Skip to main content

Four in ten married women demands satisfied by modern contraceptives in high fertility sub-Saharan Africa countries: a multilevel analysis of demographic and health surveys

Abstract

Background

Demand satisfied with modern contraceptive can be seen on both a health and economic level. Additionally, family planning helps to regulate fertility, prevent unintended pregnancies and their consequences. Thus, the aim of this study was to identify the magnitude of demand satisfied with modern contraceptive among married/in-union women in ten high fertility sub Saharan African countries.

Methods

Recent Demographic and Health Surveys that included a weighted sample of 43,745 women of reproductive age provided the data for this study. All statistical analyses were conducted once the data had been weighted, and Stata version 16.0 was used. A multilevel mixed-effect binary logistic regression model was fitted. To determine statistically significant individual and community-level factors associated with demand satisfied for modern contraceptive, odds ratios with a 95% confidence interval was generated. A p-value less than 0.05 was declared as statistical significance.

Results

Overall, demand satisfied to use modern contraceptive in high fertility sub-Saharan Africa countries was 39.53% (95%CI: 39.06, 39.98). Women aged 25–34 (AOR: 1.34, 95%CI: 1.26, 1.42) and 35–49 (AOR: 1.28, 95%CI: 1.20, 1.38), women education: primary (AOR: 1.35, 95%CI: 1.27, 1.44) and secondary (AOR: 2.05, 95%CI: 1.90, 2.21), husband education: primary (AOR: 1.26, 95%CI: 1.18, 1.35) and secondary (AOR: 1.54, 95%CI: 1.43, 1.66), husband residence (AOR: 1.75, 95%CI: 1.60, 1.91), media exposure (AOR: 1.22, 95%CI: 1.15, 1.29), wealth index: poorer (AOR: 1.1, 95%CI: 1.02, 1.19), middle (AOR: 1.18, 95%CI: 1.08, 1.28), richer (AOR: 1.37, 95%CI: 1.26, 1.49) and richest (AOR: 1.34, 95%CI: 1.56, 1.89), number of children: 4–6 (AOR: 0.48, 95%CI: 0.43, 0.55) and above 6 (AOR: 0.39, 95%CI: 0.29, 0.59), perceived distance to the health facility not big problem (AOR: 1.11, 95%CI: 1.04, 1.15), urban residence (AOR: 1.18, 95%CI: 1.10, 1.27), high community level poverty (AOR: 0.85, 95%CI: 0.74, 0.97) were significantly associated with demand satisfied for modern contraceptives.

Conclusion

Only four in ten married reproductive age women demands satisfied with modern contraceptives in high fertility Sub Saharan African countries. Modern contraceptives should therefore be more widely available, especially in rural areas and for those living away from health facilities. Also, increasing media exposure and education, providing financial support, and making contraceptive access easier for married women from poor households are important interventions that need to be put in place.

Peer Review reports

Background

Providing voluntary family planning counseling and services during pregnancy, childbirth, and postpartum periods is a crucial means of protecting women who are postpartum and post abortion and reducing unintended and closely spaced pregnancies [1, 2]. Through using family planning, it is possible to prevent 70% of maternal and 58% of under-five deaths by extending birth interval [3]. Additionally, it helps for child growth and development [4], promotes women’s autonomy in health care utilization, education, and empowerment in workforce [5,6,7], and can reduce 40% of unintended pregnancies [8]. Even though family planning has the aforementioned purposes, more than 200 million women in developing countries are still seeking to use contraceptives [8]. In 2017 one out of every ten married/in union women worldwide and one in five in Africa lacked access to family planning [9].

Despite the fact that access to family planning is vital for health and development programming, in sub-Saharan Africa and South Asia, the pace of these gains has slowed over the past two decades [10, 11]. The lower demand satisfied for modern contraceptive methods had multiple negative consequences, such as unwanted pregnancies, which in turn lead to maternal mortality, prenatal depression, poor child development and restriction of women from education, and work [12,13,14]. The Anderson-Newman behavioral model for accessing and using health services assumes that each individual's utilization of health services depends upon their predisposing factors (such as age, education), enabling factors (such as income, availability or supply of service), and need factors [15,16,17]. Different factors such as lack of trust in Western medicine, low socioeconomic status, proximity of family planning clinics, and lack of knowledge about modern contraceptives have all contributed to lower utilization of modern contraceptives in Africa [18, 19].

Worldwide, 214 million women had unmet need for family planning [20]. According to the world’s 2017 family planning reports, the international modern contraceptive satisfied was 78% and in Africa it ranged from 46.5% to 56% [21, 22]. Many strategies such as the 2030 Sustainable Development Goal (SDG 3 about good health and wellbeing, SDG 5 about gender equality and women empowerment), the 2010 Every woman Every child Global initiatives, engagement of 120 million additional modern contraceptive users from 69 poorest countries by the year 2020 have been implemented to minimize the deaths of women, children, and adolescents [23,24,25]. Beside these important initiatives had been implemented, demand satisfied for modern contraceptive methods remained an important but continued to be less studied issue in the high fertility sub-Saharan African countries [21, 26].

Modern contraceptives have been studied from different perspectives, such as intention to use [27, 28], and utilization [6, 24, 29]. Additionally, studies were conducted within SSA on mDFPS [22, 25, 30]. However, these studies did not consider the community level variables such as community level education, community level poverty, and community level media exposure to predict mDFPS. Moreover, to the investigators knowledge, studies that combine specific high fertility countries in SSA have not been carried out to understand why married/ in union women in those specific high fertility countries have a low mDFPS. Hence, this study tried to fill this gap by using a different method of statistical analysis called multilevel mixed effect analysis, which considers both individual and community level factors.

Once the mDFPS and factors associated with it are known, interventions aimed at the family planning had showed that improvements in maternal and child health, the physical and economic wellbeing of women and their families as well as for the countries [4, 8, 22]. Assessing the actual use and associated factors of mDFPS in the high fertility sub Saharan African countries using a mixed model approach generates powerful information that triggers policy makers. Aside from improving the health of women and children, evidence-based strategies should be designed to maintain population growth. Therefore, this study tried to assess the magnitude of mDFPS and associated factors among married/in union women in high fertility sub-Saharan African countries.

Methods

Study design and settings

A community-based cross-sectional survey was conducted between January 2010 and December 2018 among reproductive-age women in high fertility countries in SSA. The survey was conducted in Niger, Democratic of Republic Congo, Mali, Chad, Angola, Burundi, Nigeria, Gambia, and Burkina Faso. These countries were selected because they are the top ten countries with high fertility rates in SSA, with fertility rates above 5.0, a value that is higher than the rate of 4.44 in Africa and 2.47 in worldwide [31]. Despite Somalia being one of the top ten high fertility countries, the country has no DHS data and excluded from the analysis.

The data for these countries were obtained from the official database of the DHS program, https://dhsprogram.com after authorization was granted via online request by explaining the purpose of our study. We used the woman’s individual record (IR file) data set and extracted the dependent and independent variables. DHS is a nationally representative household survey that is conducted across low and middle-income countries every five years. ICF implements the DHS Program, which aims to collect, analyze, and disseminate data about population, health, and nutrition, as well as use these data for planning, policy-making, and program management.

It has been an essential data source on issues of reproductive health in low and middle income countries as it gathers data on a number of reproductive health issues [32]. A two-stage stratified sampling technique was used; a total weighted sample of 43,745 married/ in union reproductive age women were included in the study (Fig. 1).

Fig.1
figure 1

schematic presentation for demand satisfied for modern contraceptives among reproductive age women in high fertility sub-Saharan Africa countries [33]

Study variables

Demand satisfied for modern contraceptives among married or in union reproductive age (15–49 years) women was the dependent variable. As part of this measure, women who reported using modern contraceptive methods like female sterilisation, male sterilisation, pill, intrauterine device (IUD), injectables, implants, male condom, female condom, emergency contraceptives or lactation amenorrhea methods were considered as demand satisfied by modern methods. Demand satisfied was computed using the revised definition of demand satisfied for modern contraceptives in the Demographic and Health Survey (DHS). The calculations were carried out using modern family planning methods as nominators, which are considered as met needs. Unmet needs include those who need modern contraceptive methods for spacing and/or limiting but cannot obtain them, as well as those who use traditional methods. We used the total demanded as the denominator (sum of met and unmet needs). The demand satisfied rate is equal to \(\frac{met need \times 100}{unmet need+met need}\) [33]. Independent variables grouped under the individual, household and community level were included. The individual level factors were age, occupation, educational level, wealth index, media exposure, number of children, knowledge about family planning. Accordingly, age was grouped as 15–24, 25–34, and 35–49. Occupation was coded as working and not working. No formal education, primary education, secondary and higher education were the categories for highest educational level for the mother and her husband. In DHS wealth index was developed by principal component analysis using durable assets ownership, housing characteristics and access to utilities. Finally the wealth index was recoded as poorest, poorer, middle, richer, and richest. Less than five and five and above were categories for household members, number of children in the household was categorized as 0, 1–3, 4–6, and above 6, sex of household head was grouped as male or female. Knowledge about family planning was coded as ‘yes’ for those women who knows about family planning and otherwise ‘no’. Those women who were either reading newspapers/magazine, or listening radio and watching television less than once a week/at least once a week were considered as having media exposure whereas those women who had not either reading magazine/ newspaper or listening radio/ television at all was considered as having not media exposure. The community level variables were place of residence, countries, community level education, community level poverty, community level media exposure, and distance to the health facility. Thus, place of residence (urban, rural), countries, distance to the health facility (big problem, not big problem) variables were analyzed based on their categorization in the DHS [34,35,36,37]. The community level poverty, community level education and community level media exposure were generated by aggregating the individual level factors independently at cluster level and finally, were categorized as high if the proportion is ≥ 50% and low if the proportion is < 50% based on the national median value since these were not normally distributed [38].

Modeling approaches

A multilevel logistic regression model was used to identify the association between the individual and community level factors with demand satisfied for modern contraceptive methods. STATA version 14 command “melogit” was used in fitting the models. The data was weighted (v005/1000000) throughout the analysis to ensure that the DHS sample was a representative sample and to obtain reliable estimates and standard errors before data analysis.

The first step was a graphical representation of the demand for modern contraceptives among reproductive age women. Overall, a total weighted sample of 44,052 reproductive age women were included in this study.

The second step was a bivariable analysis that calculated the proportion of demand satisfied for modern contraceptives across the independent variables with their p-values. All the variables having a p-value less than 0.2 in bivariable analysis were used for multivariable analysis. For the multivariable analysis, adjusted odds ratios with 95% confidence intervals and a p-value of less than 0.05 were used to identify statistically significant factors associated with demand satisfied for modern contraceptives. In the final step of the analysis, a multilevel logistic regression analysis comprising fixed effects and random effects was conducted.

The results of the fixed effects of the model were presented as adjusted odds ratio (AOR) while the random effects were assessed with intra-class correlation coefficient (ICC) [39]. Accordingly, four models were fitted; null model (model 0) which shows the variations in the demand satisfied on modern contraceptives in the absence of any independent variables. Model II adjusted for the individual-level variables, Model III adjusted for the community level variables, and model IV adjusted for both individual and community level variables [39, 40]. Correspondingly, model fitness was done using the deviance (-2 log likelihood). Variance inflation factor (VIF) was used to check for multicollinearity among independent variables in which the result showed no multicollinearity (mean value for the final model = 1.38).

Results

Sample characteristics/Individual and community level characteristics of reproductive age women

In this study a total weighted sample of 43,745 reproductive age women were participated. The majority (42.99%) of the study participants were in the age group of 25–34 years with a mean age of 31.14 ± 7.85 years. Of the study participants, 44.56% of the women had no formal education. Most (70.12%) of the women had work. Among the women surveyed, 87.93% of the household head were males. Of the study participants, 62.11% were from five and more household members. More than half (54.32%) of the women were from community having low proportion of education. With regard to community level poverty, most (88.16%) were from communities having low proportion of poverty (Table 1).

Table 1 Individual and community level characteristics of study participants in high fertility sub Saharan Africa countries (n = 43,745)

The overall magnitude of demand satisfied for modern contraceptive methods in the high fertility countries in sub Saharan Africa was 39.53% (95%CI: 39.06, 39.98). The highest (48.93%) mDFPS methods was in Burundi and Chad scoring the lowest (19.6%) prevalence (Fig. 2).

Fig. 2
figure 2

Magnitude of demand satisfied for modern contraceptives in high fertility sub-Sahara African countries

Random effects (measure of variations) results

The null model in the random effects, revealed a statistically significant difference in the likelihood of demand satisfied for modern contraceptive methods with a community variance of 49.3%. Additionally, the intra-class correlation coefficient (ICC) in the null model showed that 13.0% of the total variability of demand satisfied for modern contraceptive accounted for differences among clusters. Further evidence of variation in the demand satisfied for modern contraceptive techniques was provided by the median odds ratio. Accordingly the odds of demand satisfied for modern contraceptives was 1.24 times higher among women of higher cluster of demand satisfied for modern contraceptives than women within lower cluster of demand satisfied for modern contraceptives. In terms of model comparison, model three was selected as a final model since it has the lowest deviance (48,857.554) (Table 2).

Table 2 Multilevel analysis of factors associated with demand satisfied for modern contraceptives among reproductive age women in high fertility sub Saharan Africa countries (n = 43,745)

Fixed effects (measure of associations) results

Table 2 demonstrates binary logistic regression for factors associated with mDFPS. After adjusting for individual and community related factors of demand satisfied for modern contraceptive methods, age of the women, women and husband education, husband residence, media exposure, wealth index, the number of children from the individual level factors and distance to the health care facility, urban residence, community poverty and country from the community level variables were statistically, significant associated factors with demand satisfied for modern contraceptive.

The odds of demand satisfied for modern contraceptive methods among women aged 25–34 and 35–49 years had 1.34 (AOR: 1.34, 95%CI: 1.26, 1.42) and 1.28 (AOR: 1.28, 95%CI: 1.20, 1.38) times higher as compared to women aged 15–24 years, respectively.

The likelihood of demand satisfied for modern contraceptive was 1.35 (AOR: 1.35, 95%CI: 1.27, 1.44) times and two times (AOR: 2.05, 95%CI: 1.90, 2.21) higher among women who had educated primary and secondary and higher education, respectively. Similarly, the odds of demand satisfied for modern contraceptive was 1.26 (AOR: 1.26, 95%CI: 1.18, 1.35) and 1.54 (AOR: 1.54, 95%CI: 1.43, 1.66) times higher among women whose husband had educated primary and secondary education than those women whose husband had no formal education, respectively.

The odds of demand satisfied to use modern contraceptives among women who lives with their husband was nearly two times higher as compared to their counterparts (AOR: 1.75, 95%CI: 1.60, 1.91). The likelihood of demand satisfied for modern contraceptives was 1.22 (AOR: 1.22, 95%CI: 1.15, 1.29) times higher among women who had media exposure as compared to women who had no media exposure (AOR: 1.22, 95%CI: 1.15, 1.29).

The odds of demand satisfied was 1.1 (AOR: 1.1, 95%CI: 1.02, 1.19), 1.18 (AOR: 1.18, 95%CI: 1.08, 1.28), 1.37(AOR: 1.37, 95%CI: 1.26, 1.49), and 1.72(AOR: 1.72, 95%CI: 1.56, 1.89) times higher among poorer, middle, richer, and richest households as compared to the poorest wealth quintile households.

The odds of demand satisfied for modern contraceptives among women who had 4–6 and above 6 children was reduced by 52% (AOR: 0.48, 95%CI: 0.43, 0.55) and 61% (AOR: 0.39, 95%CI: 0.29, 0.59) as compared to those women who had below 4 children, respectively.

Women who perceived distance to the health facility as not a big problem had 1.11 times higher odds (AOR: 1.11, 95%CI: 1.04, 1.15) of demand satisfied than their counterparts.

Urban resident women had 1.18 times higher odds (AOR: 1.18, 95%CI: 1.10, 1.27) of demand satisfied to use modern contraceptives than rural resident women.

Women from high community poverty had 15% less odds (AOR: 0.85, 95%CI: 0.74, 0.97) of demand satisfied for modern contraceptive methods as compared to women from low community poverty.

Demand satisfied for modern contraceptive methods was 73% (AOR: 0.27, 95%CI: 0.20, 0.32), 26% (AOR: 0.74, 95%CI: 0.66, 0.89), 43% (AOR: 0.57, 95%CI: 0.50, 0.65), 69% (AOR: 0.31, 95%CI: 0.27, 0.36), 37%(AOR: 0.63, 95%CI: 0.48, 0.82), 52% (AOR: 0.48, 95%CI: 0.43, 0.55) less odds and 1.3 times higher odds (AOR: 1.30, 95%CI: 1.00, 1.70) in Angola, Burkina Faso, Democratic Republic Congo, Gambia, Nigeria, Chad and Burundi as compared to Niger, respectively (Table 2).

Discussion

The study identified demand satisfied for modern contraceptive and associated factors among married women in high fertility sub Saharan Africa. The finding of this study reveals that almost, four among ten, 39.53% (95%CI: 39.06, 39.98) women had demand satisfied for modern contraceptive.

Demand satisfied for modern contraceptive methods was 73%, 26%, 43%, 69%, 37%, 64% less odds, and 30% higher odds in Angola, Burkina Faso, Democratic Republic Congo, Gambia, Nigeria, Chad and Burundi as compared to Niger, respectively. The better demand satisfaction for modern contraceptive in Niger might possibly the government’s ongoing improvement, such as a segmentation counseling strategy that has been developed by the Niger government to increase the use of family planning; this segmentation approach identifies categories of women and makes counseling specific to their needs. This approach will support the goal that all women being introduced to a range of contraceptive methods to meet their current family planning needs [41, 42]. Additionally, community based family planning interventions in Niger are a very important strategy to improve met need [43].

The overall magnitude of demand satisfied for modern contraceptive is in line with a study conducted in Ethiopia 39.5% [21]. However, our finding is lower than studies conducted in low and middle income countries 52.9% [4] and among 185 countries 75.8% [24] and the focus countries of 2020 family planning (67.9%) [25], and in Jordan 54.7% [26]. The lower demand satisfied in our study might be accounted with the continuous increase in the absolute number of women of reproductive age in sub-Saharan Africa. Here, the percentage of women with unmet need for family planning is increased as well. Adolescents in Sub-Saharan Africa, in particular, have a significant unmet need for sexual and reproductive health care, whereas in most other regions of the world, the number of adolescent girls and young women with an unmet need for contraception has decreased or remained constant [44, 45]. Additionally, in Africa one among five women lack access to family planning since 2017 [9].This study tried to assess demand satisfied for modern contraceptives among married women in selected high fertility countries. Which indicates a need to overcome unmet need and extensive women’s counseling to bring down population growth and unwanted or unplanned pregnancies.

The result of this study revealed that higher odds of demand satisfied for modern contraceptive methods in the oldest age groups of women as compared to those young women. On the contrary higher odds of mDFPS was observed among young women in Ethiopia [46], Uganda [47], Zambia [29], Bangladesh [48]. The reason might be accounted that limited knowledge, access, worries about fertility and low status of women are the major factors of family planning utilization among youths in developing country [49]. On the other hand those older women might receive enough information about family planning from relatives, and media in their lives [50]. Moreover, these older women had higher desire in spacing births. On the contrary those young women are a high desire in bearing children [51]. This implies that improving modern contraceptive access and counseling of young women might be very important to address unmet need.

The odds of demand satisfied for modern contraceptive was higher among women who had educated as compared to women who had no formal education. Similarly, women whose husband had educated primary and secondary education were higher odds of demand satisfied for modern contraceptives than women whose husband had no formal education. Perhaps this is due to the fact that education enhances the self-confidence of women, gives them a better understanding of health care decision-making, and helps them make independent decisions about their health care utilization. As a result of exercising gender equality, educated women are more likely to participate in health care decisions [52, 53]. Additionally, if partner is educated, the more he will accept gender equality and believe in equal participation in decision making [54, 55].

The odds of demand satisfied to use modern contraceptives was nearly twice among women who lives with their husband as compared to those women who lives separately with their husband. The same is true in Nepal [56, 57]. Women who live with their husbands probably have frequent sexual contact, so they may believe pregnancy is likely, leading them to look for family planning. Therefore, family planning can be of greater benefit to them, such as minimizing unwanted and unplanned pregnancies.

Women who had media exposure had higher odds of demand satisfied for modern contraceptives as compared to women who had no media exposure. This finding is consistent with studies done in Ethiopia [58], Nigeria [59], and Pakistan [60]. The possible reason for this finding is women with high media exposure might have a better understanding of reproductive health rights and the advantages of their health care service utilization that encourages their participation in reproductive health decisions [58].

The odds of demand satisfied was higher among poorer, middle, richer, and richest households as compared to the poorest wealth quintile households. The finding is similar with studies conducted in Africa [61], Nigeria [62], and Zambia [29]. The possible justification might be having enough income enables women to involve in labor force in which their level of awareness and decision making power will be improved [61]. Similarly, women from high community poverty had 15% less odds of demand satisfied for modern contraceptive methods as compared to women from low community poverty. This might be that women from the high community poverty have decreased the use of contraceptives [63]. Because the children are considered as an economic value who pay back during the old age [64]. Women from the poor community may expect that when a child grows older, he/she will be a responsibility to support the parents for his/her upbringing. Additionally, couples (or parents) who place a high value on having children will seek out larger families who will later be able to take on the role of caregiving for their parents when they are older [64].

Reproductive age women who had 4–6 and above 6 children were 52% and 61% less odds of demand satisfied for modern contraceptives as compared to those women who had below 4 children, respectively. The finding is in line with a study conducted in Malawi [51]. This is because the demand for contraceptives increases with parities after the desire family size has achieved.

Urban resident women had 1.18 times higher odds of demand satisfied to use modern contraceptives than rural resident women. This finding is similar with Zambia [29], Pakistan [65], and Bangladesh [50]. The possible reason might be that in Africa most of the population are settled in rural area where education, information about the available contraceptive method, access to family planning are obstacles [51]. Again it is confirmed from this study finding that Women who perceived distance to the health facility as not a big problem had higher odds of demand satisfied than their counterparts.

Due to the high fertility rate, sub-Saharan Africa has contributed most of the world’s unexpected population dynamics. Modern contraception plays a crucial role in helping to regulate population growth, and to improve the physical and economic wellbeing of women and their families as well as for the countries. However, in Sub-Saharan African countries with high fertility, only four out of ten married/in union women demand satisfied by modern contraceptives. Thus, thousands of reproductive age women had unmet need for modern contraceptives. In turn, this can lead to an increase in unwanted or mistimed pregnancies, and sexually transmitted infections such as HIV/AIDS. In order to combat the problem, the respective country governments, nongovernmental organizations and policy makers should try to improve access to modern contraceptive or met need for family planning more widely in the region.

Strengths and limitations

The utilization of nationally representative data, large sample size, and analysis of the individual and community level factors were the key strengths. In order to find a more accurate result, multilevel-modeling technique accounting the survey data hierarchical nature was employed. The current study is not generalisable to all women in SSA. Moreover, the study was unable to explore cultural norms and values. The study also have limitations, because the DHS data are cross-sectional no temporal link between the independent variables and the dependent variable is demonstrated.

Conclusion

Only four in ten married reproductive age women demands satisfied with modern contraceptives in high fertility Sub Saharan African countries. Individual level factors such as age, education, husband residence, media exposure, wealth index, number of children, and distance to the health facility, and community level factors of urban residence and community level poverty were significantly associated with demand satisfied for modern contraceptives. It is therefore, important to improve access to modern contraceptives, particularly for those living in rural areas and far from health facilities. Increasing media exposure and educate women about modern contraceptives, increasing financial support, and enabling married women from poor households to get contraceptives, are also important interventions that need to be put in place.

Availability of data and materials

The study used publicly available data, which can be found at the following link: https://dhsprogram.com/data/dataset_admin/login_main.cfm?CFID=39421058&CFTOKEN=a8b8a36f1fb27230-E89DAEA4-D47B-719A 9AD1F13D7D93EF8A.

Abbreviations

AOR:

Adjusted Odds Ratio

COR:

Crude Odds Ratio

CI:

Confidence Interval

DHS:

Demographic and Health Survey

mDFPS:

Demand Satisfied for Modern Contraceptives

PCV:

Proportional change in variance

ICC:

Intra class corrolation cofficent

IUD:

Intrauterine Device

MOR:

Median Odds Ratio

SSA:

Sub Saharan Africa

VIF:

Variance Inflation Factor

References

  1. Cleland J, Conde-Agudelo A, Peterson H, Ross J, Tsui A. Contraception and health. Lancet. 2012;380(9837):149–56.

    Article  PubMed  Google Scholar 

  2. Organization WH: Programming strategies for postpartum family planning. 2013.

  3. Dadi AF. A systematic review and meta-analysis of the effect of short birth interval on infant mortality in Ethiopia. PLoS ONE. 2015;10(5):e0126759.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Ewerling F, Victora CG, Raj A, Coll CV, Hellwig F, Barros AJ. Demand for family planning satisfied with modern methods among sexually active women in low-and middle-income countries: who is lagging behind? Reprod Health. 2018;15(1):1–10.

    Article  Google Scholar 

  5. Hellwig F, Coll CV, Ewerling F, Barros AJ. Time trends in demand for family planning satisfied: analysis of 73 countries using national health surveys over a 24-year period. J Glob Health. 2019;9(2):020423. https://doi.org/10.7189/jogh.09.020423.

  6. Taye EB, Mekonen DG, Debele TZ. Prevalence of post partum modern family planning utilization and associated factors among postpartum mothers in Debre Tabor town, North West Ethiopia, 2018. BMC Res Notes. 2019;12(1):1–7.

    Article  Google Scholar 

  7. Uddin Howlader S, Howlader S. Current situation of utilization of modern family planning methods in Dhaka City. Womens Health. 2018;7(10.15406). Available at: https://medcraveonline.com.

  8. Adebowale SA, Adedini SA, Ibisomi LD, Palamuleni ME. Differential effect of wealth quintile on modern contraceptive use and fertility: evidence from Malawian women. BMC Womens Health. 2014;14(1):1–13.

    Article  Google Scholar 

  9. United Nations DoE. Affairs S. United Nations New York: World Family Planning 2017—Highlights; 2017.

    Google Scholar 

  10. Darroch JE, Singh S. Trends in contraceptive need and use in developing countries in 2003, 2008, and 2012: an analysis of national surveys. The Lancet. 2013;381(9879):1756–62.

    Article  Google Scholar 

  11. Alkema L, Kantorova V, Menozzi C, Biddlecom A. National, regional, and global rates and trends in contraceptive prevalence and unmet need for family planning between 1990 and 2015: a systematic and comprehensive analysis. The Lancet. 2013;381(9878):1642–52.

    Article  Google Scholar 

  12. Bhusal CK, Bhattarai S. Factors affecting unmet need of family planning among married Tharu women of Dang District, Nepal. Int J Reprod Med. 2018;2018:Article ID 9312687. https://doi.org/10.1155/2018/9312687.

  13. Bahk J, Yun S-C, Kim Y-m, Khang Y-H. Impact of unintended pregnancy on maternal mental health: a causal analysis using follow up data of the Panel Study on Korean Children (PSKC). BMC Pregnancy Childbirth. 2015;15(1):1–12.

    Article  Google Scholar 

  14. Foster DG, Raifman SE, Gipson JD, Rocca CH, Biggs MA. Effects of carrying an unwanted pregnancy to term on women’s existing children. J Pediatr. 2019;205(183–189):e181.

    Google Scholar 

  15. Boah M, Issah A-N, Demuyakor I, Hyzam D. Long-acting reversible contraceptives utilization and its determinants among married Yemeni women of childbearing age who no longer want children. Medicine. 2022;101(40):e30717.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Olakunde BO, Pharr JR, Chien L-C, Benfield RD, Sy FS. Individual-and country-level correlates of female permanent contraception use in sub-Saharan Africa. PLoS ONE. 2020;15(12):e0243316.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Bradley EH, McGraw SA, Curry L, Buckser A, King KL, Kasl SV, et al. Expanding the Andersen model: the role of psychosocial factors in long-term care use. Health Serv Res. 2002;37(5):1221–42.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ackerson K, Zielinski R. Factors influencing use of family planning in women living in crisis affected areas of Sub-Saharan Africa: A review of the literature. Midwifery. 2017;54:35–60.

    Article  PubMed  Google Scholar 

  19. Ugaz JI, Chatterji M, Gribble JN, Banke K. Is household wealth associated with use of long-acting reversible and permanent methods of contraception? A multi-country analysis. Global Health Science Pract. 2016;4(1):43–54.

    Article  Google Scholar 

  20. Wai MM, Bjertness E, Stigum H, Htay TT, Liabsuetrakul T, Moe Myint AN, Sundby J. Unmet need for family planning among urban and rural married women in Yangon region, Myanmar—a cross-sectional study. Int J Environ Res Public Health. 2019;16(19):3742.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Tsehay CT. Factors associated with modern contraceptive demands satisfied among currently married/in-union women of reproductive age in Ethiopia: a multilevel analysis of the 2016 Demographic and Health Survey. BMJ Open. 2022;12(2):e049341.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Olakunde BO, Pharr JR, Adeyinka DA, Chien L-C, Benfield RD, Sy FS. Spatial variations in family planning demand to limit childbearing and the demand satisfied with modern methods in sub-Saharan Africa. Reprod Health. 2022;19(1):1–12.

    Article  Google Scholar 

  23. Li Q, Rimon JG, Ahmed S. Capitalising on shared goals for family planning: a concordance assessment of two global initiatives using longitudinal statistical models. BMJ Open. 2019;9(11):e031425.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Kantorová V, Wheldon MC, Ueffing P, Dasgupta AN. Estimating progress towards meeting women’s contraceptive needs in 185 countries: A Bayesian hierarchical modelling study. PLoS Med. 2020;17(2):e1003026.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Cahill N, Sonneveldt E, Stover J, Weinberger M, Williamson J, Wei C, Brown W, Alkema L. Modern contraceptive use, unmet need, and demand satisfied among women of reproductive age who are married or in a union in the focus countries of the Family Planning 2020 initiative: a systematic analysis using the Family Planning Estimation Tool. The Lancet. 2018;391(10123):870–82.

    Article  Google Scholar 

  26. Komasawa M, Yuasa M, Shirayama Y, Sato M, Komasawa Y, Alouri M. Demand for family planning satisfied with modern methods and its associated factors among married women of reproductive age in rural Jordan: a cross-sectional study. PLoS ONE. 2020;15(3):e0230421.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Ahinkorah BO, Budu E, Aboagye RG, Agbaglo E, Arthur-Holmes F, Adu C, Archer AG, Aderoju YBG, Seidu A-A. Factors associated with modern contraceptive use among women with no fertility intention in sub-Saharan Africa: evidence from cross-sectional surveys of 29 countries. Contracept Reprod Med. 2021;6(1):1–13.

    Article  Google Scholar 

  28. Ahinkorah BO. Predictors of modern contraceptive use among adolescent girls and young women in sub-Saharan Africa: a mixed effects multilevel analysis of data from 29 demographic and health surveys. Contracept Reprod Med. 2020;5(1):1–12.

    Google Scholar 

  29. Lasong J, Zhang Y, Gebremedhin SA, Opoku S, Abaidoo CS, Mkandawire T, Zhao K, Zhang H. Determinants of modern contraceptive use among married women of reproductive age: a cross-sectional study in rural Zambia. BMJ Open. 2020;10(3):e030980.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Mutua MK, Wado YD, Malata M, Kabiru CW, Akwara E, Melesse DY, Fall NA, Coll CV, Faye C, Barros AJ. Wealth-related inequalities in demand for family planning satisfied among married and unmarried adolescent girls and young women in sub-Saharan Africa. Reprod Health. 2021;18(1):1–13.

    Google Scholar 

  31. African countries with the highest fertility rate | Statista https://worldpopulationreview.com/countries/total-fertility-rate. cited on December 8, 2021.

  32. Corsi DJ, Neuman M, Finlay JE, Subramanian S. Demographic and health surveys: a profile. Int J Epidemiol. 2012;41(6):1602–13.

    Article  PubMed  Google Scholar 

  33. Bradley SE, Croft TN, Fishel JD, Westoff CF. Revising unmet need for family planning. MD ICF International: DHS Analytical Studies No.25. Calverton; 2012.

    Google Scholar 

  34. Gnanadesikan R. Methods for statistical data analysis of multivariate observations: Wiley; 2011. Available at: https://books.google.com.

  35. Araban M, Karimy M, Armoon B, Zamani-Alavijeh F. Factors related to childbearing intentions among women: a cross-sectional study in health centers, Saveh Iran. J Egypt Public Health Assoc. 2020;95(1):1–8.

    Article  Google Scholar 

  36. Bhargava A. Desired family size, family planning and fertility in Ethiopia. J Biosoc Sci. 2007;39(3):367–81.

    Article  PubMed  Google Scholar 

  37. Atake E-H, Gnakou Ali P. Women’s empowerment and fertility preferences in high fertility countries in Sub-Saharan Africa. BMC Womens Health. 2019;19(1):1–14.

    Article  Google Scholar 

  38. Liyew AM, Teshale AB. Individual and community level factors associated with anemia among lactating mothers in Ethiopia using data from Ethiopian demographic and health survey, 2016; a multilevel analysis. BMC Public Health. 2020;20(1):1–11.

    Article  Google Scholar 

  39. Gulliford M, Adams G, Ukoumunne O, Latinovic R, Chinn S, Campbell M. Intraclass correlation coefficient and outcome prevalence are associated in clustered binary data. J Clin Epidemiol. 2005;58(3):246–51.

    Article  CAS  PubMed  Google Scholar 

  40. Merlo J, Wagner P, Ghith N, Leckie G. An original stepwise multilevel logistic regression analysis of discriminatory accuracy: the case of neighbourhoods and health. PLoS ONE. 2016;11(4):e0153778.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Speizer IS, Amani H, Winston J, Garba SA, Maytan-Joneydi A, Halidou IC, Calhoun LM, Nouhou AM. Assessment of segmentation and targeted counseling on family planning quality of care and client satisfaction: a facility-based survey of clients in Niger. BMC Health Serv Res. 2021;21(1):1–6.

    Article  Google Scholar 

  42. León F, Vernon R, Martin A, Bruce L. The balanced counseling strategy: a toolkit for family Planning service providers. Washington, DC: Population Council; 2008.

    Google Scholar 

  43. Erhardt-Ohren B, Brooks M, Aliou S, et al. Sustained impact of community-based interventions on contraceptive use among married adolescent girls in rural Niger: results from a cluster randomized controlled trial. Int J Gynecol Obstet. 2022;00:1–8. https://doi.org/10.1002/ijgo.14378.

    Article  Google Scholar 

  44. Family Planning Trends in Sub-Saharan Africa available at: ttps://documents1.worldbank.org › accessed on October 26/2022.

  45. Ahinkorah BO. Predictors of unmet need for contraception among adolescent girls and young women in selected high fertility countries in sub-Saharan Africa: a multilevel mixed effects analysis. PLoS ONE. 2020;15(8):e0236352.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Yirsaw B, Gebremeskel F, Gebremichael G, Shitemaw T. Determinants of long acting contraceptive utilization among HIV positive reproductive age women attending care at art clinics of public health facilities in Arba Minch town, southern Ethiopia, 2019: a case control study. AIDS Res Ther. 2020;17(1):1–8.

    Article  Google Scholar 

  47. Bongomin F, Chelangat M, Eriatu A, Chan Onen B, Cheputyo P, Godmercy SA, et al. Prevalence and factors associated with contraceptive use among HIV-infected women of reproductive age attending infectious disease clinic at Gulu Regional Referral Hospital, Northern Uganda. Biomed Res Int. 2018;2018:Article ID 9680514. https://doi.org/10.1155/2018/9680514.

  48. Haq I, Sakib S, Talukder A. Sociodemographic factors on contraceptive use among ever-married women of reproductive age: evidence from three demographic and health surveys in Bangladesh. Medical Sciences. 2017;5(4):31.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Williamson LM, Parkes A, Wight D, Petticrew M, Hart GJ. Limits to modern contraceptive use among young women in developing countries: a systematic review of qualitative research. Reprod Health. 2009;6(1):1–12.

    Article  Google Scholar 

  50. Islam AZ, Rahman M, Mostofa MG. Association between contraceptive use and socio-demographic factors of young fecund women in Bangladesh. Sex Reprod Healthc. 2017;13:1–7.

    Article  PubMed  Google Scholar 

  51. Palamuleni ME. Socio-economic and demographic factors affecting contraceptive use in Malawi. Afr J Reprod Health. 2013;17(3):91–104.

    PubMed  Google Scholar 

  52. Kabeer N. Gender equality and women’s empowerment: A critical analysis of the third millennium development goal 1. Gend Dev. 2005;13(1):13–24.

    Article  Google Scholar 

  53. Acharya DR, Bell JS, Simkhada P, Van Teijlingen ER, Regmi PR. Women’s autonomy in household decision-making: a demographic study in Nepal. Reprod Health. 2010;7(1):1–12.

    Article  Google Scholar 

  54. Seidu A-A, Aboagye RG, Okyere J, Agbemavi W, Akpeke M, Budu E, Saah FI, Tackie V, Ahinkorah BO. Women’s autonomy in household decision-making and safer sex negotiation in sub-Saharan Africa: An analysis of data from 27 Demographic and Health Surveys. SSM-Popul Health. 2021;14:100773.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Alemayehu M, Meskele M. Health care decision making autonomy of women from rural districts of Southern Ethiopia: a community based cross-sectional study. Int J Women’s Health. 2017;9:213.

    Article  Google Scholar 

  56. Mehata S, Paudel YR, Dhungel A, Paudel M, Thapa J, Karki DK: Spousal separation and use of and unmet need for contraception in Nepal: results based on a 2016 survey. The Scientific World Journal 2020, 2020

  57. Ban B, Karki S, Shrestha A, Hodgins S. Spousal separation and interpretation of contraceptive use and unmet need in rural Nepal. Int Perspect Sex Reprod Health. 2012;38(1):43–7.

    Article  PubMed  Google Scholar 

  58. Mare KU, Aychiluhm SB, Tadesse AW, Abdu M. Married women’s decision-making autonomy on contraceptive use and its associated factors in Ethiopia: A multilevel analysis of 2016 demographic and health survey. SAGE Open Medicine. 2022;10:20503121211068720.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Osamor P, Grady C. Factors associated with women’s health care decision-making autonomy: empirical evidence from Nigeria. J Biosoc Sci. 2018;50(1):70–85.

    Article  PubMed  Google Scholar 

  60. Nadeem M, Malik MI, Anwar M, et al. Women decision making autonomy as a facilitating factor for contraceptive use for family planning in Pakistan. Soc Indic Res. 2021;156:71–89. https://doi.org/10.1007/s11205-021-02633-7.

    Article  Google Scholar 

  61. Creanga AA, Gillespie D, Karklins S, Tsui AO. Low use of contraception among poor women in Africa: an equity issue. Bull World Health Organ. 2011;89:258–66.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Adedini SA, Babalola S, Ibeawuchi C, Omotoso O, Akiode A, Odeku M. Role of religious leaders in promoting contraceptive use in Nigeria: evidence from the Nigerian urban reproductive health initiative. Glob Health Sci Pract. 2018;6(3):500–14.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Johnson OE. Determinants of Modern Contraceptive Uptake among Nigerian Women: Evidence from the National Demographic and Health Survey. Afr J Reprod Health. 2017;21(3):89–95.

    Article  PubMed  Google Scholar 

  64. Sathiya Susuman A, Bado A, Lailulo YA. Promoting family planning use after childbirth and desire to limit childbearing in Ethiopia. Reprod Health. 2014;11(1):1–8.

    Article  Google Scholar 

  65. Aslam SK, Zaheer S, Qureshi MS, Aslam SN, Shafique K. Socio-economic disparities in use of family planning methods among Pakistani women: findings from Pakistan demographic and health surveys. PLoS ONE. 2016;11(4):e0153313.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Our thanks forwarded to the DHS programs, for the permission to use all the relevant EDHS data for this study.

Funding

No funding was secured for this study.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the preparation of the manuscript. WDN conceived the idea. WDN extract the data, conducted analysis, and write the original draft of the manuscript, DAB, DBA, TBB, critically edited, revised and reviewed the manuscript. All authors assisted in the data analysis and interpretation. All of the authors read and approved the final manuscript.

Corresponding author

Correspondence to Wubshet Debebe Negash.

Ethics declarations

Ethics approval and consent to participate

The ethical approval and permission to access the data were obtained from the DHS website www.measuredhs.com. All methods were approved by ICF International ethical committee, in accordance with United states Department of Health and Human Services requirements for human subject protection. Ethical clearance was obtained by the Institutional Review Board of Demographic and Health Surveys (DHS) program data archivists after the consent manuscript was submitted to DHS Program/ICF International. Informed consent was obtained from all subjects and/or their legal guardian(s) of minors’ age below 16. All the methods were conducted according to Helsinki declarations. No information obtained from the data set was disclosed to any third person. Further explanation of how the DHS uses data and its ethical standards can be found at: http://goo.gl/ny8T6X.

Consent for publication

It is not applicable for this study since the study was used a secondary data analysis conducted by central statistical agency.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Negash, W.D., Belachew, T.B., Asmamaw, D.B. et al. Four in ten married women demands satisfied by modern contraceptives in high fertility sub-Saharan Africa countries: a multilevel analysis of demographic and health surveys. BMC Public Health 22, 2169 (2022). https://doi.org/10.1186/s12889-022-14610-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-022-14610-x

Keywords

  • Demand satisfied
  • Modern contraceptives
  • High fertility
  • Sub Saharan Africa