**2. Methodology**

families and communities. These include improved maternal and child health, prevention of sexually transmitted infections through adoption of safer sexual practices, reduction in prevalence of unintended pregnancies and unsafe abortion and improved economic growth [2–4]. However, evidence abounds worldwide about women who have desire to either space or limit their next pregnancies, but are not using any family planning method to actualise their pregnancy intention [5–9]. Such women have been described as having unmet need for family planning. The term 'unmet need for family planning' evolved in 1977 from 'KAP-gap' a term used in the 1960s to indicate the proportion of women in Family Planning Knowledge, Attitude and Practice (KAP) surveys who reported desire to limit childbearing but doing nothing to actualise their fertility desire [10, 11]. Though, the measurement of unmet need for family planning has undergone several refinements [12, 13], in its contemporary form, it measures the proportion of women who have desire to either delay the next pregnancy for at least the next 2 years or stop childbearing, but not using either traditional or modern method of contraception to achieve such intention [14–16]. These women have elevated the risk of unintended pregnancies and its associated consequences [17, 18]. Recent estimates of unmet need for family planning revealed that across the world, the prevalence of unmet need for family planning among women aged 15–49 years reduced from 15.4% in 1990 to 12.3% in 2010. However, the absolute number of women with unmet contraceptive need is not only expected to grow marginally, but also expected to increase in developing countries [19]. Hence, unmet need for family planning methods remains relatively high in some regions particularly sub-Saharan Africa, South Asia, Western Asia and the Caribbean [15, 20, 21]. This has made further investigation of the socio-demographic drivers of unmet need for family planning imperative in the regions. Several studies across developing countries have examined the determinants of unmet need for family planning [22–36]. These studies observed varying prevalence of unmet need for family planning in different countries, identified key determinants of unmet need for family planning (such as women's education, decision-making autonomy, parity, access to mass media, partner desire for more children, spousal violence and place of residence), and also provided context relevant information for the development of appropriate interventions for reducing unmet need for family planning. A recent study [21] organised the identified determinants into multiple levels of influence such as determinants operating at the individual women level, partner or household level and health service level, indicating that the factors influencing the prevalence of unmet need for family planning oper-

However, in spite of the numerous studies, multi-country studies focusing on urban West Africa are rarely available in literature. Though, a number of studies have focused on urban women in a number of countries [36–43], women of advanced reproductive age, that is women aged 35 years or older [44] in urban West Africa have not been explicitly examined. Five key reasons account for the need to focus on this group of women in West Africa. One, the subregion has one of the highest levels of unmet need for family planning in the world [15]. Two, urban areas in West Africa not only drives development in the sub-region, but also the urban health in West Africa drives the health of both urban and non-urban dwellers as found in urban areas of most other developing regions [45–47]. Three, there are hardly specific interventions focusing on women of advanced reproductive age across the sub-region [48, 49]. Four, substantial proportions of women in advanced age group in West Africa are high parity women

ates at different levels of the social environment.

96 Family Planning

#### **2.1. Data source and sample**

Data analysed in the study were extracted from individual recode (women's data) of the most recent Demographic and Health Survey (DHS) implemented in the selected countries. The surveys provided reliable information about fertility, mortality, family planning, nutrition, child health and other basic demographic and health information in each country. The surveys in the Gambia and Nigeria were conducted in 2013, while the survey in Guinea was conducted in 2012. The surveys were conducted using similar design and methodology in line with DHS uniform survey methodology [61]. Samples in each country were drawn using multi-stage sampling techniques and were weighted by cluster. Detailed information about the survey designs have been published [62–64]. The surveys covered 9142, 10,233 and 38,948 women of reproductive age, respectively, in Guinea, the Gambia and Nigeria. However, not all the women were analysed in the study. All women less than 35 years and all rural women were excluded in the study. The study analysed weighted sample sizes of 800 women in Guinea, 4928 women in Nigeria and 1253 women in the Gambia.

#### **2.2. Outcome variable**

The outcome variable in the study was unmet need for family planning. This was measured adopting a recent revision of the measurement of unmet need for family planning [12]. The outcome variable naturally had three categories, namely, unmet need for limiting (criteria for inclusion in this category included being not having desire for additional child, not currently pregnant, not postpartum amenorrheic, not considered fecund, but not using a method of contraception. Women who are currently pregnant with an unwanted pregnancy and postpartum amenorrheic women whose last births in the last 2 years were unwanted are also included in the category); no unmet need (criteria for inclusion in this category included being infecund or being fecund but desire to have a child in the next 2 years); and unmet need for spacing (criteria for inclusion in this category included being not pregnant, not postpartum amenorrheic, not considered fecund, desire to delay the next birth by two or more years but not using any contraception. Women who currently had a mistimed pregnancy or postpartum women whose last birth in the last 2 years were mistimed are also included in this category). However, at the multivariable analysis level, both unmet need for spacing and unmet need for limiting are grouped as unmet need, which is the category of interest in the chapter.

examine association between the sets of explanatory variables and unmet need for family planning. The cross tabulations showed the prevalence of unmet need for family planning given the individual and community characteristics, while the unadjusted binary regression coefficients showed whether the association was positive or negative. Three, the multilevel mixed effect logistic regression was applied to examine the influence of the individual and community characteristics on unmet need for family planning. This analytical method was appropriate for the study because of the need to determine the extent of variation in unmet need for family planning that are attributable to each level of influence on the outcome variable. A multilevel mixed effect regression model has two components, namely, the fixed and random components [67]. The fixed effect was measured by the odds ratios of the binary logistic regression, while the random component was measured by the intra-class correlation (ICC) which measures the effects of the community characteristics. The

Drivers of Unmet Need for Family Planning among Women of Advanced Reproductive Age…

http://dx.doi.org/10.5772/intechopen.72896

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mixed effects regression models were fitted in the study using Stata 12. Model 1 was based on individual characteristics, while Model 2 included both the individual and community characteristics. Model 3 included all the explanatory and control variables. The goodness-of-fit of the multilevel models were examined using the Likelihood Ratio test. Statistical significance was set at 5%.

The data analysed were formally requested from MEASURE DHS. Authorisation to download and analyse the data sets were granted. The analyses and inferences drawn from the

**Figure 1** presents the prevalence of unmet need for family planning among the respondents. Unmet need for spacing was higher in the Gambia compared with Guinea and Nigeria, while unmet need for limiting was higher in Guinea compared with Nigeria and the Gambia. Overall, the prevalence of unmet need for family planning among urban women of advanced reproductive age was slightly more than one-fifth in Guinea (22.2%) and the Gambia (22.9%), but slightly more than one-tenth in Nigeria (12.6%). **Table 1** presents respondents' sociodemographic profile. In Guinea, women's healthcare decision was not only mostly taken by husband/others (68.4%), but also the proportion of joint decision with male partners was slightly less than one-fifth among respondents (19.8%). But in Nigeria and the Gambia, more than one-third of women's healthcare decisions were taken jointly with the male partner. However, decision by husband/others was dominant in Nigeria (48.9%), while joint decision was dominant in the Gambia (39.8%). Nearly all respondents in Nigeria and the Gambia did not accept gender norms that justify men's control over women. But in Guinea, one-third of the women (33.0%) accepted the norms. The majority of respondents' partners in Guinea and the Gambia had no formal education. But across the countries, while secondary education was the dominant educational level attained by respondents' partners, higher education was

**3.1. Sample characteristics and prevalence of unmet need for family planning**

<sup>2</sup> been the variance at the community level [68]. Three multilevel

ICC was calculated as: *<sup>σ</sup>ui*

**2.5. Ethical considerations**

**3. Results**

2 \_\_\_\_\_\_\_\_ *σui* <sup>2</sup> + [3.29]

with *σui*

study are not linked to any individual, couple or communities.

#### **2.3. Explanatory and control variables**

Two sets of explanatory variables are analysed in the study. The first sets are individual characteristics, namely, healthcare decision, gender norms that justify men's control over women, partner education, marital status, fertility desire, child death and age at first marriage. A number of previous studies have linked some of these variables to unmet need for family planning [30–32, 36, 65, 66]. Healthcare decision was based on who had final say on women's health care decision. Gender norm that justify men's control over women was based on women's response to whether wife battery was justify given some circumstances such as when wife goes out without husband permission, argues with husband, refuses to have sex with husband, burns food, and neglects children. Women who accepted at least one of the norms were grouped as 'norm accepted', while women who rejected all the norms were grouped as 'norm not accepted'. The second sets of variables are community characteristics, namely, community wealth level (proportion of women in the richer or richest wealth quintile in the community), community literacy level (proportion of women who can read and write complete sentence), proportion of women who have ever used contraceptive method in the community and community childcare burden (proportion of high parous women in the community). The community characteristics were derived from individual characteristics aggregated at the cluster level, and divided into low, medium and high categories. Three variables, namely, pregnancy termination, visitation by family planning worker and exposure to family planning mass media messages are selected for statistical control. These variables may impact need for either spacing or limiting pregnancies. While visitation by family planning worker and exposure to family planning media messages may enhance contraceptive use by providing reliable information about contraceptive choice, pregnancy termination experience may give insight into levels of exposures to unhealthy reproductive practices due to either non-use of contraceptive or contraceptive failure.

#### **2.4. Data analyses**

Statistical analyses were performed at three levels. One, frequency distribution, percentages and charts were used to described sample characteristics or prevalence of unmet need for family planning. Two, cross tabulations and unadjusted binary logistic regression coefficients were used to examine association between the sets of explanatory variables and unmet need for family planning. The cross tabulations showed the prevalence of unmet need for family planning given the individual and community characteristics, while the unadjusted binary regression coefficients showed whether the association was positive or negative. Three, the multilevel mixed effect logistic regression was applied to examine the influence of the individual and community characteristics on unmet need for family planning. This analytical method was appropriate for the study because of the need to determine the extent of variation in unmet need for family planning that are attributable to each level of influence on the outcome variable. A multilevel mixed effect regression model has two components, namely, the fixed and random components [67]. The fixed effect was measured by the odds ratios of the binary logistic regression, while the random component was measured by the intra-class correlation (ICC) which measures the effects of the community characteristics. The ICC was calculated as: *<sup>σ</sup>ui* 2 \_\_\_\_\_\_\_\_ *σui* <sup>2</sup> + [3.29] with *σui* <sup>2</sup> been the variance at the community level [68]. Three multilevel mixed effects regression models were fitted in the study using Stata 12. Model 1 was based on individual characteristics, while Model 2 included both the individual and community characteristics. Model 3 included all the explanatory and control variables. The goodness-of-fit of the multilevel models were examined using the Likelihood Ratio test. Statistical significance was set at 5%.

#### **2.5. Ethical considerations**

The data analysed were formally requested from MEASURE DHS. Authorisation to download and analyse the data sets were granted. The analyses and inferences drawn from the study are not linked to any individual, couple or communities.
