Proximate determinants and decomposition of changes in fertility levels across Nigeria regions: Evidence from Nigeria Demographic Health Survey, 2003-2018.

There is disparity in fertility level across the six geopolitical zones in Nigeria. Deeper uunderstanding about the drivers of fertility trends are necessary to prioritize zonal specific strategies for fertility reduction in Nigeria. Thus, this study examined the proximate determinants (PDs) of fertility and decomposed the change in its level across the six geo-political zones in Nigeria. Data from Nigeria Demographic and Health Surveys of 2003 and 2018 were analyzed. Fertility data were based on the report of full birth history from women of reproductive age. The Revised Bongaarts framework was used to estimate PDs and fertility levels. The contribution of each PDs to the observed changes in fertility levels was quantified using Das Gupta's five- factor decomposition method. The Total fertility rate (TFR) in 2003 and 2008 across the zones are South-South (5.04 vs 4.36), South-West (4.88 vs 4.26), North West (7.25 vs 6.85), North East (6.87 vs 6.54), North Central (5.72 vs 5.48), South East (5.06 vs 4.86), Nigeria (6.00 vs 5.59). Across the zones, there was a change in the fertility inhibiting effect of Contraception (Cc) between 2003 and 2018. The fertility inhibiting effect of Postpartum Infecundability (Ci) and Abortion was the highest and smallest respectively across the zones. Delayed sexual exposure (Cm) and contraceptive use (Cc) contributed the most to the change across the regions. The percentage contribution of Cm in South-South, South West, and South East was 87.04%, 52.89%, and 172.85% respectively. Furthermore, most of the fertility change observed in North Central was attributable to Cc. Abortion index was not an important inhibiting factor of fertility in Nigeria. Delayed sexual exposure and contraceptive use accounted for the largest change observed in fertility levels across the six geo-political zones in Nigeria between 2003 and 2018. Strategies that promote delayed sexual exposure, contraceptive use and breast feeding practices will enhance fertility transition in Nigeria.

Shifts in age pattern, timing of childbearing and trend in fertility level across six regions of Nigeria: Nigeria Demographic and Health Surveys from 2003-2018.

BACKGROUND: Nigeria's population is projected to increase from 200 million in 2019 to 450 million in 2050 if the fertility level remains at the current level. Thus, we examined the shifts in the age pattern of fertility, timing of childbearing and trend in fertility levels from 2003 and 2018 across six regions of Nigeria. METHOD: This study utilised the 2003, 2008, 2013, and 2018 Nigeria Demographic and Health Survey datasets. Each survey was a cross-sectional population-based design, and a two-stage cluster sampling technique was used to select women aged 15-49 years. The changes in the timing of childbearing were examined by calculating the corresponding mean ages at the birth of different birth orders for each birth order separately to adjust the Quantum effect for births. The Gompertz Relational Model was used to examine the age pattern of fertility and refined fertility level. RESULT: In Nigeria, it was observed that there was a minimal decline in mean children ever born (CEB) between 2003 and 2018 across all maternal age groups except aged 20-24 years. The pattern of mean CEB by the age of mothers was the same across the Nigeria regions except in North West. Nigeria's mean number of CEB to women aged 40-49 in 2003, 2008, 2013 and 2018 surveys was 6.7, 6.6, 6.3 and 6.1, respectively. The mean age (years) at first birth marginally increased from 21.3 in 2003 to 22.5 in 2018. In 2003, the mean age at first birth was highest in South East (24.3) and lowest in North East (19.4); while South West had the highest (24.4) and both North East and North West had the lowest (20.2) in 2018. Similar age patterns of fertility existed between 2003 and 2018 across the regions. Nigeria's estimated total fertility level for 2003, 2008, 2013 and 2018 was 6.1, 6.1, 5.9 and 5.7, respectively. CONCLUSION: The findings showed a reducing but slow fertility declines in Nigeria. The decline varied substantially across the regions. For a downward change in the level of fertility, policies that will constrict the spread of fertility distribution across the region in Nigeria must urgently be put in place.

Social consequences of COVID-19 on fertility preference consistency and contraceptive use among Nigerian women: insights from population-based data.

BACKGROUND: Emerging evidence from high income countries showed that the COVID-19 pandemic has had negative effects on population and reproductive health behaviour. This study provides a sub-Saharan Africa perspective by documenting the social consequences of COVID-19 and its relationship to fertility preference stability and modern contraceptive use in Nigeria. METHOD: We analysed panel data collected by Performance Monitoring for Action in Nigeria. Baseline and Follow-up surveys were conducted before the COVID-19 outbreak (November 2019-February 2020) and during the lockdown respectively (May-July 2020). Analysis was restricted to married non-pregnant women during follow-up (n = 774). Descriptive statistics and generalized linear models were employed to explore the relationship between selected social consequences of COVID-19 and fertility preferences stability (between baseline and follow-up) as well as modern contraceptives use. RESULTS: Reported social consequences of the pandemic lockdown include total loss of household income (31.3%), food insecurity (16.5%), and greater economic reliance on partner (43.0%). Sixty-eight women (8.8%) changed their minds about pregnancy and this was associated with age groups, higher wealth quintile (AOR = 0.38, CI: 0.15-0.97) and household food insecurity (AOR = 2.72, CI: 1.23-5.99). Fertility preference was inconsistent among 26.1%. Women aged 30-34 years (AOR = 4.46, CI:1.29-15.39) were more likely of inconsistent fertility preference compared to 15-24 years. The likelihood was also higher among women with three children compared to those with only one child (AOR = 3.88, CI: 1.36-11.08). During follow-up survey, 59.4% reported they would feel unhappy if pregnant. This was more common among women with tertiary education (AOR = 2.99, CI: 1.41-6.33). The odds increased with parity. The prevalence of modern contraceptive use was 32.8%. Women aged 45-49 years (AOR = 0.24, CI: 0.10-0.56) were less likely to use modern contraceptives than those aged 15-24 years. In contrast, the odds of contraceptive use were significantly higher among those with three (AOR = 1.82, CI: 1.03-3.20), four (AOR = 2.45, CI: 1.36-4.39) and at least five (AOR = 2.89, CI: 1.25-6.74) children. Unhappy disposition towards pregnancy (AOR = 2.48, CI: 1.724-3.58) was also a significant predictor of modern contraceptive use. CONCLUSION: Some social consequences of COVID-19 affected pregnancy intention and stability of fertility preference but showed no independent association with modern contraceptive use.

Barriers to acceptance of post-partum family planning among women in Montserrado County, Liberia.

BACKGROUND: Maternal mortality in Liberia is one of the highest in Sub-Saharan Africa. Post-partum family planning (PPFP) can reduce the risk of maternal mortality by preventing unwanted and closely spaced pregnancies. Yet, the uptake of PPFP is low in Liberia. OBJECTIVE: We investigated the barriers to acceptance of PPFP use among women in Montserrado County, Liberia. MATERIALS AND METHODS: A cross-sectional facility-based survey was conducted using a multistage sampling technique to select 378 women within 12 months' post-partum period. RESULTS: About half of our respondents were <25 years (52.9%), 24.1% were married, 66.4% had at least secondary education and 92.1% were Christians. The most commonly reported barriers were the fear of side effects (22.0%) and the post-partum abstinence (22.2%). Binary logistic regression analysis showed that being within the early post-partum period, i.e., within the first 6 months (adjusted odds ratio [AOR] = 0.23, 95% confidence interval [CI] [0.09-0.60] and lack of access to PPFP [AOR = 0.22, 95% CI [0.09-0.52]). Importantly, women who were married [AOR = 1.686, 95% CI (0.65, 4.36)] and those who were aware of PPFP [AOR 3.69, 95% CI (1.224, 11.096)] increased the likelihood of using PPFP. CONCLUSION: Important barriers to the utilisation of PPFP in Liberia were being within early post-partum period, lack of access and awareness of PPFP including myths and misconception. Therefore, health communication targeting mothers for PPFP at every contact with maternal and childcare services should be encouraged.