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1.
BMC Health Serv Res ; 15: 271, 2015 Jul 17.
Article in English | MEDLINE | ID: mdl-26184765

ABSTRACT

BACKGROUND: Uganda's poor maternal health indicators have resulted from weak maternal health services delivery, including access to quality family planning, skilled birth attendance, emergency obstetric care, and postnatal care for mothers and newborns. This paper investigated the predictors of maternal health services (MHS) utilization characterized as: desirable, moderate and undesirable. METHODS: We used a sample of 1728 women of reproductive ages (15-49), who delivered a child a year prior to the 2011 UDHS survey. A multinomial logistic regression model was used to analyze the relative contribution of the various predictors of ideal maternal health services package utilization. Andersen's Behavioral Model of Health Services Utilization guided the selection of covariates in the regression model. RESULTS: Women with secondary and higher education were more likely to utilize the desirable maternal health care package (RRR = 4.5; 95% CI = 1.5-14.0), compared to those who had none (reference = undesirable MHS package). Women who lived in regions outside Kampala, Uganda's capital, were less likely to utilize the desirable package of maternal health services (Eastern--RRR = 0.2, CI = 0.1-0.5; Western--RRR = 0.3, CI = 0.1-0.8; Central--RRR = 0.3, CI = 0.1-0.8; Northern--RRR = 0.4, CI = 0.2-1.0). Women from the richest households were more likely to utilize the desirable maternal health services package (RRR = 1.9; 95% CI = 1.0-3.7). Residence in rural areas, being Moslem and being married reduced a woman's chances of utilizing moderate maternal health care services. CONCLUSIONS: Utilization of maternal health services varied greatly by demographic and socio-economic characteristics. Women with a secondary and higher education, and those of higher income levels, were more likely to utilize the ideal maternal health services package. Therefore, there is need to formulate policies and design maternal health services programs that target the socially marginalized women.


Subject(s)
Maternal Health Services/statistics & numerical data , Patient Acceptance of Health Care , Adolescent , Adult , Behavioral Research , Delivery, Obstetric/statistics & numerical data , Family Planning Services , Female , Health Care Surveys , Humans , Logistic Models , Middle Aged , Uganda , Young Adult
2.
BMC Public Health ; 15: 262, 2015 Mar 18.
Article in English | MEDLINE | ID: mdl-25885372

ABSTRACT

BACKGROUND: The rationale for promotion of family planning (FP) to delay conception after a recent birth is a best practice that can lead to optimal maternal and child health outcomes. Uptake of postpartum family planning (PPFP) remains low in sub-Saharan Africa. However, little is known about how pregnant women arrive at their decisions to adopt PPFP. METHODS: We used 3298 women of reproductive ages 15-49 from the 2011 UDHS dataset, who had a birth in the 5 years preceding the survey. We then applied both descriptive analyses comprising Pearson's chi-square test and later a binary logistic regression model to analyze the relative contribution of the various predictors of uptake of modern contraceptives during the postpartum period. RESULTS: More than a quarter (28%) of the women used modern family planning during the postpartum period in Uganda. PPFP was significantly associated with primary or higher education (OR=1.96; 95% CI=1.43-2.68; OR=2.73; 95% CI=1.88-3.97 respectively); richest wealth status (OR=2.64; 95% CI=1.81-3.86); protestant religion (OR=1.27; 95% CI=1.05-1.54) and age of woman (OR=0.97, 95% CI=0.95-0.99). In addition, PPFP was associated with number of surviving children (OR=1.09; 95 % CI=1.03-1.16); exposure to media (OR=1.30; 95% CI=1.05-1.61); skilled birth attendance (OR=1.39; 95% CI=1.12-1.17); and 1-2 days timing of post-delivery care (OR=1.68; 95% CI=1.14-2.47). CONCLUSIONS: Increasing reproductive health education and information among postpartum women especially those who are disadvantaged, those with no education and the poor would significantly improve PPFP in Uganda.


Subject(s)
Contraception Behavior/statistics & numerical data , Family Planning Services/statistics & numerical data , Postpartum Period , Adolescent , Adult , Africa South of the Sahara , Age Factors , Chi-Square Distribution , Cross-Sectional Studies , Female , Health Education , Humans , Logistic Models , Middle Aged , Socioeconomic Factors , Uganda , Young Adult
3.
Fertil Res Pract ; 1: 16, 2015.
Article in English | MEDLINE | ID: mdl-28620521

ABSTRACT

BACKGROUND: While recent studies have indicated that fertility has remained high in Uganda, no systematic attempt has been made to identify the factors responsible for this persistent trend and to quantify these factors. This paper uses the Uganda Demographic and Health Surveys (UDHS) of 2006 and 2011, to examine the contribution contraceptive use, marriage and postpartum infecundability on one hand and Total Fertility Rate (TFR) on the other. We constructed a database using the Woman's Questionnaire from the UDHS 2006 and 2011. We then apply Bongaarts aggregate fertility model procedures to derive estimates of total fertility rate for the different socioeconomic groups. RESULTS: The findings indicate that a woman's contraceptive behavior; marriage status and postpartum infecundability (also referred to as postpartum insusceptibility due to postpartum amenorrhea, which is intended to measure the effects on fertility breastfeeding), are important predictors of fertility outcomes. The results also show that higher education levels and urban residence are consistently associated with lower fertility rates and are positively associated with contraceptive use. Other key predictors of fertility include: wealth status, and region of residence. CONCLUSION: The country needs to scale-up target interventions that are aimed at uplifting the education status of women and improving their economic wellbeing, because such interventions have a positive impact on fertility reduction and on improving maternal and reproductive health outcomes.

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