing skills, which may translate to a greater understanding of family planning messages and use of LAPMs [36]. These educated women also had an increased likelihood of being more autonomous when it came to decisions related to contraceptive use [37–39]. About 4.4% of the change in LAPMs use in this study was due to a change in the proportion of mothers who were working at the time of the survey. Working mothers may prefer using LAPMs to reduce absenteeism from work as a result of an unplanned pregnancy. Working mothers may also be better exposed to family planning messages in the workplace than those who just stay at home. Better autonomy in decision making in this group may also contribute for their increased use of reproductive health services including contraceptives.

Another important factor for the change in LAPMs use was the effect of health workers’ visit. About 3% change in LAPMs use was due to the change in LAPMs use behavior among women who were visited by health workers. Studies in Ethiopia indicated that discussion about family planning with health workers was associated with increased LAPMs uptake [35, 40]. The reason for this might be that when health workers visit home, they are more likely to provide detailed information about LAPMs. The health workers may have chance to identify household level barrier for using these methods. In addition, women may be more comfortable to discuss about contraceptives at home [41]. Health care workers may have better time to counsel the mother when visiting home since health facilities are crowded in most cases. This study used the EDHS data, a nationally representative data with large sample size. The findings of the study may inform family planning programmers to strengthen home visit by health care workers to improve LAPMs uptake. The analysis did not consider program-related variables since only few of these variables were collected by the EDHS.

Conclusion

Long-acting and permanent contraceptive methods use among married reproductive age women changed significantly between 2005 and 2016. The contribution of the variation in the survey population structure was not significant for the observed change. Most of the change in LAPMs use was associated with changes in the behavior of specific groups of women. Specifically, the change in LAPMs use was due to the behavioral change among older, educated and working women. In addition, the behavioral change among mothers who were visited by health workers contributed significantly for the change in LAPMs use. Therefore, strengthening the ongoing home visit and girls’ education may have significant impact on LAPM uptake besides the other benefits these interventions had.

Acknowledgments

We would like to acknowledge The DHS program for allowing using the EDHS data set.

Data Availability

For this analysis, we used the 2005 and 2016 Ethiopian demographic and health survey data sets. The data was accessed from The DHS Program website (https://dhsprogram.com/data/available-datasets.cfm) for free. We do not have special access privileges to this data. All authors can access the data from this website. To get the data, authors should register and log in. While login, they requested to state the project title, co-researchers' name and email and a brief description of the study. After that, the researchers continue to select the country and the data set. Within a few days, he/she will get permission to download the data via email. After the permission, the researcher can log in and select the specific data with the format he/she wants.

Funding Statement

The authors received no specific funding for this work.

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Decision Letter 0

Kannan Navaneetham

7 Oct 2019

PONE-D-19-23062

Determinants of change in long-acting and permanent contraceptive methods use in Ethiopia; a multivariate decomposition analysis of data from the Ethiopian demographic and health survey

PLOS ONE

Dear Mr. Fekadu,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We would appreciate receiving your revised manuscript by Nov 21 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Kannan Navaneetham

Academic Editor

PLOS ONE

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[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Reviewer’s report

Title: Determinants of change in long-acting and permanent contraceptive methods use in Ethiopia; a multivariate decomposition analysis of data from the Ethiopian demographic and health survey

Version: Date: 17th September 2019

Reviewer: Samuel Bosomprah

Reviewer’s report

The paper sought to explain the change in LAPMs use over time. I believe that this is an important topic especially in developing countries where there is concern for population growth and its negative consequences on available resources and economic growth. The choice of decomposition analysis technique is appropriate to answer to the research question “why has LAMPs use change over time?”. The paper can be improved if the authors addressed the following concerns.

Major Compulsory Revisions: Yes

Introduction

Delete the first para of the introduction – it’s just a background. Begin the introduction with a clear declarative statement of the problem. The rest of the sentence in the paragraph should be an elaboration of the problem using global and sub-Saharan statistics.

Para 1 (problem statement):

Rewrite lines 57 to 71 into para 1 as follows:

“Unintended pregnancy is a major global health problem among sexually active women. <describe and="" global="" lapms="" or="" statistic="" sub-saharan="" the="" uptake="" use="" using="">. The long acting and permanent contraceptive methods (LAPMs) such as intrauterine devices or IUD, and implants are known to be efficient and cost-effective interventions for reducing unintended pregnancies. Several studies have identified <knowledge about="" lapms="">

Para 2 (justification/significance/rationale/importance): This para should describe why it is important to carry out this study. In otherwise, argue for the study. You may beef up lines 72 to 79 to reflect this thinking.

Para 3 (aims/research questions/objectives/hypotheses (if any): Conclude the introduction with the aims or objectives of the study. And indicate the potential impact of the findings from the study. Lines 80 to 88 could remain as is.

Methods

Data analysis: A number of decomposition analysis techniques exist. The authors should acknowledge same and describe which of these is implemented in the mvdcmp command. Recheck the equation in line 151.

Results

1. The tables are fragmented. The authors should collapse Tables 1 to 4 into one or two (because independent variables are many) tables. See Table 1 of the paper by Bosomprah et al 2014 (ref 23 in the current paper). In this table, the population structure was presented in the same table as the prevalence. Your last column should be maintained as the Percentage change. Include the “total” row for all tables.

2. The potential factors/drivers are too many. Authors should consider including those found in the literature to be predictors of LAPMs use or uptake. For example, I am not sure whether “sex of head of household” is a predictor of LAPMs use. Also, how is working status different from occupation? Are they not measuring the same thing? Some variables can be combined into a derived variable that makes sense. For example, can we combine: Visited by health worker in the last 12 months; Visited health facility in the last 12 months etc. I can’t see an important predictor like “knowledge about LAPMs”

3. Delete line 174 - this style is thesis report. Rather comment and put the table reference in bracket.

4. Authors should be consistent in the number of decimal places. Authors should keep the percentages in 1 decimal place in the table and the main text.

5. The comments on Table 5 (Decomposition analysis) are confusing. For example, Where are the E and C in Table 5 -as I indicated earlier Authors should include the “Total” column which should have the total E and C. Then the “coeff” are the part of the total E or C which are due to the respective predictors, also translated into percentages.

Discussion

The authors should discuss the strength and limitations of the study. They should also discuss the impact of the findings as well as prescription of future work.

Discretionary Revisions: Yes

Level of interest: An article of importance in its field

Quality of written English: Authors should proofread and correct for grammatical errors

Statistical review: No, I am a statistician and have reviewed the statistical methods used.

Declaration of competing interests: I declare that I have no competing interest

Reviewer #2: COMMENTS FOR AUTHORS/ RESEARCH TEAM

Introduction

This is a good paper and if the research team makes some changes, I think it will be worth publishing.

The authors need to consider having the manuscript edited before submission. There are several errors related to grammar and punctuation that would be caught by an editor and will also improve readability.

At some point in the introduction, the authors should provide a definition for Long acting and permanent contraceptive methods (LAPMs). They provide examples, which does help to make a distinction, but a definition will be more appropriate, I think.

A definition will also help the authors make a case for why LAPMs are superior to other forms of modern contraceptives. I assume the authors are working on the idea that LAPMs are better for efforts to lower fertility rates in Ethiopia.

The authors should decide on the preferred acronym and then stick with it. Throughout the paper, they go between LAPM and LACPM.

Methods

The authors should consider providing a definition of women who are of reproductive age (perhaps base it on the Ethiopian government's policy on national fertility). It is important to provide such a definition as that appears to be the primary inclusion criteria for data.

For example, the women's survey component of DHS data typically includes women from 15-49 years as is the case with Ethiopia. That age range falls into the reproductive age range. The authors need to confirm if this matches their notions of reproductive age ranges.

The authors chose to limit their data to married women or women cohabiting with a partner, excluding single, divorced and widowed women. I think an explanation is in order here. Contraceptive use is not something that is limited to married women and women in long-term partnerships. I can understand excluding women who are pregnant at the time of the survey, but why exclude the others? Are not the sexual health and reproductive needs of women not living with a permanent partner, pertinent to understanding the use of LAPMs?

The last paragraph of the data analysis section could be shortened a bit. For example, state from the outset that STATA was the preferred analytical software, and then note that 2005 data was appended to 2016 data to create the analysis data. Don't think there is a need to go into detail about how the data was analysis data set was created and what commands were relevant for that process.

Results

I would recommend for this manuscript the authors place the tables at the end of the document rather than incorporate them within the text. It will help improve readability I believe at this stage of the review (minor issue).

The authors use too many decimal places in their tables, particularly in what is Table 05. I can understand having several decimal places for regression coefficients, particularly if the value is small (3 decimal places should be adequate), but for percent values, these can be limited to one or two decimal places.

Consider merging Table 01 and Table 02 and within the table distinguish between the three broad categories of explanatory variables (independent variables), rather than have a separate table for demographic characteristics, a separate table for fertility-related characteristics and a separate table for family planning exposure through media. It will be a long table, but it will improve the way in which readers navigate the paper.

Similarly, the authors should consider merging Table 03 and Table 04. As suggested above, within this table the authors would distinguish between the three broad categories of independent variables.

(If the authors are feeling adventurous, it may even be possible to merge Table 01, 02, 03, and 04 into one table that is both wide and long. This table would have one major column that would be characteristics by year and then there would be two sub-columns for 2005 data and 2016 data. Similarly, there would be a larger column for Percent LAPM use per year and then sub column heading for changes in LAPM use).

Overall, the authors need to be careful about the column headings and subheadings they are using for their tables. For example, in Table 03, column headings are simply 2005 N=7918 and 2016 N=9127, when the context suggests that the authors mean, percent of LAPM use in those particular years.

Another example, in Table 05 which shows the results from the decomposition analysis, the first column is labeled as ‘LAPM contraceptive method use'. I imagine the authors simply mean variable for this particular column heading.

Lastly, does STATA not provide the totals for each variable when looking at differences in characteristics and differences in coefficients/effects? For example, there should be a total age (in years) when reporting differences in characteristics and differences in effects. There should also be an overall total for each column in Table 05. That is there should be totals reported for all differences in characteristics and differences in effects, this would correspond to what was reported in paragraph 2 of the sub-section on decomposition analysis in the results section.

Discussion

My only issue with the discussion section at present is that the authors should also consider the practical significance of their findings. Statistical significance is certainly important and worth noting and explaining. However, LAPMs in the context of a country like Ethiopia is more than whether a factor like education explains a portion of the change in use behavior. For example, the authors note that secondary education explains about 1% of the observed change in LAPM use. What does that mean for policy efforts to increase the use of LAPMs? Does it mean a focus on secondary education? But then again, though significant, a 1% change, appears to be practically small and will have little practical value for any kind of policy efforts. I am hoping that hate authors can engage these kinds of thoughts for their discussion section.

 </knowledge></describe>

**********

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Reviewer #1: Yes: Dr Samuel Bosomprah

Reviewer #2: No

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PLoS One. 2020 Jan 14;15(1):e0227218. doi: 10.1371/journal.pone.0227218.r002

Author response to Decision Letter 0

24 Oct 2019

We revised the manuscript based on the editor and reviewers comments. A point by point response is uploaded in the editorial manager.

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Decision Letter 1

Kannan Navaneetham

3 Dec 2019

PONE-D-19-23062R1

Determinants of change in long-acting and permanent contraceptive methods use in Ethiopia; a multivariate decomposition analysis of data from the Ethiopian demographic and health survey

PLOS ONE

Dear Mr. Fekadu,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We would appreciate receiving your revised manuscript by Jan 17 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

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Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Kannan Navaneetham

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #2: This is a good paper worth publishing. The authors outline the fact that LAPM use is on the rise in Ethiopia but at less than desired rate. Furthermore, the Ethiopian public health community views the use of LAPMs as a viable, effective and safe mechanism for helping the population address the issue of unwanted pregnancies. They employ decomposition analysis, among other analytical methods, in an attempt to identify what sociodemographic factors are strongly associated with the changes in LAPM use among married/cohabiting women. Broadly, the findings point to the effect of certain factors as opposed to the structural composition of the population sampled. I believe such information is useful to those with social and public health interests on the matter of family planning and fertility.

Please see below for my comments about issues that may help to improve the quality of the manuscript further:

Introduction

I am not sure I agree with the framing in the first sentence. Are unintended pregnancies an actual public health issue? Certainly, they are a social issue and perhaps an economic one. But a public health one I am not sure about that. Perhaps there are serious public health effects that arise out of a high rate of unintended pregnancies, but I am not sure characterizing the pregnancies themselves as a health issue is wise.

What is the national target for LAPMs (Line 80)? I think it would be a good idea to state this national target if it is known or cite the policy statement that makes it a national target.

The introduction is missing a statement of aims and objectives. Traditionally, introductions will conclude with a paragraph illustrating what is intended for the rest of the manuscript. That appears to be missing in this revision. The authors get at that a bit with the last line of the paragraph (Line 84).

Methods

Personally, I believe the authors could do away with paragraph 1 in the methods or at least condense it a bit. The survey techniques employed for DHS are widely known. I think the authors could get by, by calling attention to the final reports which do a more detailed description of survey methods.

Line 100 - 106

Authors should consider providing a citation in support of the point of social desirability bias. Also, what makes the authors confident that married women or women in unions are not subject to social desirability biases when considering the issue of contraceptive use? There is an argument to be made for limiting the analysis to married/ women cohabiting with a partner, it is just not clear, at least in the text of the manuscript. The responses that the authors provided to my comment from the first review, when I raised a similar issue, could serve as a means of bolstering the argument here.

The figure legend should be placed underneath the figure. Line 107 - 109

I can appreciate the authors wanting to describe the analytical methods the chose to use. But a step-by-step descriptor of STATA commands and the way they are applied is not necessary, at least in the context of this paper. For example, where the authors write, “First the 2005 EDHS data was opened.” And then later write, “Then, the 2016 EDHS was opened.” All of that is unnecessary in my view. All those lines can be condensed to something like, “2016 EDHS data was appended to 2005 data, using the ‘append’ command”. If the authors insist on providing detail about their STATA coding choices, then perhaps consider submitting the annotated STATA do file as a supplement to be included in an appendix.

Line 166 - 167, “… and did not attend formal education.” This part of the sentence is confusing. Do the authors mean that the sampled women had no formal education or that they were not enrolled in school or some other kind of formal education at the time of the survey? I think it is the former.

In Table 01, the authors present results from the chi-square analysis. However, they make no mention of the intention to do this type of analysis in the methods section of their manuscript. Chi-square is a good choice in this case, but the authors need to explain its use in the methods.

Additionally, as a means of simplifying the table, why don’t the authors just summarize the chi-square findings in a manner similar to Table 03 (i.e., show the statistically significant findings using asterisk).

I recommend the authors take a look at Table 02. From the table, it is clear that more women are using LAPMs in 2016 than were using in 2005. However, when breaking this down by age categories the change is not as large as you do see in other categories. For 'age' we see a percent change from 2005 to 2016 of about 1.0 while for all the other variables (i.e., residence, religion, etc.) we are seeing percentage changes by categories that are very high. Why does the break down by age not account for these fairly large changes, is it an error?

Also, for Table 2 it would be a good idea to have a row at the bottom that accounted for all the women in the sample. That is the information provided in Lines 184 - 185 in the section on decomposition.

Line 226 - 227

The sentence beginning with, “About 10% of the increase…”, is confusing.

Line 228 - 229

I am not convinced by this argument, not that women in the 35-49 age bracket may want to have fewer children. But that the authors don’t put forth an explanation. Why would women in that age bracket seek fewer children on average?

Line 232 - 242

I think citing some sources may help to strengthen the authors’ arguments here. I assume that there are documented studies or interventions showing that women with an education are more likely to use LAPMs or modern contraceptives in general. For example, in line 238 where the authors suggest that LAPMs may help make Ethiopian women more economically productive, I am confident that there are economic studies demonstrating that women with a better grasp on their fertility, are more economically productive. Citing something like that gives the point the authors make in this paragraph more credibility and moves their arguments from the area of speculation.

Line 243 - 256

Similar to my comment above, I am also confident that there are interventions and studies detailed in the literature which demonstrate that some kind of home visit by some kind of medical provider/ health worker, can serve to alter behavior towards LAPMs. Citing such studies in support of the arguments here strengthens the paper in my view.

Line 253 - 256

I appreciate that the authors making this inclusion into the paper. I would suggest that the authors resist using such definitive language. Say, “The findings from this study may inform” as opposed to, “The findings from this study will inform.” There is no guarantee that policymakers will take up your work.

Did the authors remove their description of study limitations?

Suggestions for Discussion

Are there interventions that could benefit from the results of your analysis? If there are some on going on some planned, it may help to mention them in the discussion. Or the authors could suggest an intervention based on their findings, as something that merits further research.

Another potential issue of discussion is the rate of LAPMs among married men/ or men cohabiting with women. It is not the focus of your paper. However, if the argument is about informing policymaking and filling in gaps in our understanding, then it may be useful to bring up men’s use of LAPMs particularly vasectomy. The authors could bring it up in the context of future studies that need to be done in the area.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

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Decision Letter 2

Kannan Navaneetham

16 Dec 2019

Determinants of change in long-acting or permanent contraceptive methods use in Ethiopia; a multivariate decomposition analysis of data from the Ethiopian demographic and health survey

PONE-D-19-23062R2

Dear Dr. Fekadu,

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Acceptance letter

Kannan Navaneetham

3 Jan 2020

PONE-D-19-23062R2

Determinants of change in long-acting or permanent contraceptives use in Ethiopia; a multivariate decomposition analysis of data from the Ethiopian demographic and health survey

Dear Dr. Fekadu:

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Associated Data

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    Supplementary Materials

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    Data Availability Statement

    For this analysis, we used the 2005 and 2016 Ethiopian demographic and health survey data sets. The data was accessed from The DHS Program website (https://dhsprogram.com/data/available-datasets.cfm) for free. We do not have special access privileges to this data. All authors can access the data from this website. To get the data, authors should register and log in. While login, they requested to state the project title, co-researchers' name and email and a brief description of the study. After that, the researchers continue to select the country and the data set. Within a few days, he/she will get permission to download the data via email. After the permission, the researcher can log in and select the specific data with the format he/she wants.

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