Prevalence and factors associated with early childbearing in sub-saharan Africa: evidence from demographic and health surveys of 31 countries.

BACKGROUND: Early childbearing remains a public health concern in sub-Saharan Africa (SSA) because it has substantial implications for women's and children's health and population control. However, little is known about recent changes in early childbearing in the region following the implementation of the Family Planning 2020 initiative (FP2020) national-level interventions. Thus, this study examined factors associated with early childbearing among women in SSA. METHODS: The study used data from the most recent Demographic and Health Surveys conducted in 31 countries in sub-Saharan Africa between 2010 and 2021. The analysis included a pooled sample of 54,671 parous young women aged 20-24 years. A multivariable binary logistic regression model was used to examine the association between early childbearing and individual and household-level factors. All analyses were weighted to account for complex survey design. RESULTS: The study shows that the mean prevalence of early childbearing was high in SSA at 39% (95% CI: 35, 43). Chad had the highest prevalence of early childbearing, 62% (95% CI: 60, 64) while Rwanda had the lowest prevalence of 13% (95% CI: 11, 15). Completing secondary school (aOR = 0.57; 95% CI: 0.52, 0.62) or attaining tertiary level education (aOR = 0.32; 95% CI: 0.22, 0.45), first sexual debut in the age range 15-24 years (aOR = 0.15; 95% CI: 0.14, 0.16) and desire for a small family size (aOR = 0.63; 95% CI: 0.58, 0.69) were associated with reduced odds of early childbearing among young women in SSA. CONCLUSION: The study has established that the prevalence of early childbearing is high in SSA. Level of education, age at first sexual debut, household size, and desired family size are associated with early childbearing in SSA. Governments of SSA countries should enhance sexual and reproductive health interventions to change reproductive behaviour, particularly in adolescents and young women.

Contrasting HIV prevalence trends among young women and men in Zambia in the past 12 years: data from demographic and health surveys 2002-2014.

BACKGROUND: The HIV epidemic remains a concern on the global health agenda, despite progress made in reducing incidence. Investigation of trends among young people is important for monitoring HIV incidence and informing programming. The study examined geographical and sub-population differences in HIV prevalence trends among young people aged 15-24 years in Zambia. METHODS: This study analysed data from Zambia Demographic and Health Surveys (ZDHSs) that were conducted in 2001-2, 2007, and 2013-14. A two-stage cluster stratified sampling procedure was used to select samples of 8050, 7969, and 18,052 for the three surveys, respectively. Young people (15-24 years) with known HIV status were selected for analysis. The outcome variable was HIV status. Log binomial regression analysis of generalised linear models was used to test for trends. RESULTS: Overall HIV prevalence declined over the period 2001-2 to 2013-14 among women and men aged 15-49 years (17.8 and 12.9% to 15.1 and 11.3%, respectively). There was, however, an increase in HIV prevalence among urban young men over this period, from 3.7% in 2001-2 to 7.3% in 2013-14 (aRR 2.17, 95% CI 0.99-4.75), and, in rural areas, from 2.6 to 3.6% (aRR 1.46, 95% CI 0.78-2.75). In contrast, HIV prevalence among women declined over the same period of time. In urban areas, HIV prevalence among women declined from 15.2 to 10.7% (aRR 0.66, 95% CI 0.53-0.93), while in rural areas it declined from 8.2 to 4.8% (aRR 0.41, 95% CI 0.59-0.85). In addition, there was a narrowing gender gap in terms of HIV infection, as the prevalence ratio of females to males declined from 4.2 and 3.1 to 1.5 and 1.3, in urban and rural areas, respectively. CONCLUSIONS: The increase in HIV prevalence among urban young men over the past 12 years, contrasting declining trends among young women in both urban and rural populations, suggests differential effects of prevention efforts. Furthermore, findings that Zambia's overall national HIV prevalence decline masks some striking sex and rural/urban differentials, indicate the need for reconsidering the prevention efforts for young urban men.

Who is missed in a community-based survey: Assessment and implications of biases due to incomplete sampling frame in a community-based serosurvey, Choma and Ndola Districts, Zambia, 2022.

Community-based serological studies are increasingly relied upon to measure disease burden, identify population immunity gaps, and guide control and elimination strategies; however, there is little understanding of the potential for and impact of sampling biases on outcomes of interest. As part of efforts to quantify measles immunity gaps in Zambia, a community-based serological survey using stratified multi-stage cluster sampling approach was conducted in Ndola and Choma districts in May-June 2022, enrolling 1245 individuals. We carried out a follow-up study among individuals missed from the sampling frame of the serosurvey in July-August 2022, enrolling 672 individuals. We assessed the potential for and impact of biases in the community-based serosurvey by i) estimating differences in characteristics of households and individuals included and excluded (77% vs 23% of households) from the sampling frame of the serosurvey and ii) evaluating the magnitude these differences make on healthcare-seeking behavior, vaccination coverage, and measles seroprevalence. We found that missed households were 20% smaller and 25% less likely to have children. Missed individuals resided in less wealthy households, had different distributions of sex and occupation, and were more likely to seek care at health facilities. Despite these differences, simulating a survey in which missed households were included in the sampling frame resulted in less than a 5% estimated bias in these outcomes. Although community-based studies are upheld as the gold standard study design in assessing immunity gaps and underlying community health characteristics, these findings underscore the fact that sampling biases can impact the results of even well-conducted community-based surveys. Results from these studies should be interpreted in the context of the study methodology and challenges faced during implementation, which include shortcomings in establishing accurate and up-to-date sampling frames. Failure to account for these shortcomings may result in biased estimates and detrimental effects on decision-making.

Challenges Addressing Inequalities in Measles Vaccine Coverage in Zambia through a Measles-Rubella Supplementary Immunization Activity during the COVID-19 Pandemic.

BACKGROUND: Measles-rubella supplementary immunization activities (MR-SIAs) are conducted to address inequalities in coverage and fill population immunity gaps when routine immunization services fail to reach all children with two doses of a measles-containing vaccine (MCV). We used data from a post-campaign coverage survey in Zambia to measure the proportion of measles zero-dose and under-immunized children who were reached by the 2020 MR-SIA and identified reasons associated with persistent inequalities following the MR-SIA. METHODS: Children between 9 and 59 months were enrolled in a nationally representative, cross-sectional, multistage stratified cluster survey in October 2021 to estimate vaccination coverage during the November 2020 MR-SIA. Vaccination status was determined by immunization card or through caregivers' recall. MR-SIA coverage and the proportion of measles zero-dose and under-immunized children reached by MR-SIA were estimated. Log-binomial models were used to assess risk factors for missing the MR-SIA dose. RESULTS: Overall, 4640 children were enrolled in the nationwide coverage survey. Only 68.6% (95% CI: 66.7%, 70.6%) received MCV during the MR-SIA. The MR-SIA provided MCV1 to 4.2% (95% CI: 0.9%, 4.6%) and MCV2 to 6.3% (95% CI: 5.6%, 7.1%) of enrolled children, but 58.1% (95% CI: 59.8%, 62.8%) of children receiving the MR-SIA dose had received at least two prior MCV doses. Furthermore, 27.8% of measles zero-dose children were vaccinated through the MR-SIA. The MR-SIA reduced the proportion of measles zero-dose children from 15.1% (95% CI: 13.6%, 16.7%) to 10.9% (95% CI: 9.7%, 12.3%). Zero-dose and under-immunized children were more likely to miss MR-SIA doses (prevalence ratio (PR): 2.81; 95% CI: 1.80, 4.41 and 2.22; 95% CI: 1.21 and 4.07) compared to fully vaccinated children. CONCLUSIONS: The MR-SIA reached more under-immunized children with MCV2 than measles zero-dose children with MCV1. However, improvement is needed to reach the remaining measles zero-dose children after SIA. One possible solution to address the inequalities in vaccination is to transition from nationwide non-selective SIAs to more targeted and selective strategies.

Examining the association between HIV prevalence and socioeconomic factors among young people in Zambia: Do neighbourhood contextual effects play a role?

BACKGROUND: The study examined the association between HIV infection and individual and neighbourhood-level socioeconomic factors in Zambia. METHODS: We used multilevel mixed effects logistic regression to examine the association of individual and neighbourhood level variables on HIV prevalence based on data from the 2013-14 and 2018 Zambia Demographic and Health Surveys, population-based cross-sectional surveys. The analysis was restricted to young people (15-24 years) with HIV serostatus results (n = 11,751 and n = 10,154). HIV serostatus was the outcome variable and socioeconomic status was measured by wealth, education and employment. RESULTS: Overall, at individual level, education was associated with reduced odds of HIV infection among young women and men. Conversely, relative wealth was generally associated with increased odds of infection for both young women and men. Young, employed men were at reduced odds of HIV infection than the unemployed. Living in neighbourhoods with higher average level of education was associated with higher odds of HIV infection. In 2013-14, 13% and 11% of the variation in HIV infection among young men and women was attributed to neighbourhoods, while 20% and 11% variation was attributed to neighbourhoods in 2018. Inclusion of individual and neighbourhood variables in the full regression model accounted for 65.7% and 59.5% of explained variance in 2013-14 and 64.6% and 44.3% in 2018, for women and men, respectively. This reduced unexplained variance by an average of 56% in 2013-14 and 29% in 2018. CONCLUSION: We found that HIV infection among young people in Zambia is more strongly associated with individual-level socioeconomic factors compared to neighbourhood factors. Individual-level education remains an important socioeconomic factor associated with reduced odds of HIV infection. This suggests that the HIV response in Zambia should still focus on individual level prevention strategies.