Determinants of Marital Instability in Ibadan, Nigeria

Abstract

This study examined marital instability in Ibadan with focus on the pattern and factors which influence it. Marital instability was represented by three single spouse marital states (divorce, separation and widowhood). The study sampled 186 individuals from city and less city Local Government Areas. Upon estimating a multinomial logit model, age at marriage, gender, ethnic and religious heterogamy, and marriage length were found to significantly affect the likelihoods of divorce and separation. The number of kids in a marriage was significant in the separated category but not in the divorced category. Starting from age 26, the probability of marital instability falls with age at marriage but starts to rise after age 30 in the case of separation and after age 34 in the case of divorce.

Regional variation in early marriage in Kenya

Abstract

Abstract Background: This study seeks to the establish the association between region and early marriage and whether or not the association has changed over time.
Method: The study used a national representative sample of 21315 ever married women aged 20-49 years drawn from the 2014 Kenya Demographic and Health Survey.

Descriptive statistics and logistic regression analysis were used to analyse the data. Results: The study found early marriage prevalence of 32.4% [95% CI: 31.81 – 33.06] and considerable regional variation. Early marriage was significantly associated with region [Rift Valley: aOR =1.22, 95%; 1.07 – 1.39, p value = 0.000; Western: aOR=1.31, 95%; 1.12 – 1.52, p value = 0.000; Nyanza: aOR =2.08, 95%; 1.80 – 2.40, p value = 0.000; North Eastern: aOR=0.63, 95%; 0.45 – 0.82, p value = 0.05; Eastern: aOR= 0.84, 95%; 0.72 – 0.97, p value = 0.05], education [primary education: aOR= 0.63, 95% CI ; 0.56 -0.70; secondary education: aOR= 0.201, 95% CI; 0.18- 0.24, higher education: aOR= 0.05, 95% CI; 0.04 - 0.06], household wealth status [poor: aOR= 1.31, 95% CI; 1.20 – 1.44; middle level: aOR=1.24, CI; 1.13 – 1.36], religion [muslim: aOR= 1.36, 95% CI; 1.14 – 1.61, other non-christian faith: aOR= 1.28, 95% CI; 1.03 - 1.59], premarital sex [ yes: aOR= 1.91, 95% CI; 1.78 – 2.05] , pregnancy [yes: aOR= 1.44, 95% CI; 1.24 – 1.68] and age cohort [30-39: aOR = 0.71, 95% CI; 0.66 – 0.77, 40-49: aOR= 0.80, 95% ; 0.74 – 0.87].

Conclusion: Early marriage significantly varies across the regions of the country and it was varied with education, household economic status, premarital sex and pregnancy experience. The study recommends region specific programs to address early marriage and to improve girls’ education and access to reproductive health information and services.

Keywords: Early marriage, Region, prevalence, variation, Kenya

Résumé

Contexte : Cette étude cherche à établir l'association entre la région et le mariage précoce et si oui ou non l'association a changé au fil du temps. Méthode : L'étude a utilisé un échantillon national représentatif de 21 315 femmes célibataires âgées de 20 à 49 ans tirées de l'enquête démographique et sanitaire de 2014 au Kenya. Des statistiques descriptives et une analyse de régression logistique ont été utilisées pour analyser les données.

Résultats : L'étude a révélé une prévalence du mariage précoce de 32,4% [IC à 95%: 31,81 - 33,06] et une variation régionale considérable. Le mariage précoce était significativement associé à la région [Vallée du Rift : aOR = 1.22, 95 % ; 1,07 – 1,39, valeur p = 0,000; Ouest : aOR = 1,31, 95%; 1,12 – 1,52, valeur p = 0,000; Nyanza: aOR = 2,08, 95%; 1,80 – 2,40, valeur p = 0,000; Nord-Est: aOR =0,63, 95%; 0,45 – 0,82, valeur p = 0,05; Est: aOR = 0,84, 95%; 0,72 – 0,97, p value = 0,05], éducation [primaire : aOR = 0,63, IC 95 % ; 0,56 -0,70; enseignement secondaire : aOR = 0,201, IC 95 % ; 0,18-0,24, études supérieures : aOR = 0,05, IC 95%; 0,04 - 0,06], statut de richesse du ménage [mauvais : aOR = 1,31, IC à 95%; 1,20 – 1,44 ; niveau moyen : aOR = 1,24, IC ; 1,13 – 1,36], religion [ musulman : aOR = 1,36, IC 95 % ; 1,14 – 1,61, autre confession non chrétienne : aOR = 1,28, IC à 95%; 1,03 - 1,59], sexe avant le mariage [ oui : aOR = 1,91, IC 95 % ; 1,78 – 2,05] , grossesse [oui : aOR = 1,44, IC à 95 %; 1,24 – 1,68] et cohorte d'âge [30-39 : aOR = 0,71, IC 95 % ; 0,66 – 0,77, 40-49 : aOR = 0,80, 95 % ; 0,74 – 0,87].

Conclusion: Le mariage précoce varie considérablement d'une région du pays à l'autre et varie en fonction de l'éducation, de la situation économique du ménage, des relations sexuelles avant le mariage et de l'expérience de la grossesse. L'étude recommande des programmes spécifiques à la région pour lutter contre le mariage précoce et améliorer l'éducation des filles et l'accès aux informations et aux services de santé reproductive.

Mots-clés : Mariage précoce, Région, prévalence, variation, Kenya

Decomposition and Spatiotemporal Analysis of Barriers to Healthcare Access among Women of Childbearing age in Nigeria, 2003 – 2018

Abstract

Barriers to Healthcare Access (BHA) amidst cultural demands and abject poverty aggravate the prevailing health challenge among Nigerian women. We aimed to assess the BHA among women of reproductive age in Nigeria.

Four consecutive rounds (2003-2018) of Nigeria Demographic and Health Surveys were used for this cross-sectional design study. Subjects were selected using a multi-stage cluster sampling technique. BHA classified into small and big barrier was generated based on 4 questions: getting permission to go for treatment, getting money needed for treatment, distance to health facility, and not wanting to visit health facility alone. Data were analyzed using Bayesian LRM, Wagstaff decomposition, and ArcGIS version pro-2.7 (α=0.05).

Respondents’ mean age ranges from 31.8±8.75 years in 2003 to 33.6±8.25 years in 2018. Experiencing big BHA was 41.0% (2003), 67.2% (2008), 52.7% (2013), and 53.7% (2018) among the women and was higher in the rural areas across the survey years. In 2018, the percentage of women who experienced big BHA was highest in the North-East (72.0%) and least in the South-West (33.5%). The odds of big BHA reduced consistently with increasing level of education.
Having final say on own health care was protective against big BHA (p<0.001). Education, religion, media exposure, wealth, residence and region were the common predictors of big BHA across the survey-rounds (p<0.001). Factors that contributed mostly to wealth inequality in big BHA from year 2003 to 2018 included education (36.7%), partner’s education (41.1%), and residence (35.5%).

High proportion of women in Nigeria have big BHA, but hot-spot for big BHA was mostly prevalent in the North West, North East, and South East geopolitical zones. Efforts should be geared towards alleviating BHA in Nigeria.

Keywords: Health care access, Maternal health, Barrier to health care, Nigerian women

A qualitative study on contraceptive use among young female university students: What still matters?

Abstract

In South Africa fertility rates have been steadily declining, although unplanned pregnancies among young women are high. At the same time, contraceptive prevalence rates are steadily rising. The purpose of this study was to explore the use of contraceptives among White, female university students. The study participants comprised a sample of 10 female students. An interview guide was used to explore areas in greater depth. Interviews were audiotaped and transcribed verbatim, thereafter the researchers used thematic analysis to derive emergent themes. The findings indicate that there is a high level of awareness of contraceptive use among the participants. The main reasons for contraceptive use was to prevent pregnancy and sexually transmitted infections.

Participants also reported using contraceptives for other health-related reasons such as treatment of acne and regulation of menstrual cycle. The main barrier to use was the fear of contraceptive side effects. Existing initiatives should take into account perceived myths and misinformation regarding contraception in an effort to promote use of modern contraceptives.