ABSTRACT
BACKGROUND: Happiness is the most indicator of good quality of life particularly for pregnant women. Reduced happiness of pregnant women can result in reduced maternal health services utilization and can result in adverse newborn and maternal outcomes. Assessing the level of happiness and its factors are important for pregnant women and the next generation. Hence, the current research paper aimed to assess the level of happiness and its associated factors among pregnant women who attended antenatal care follow-up in South Gondar Zone Hospitals. METHODS: Institution-based cross-sectional study was carried out from September 2018 to February 2019 among 1606 expectant pregnant women in the last 6 months. The Oxford Happiness Questionnaire (OHQ) was used as a measure of the degree of happiness and used four as average person score. Besides, bivariate, multivariable logistic analyses were deployed to identify associations. RESULTS: A total of 1606 pregnant women were participating in this study. The prevalence of low level of pregnancy happiness in this study was 24% (95% CI: 20.7 -26.6). Mothers who exposed to unintended pregnancy (AOR; 1.94, CI 95% 1.86-4.52), reported intimate partner violence (AOR; 2.42, 95% CI 1.67-3.54) and being in the third trimester (AOR; 1.89 95% CI 1.19-3.01) were the most predictor variables with the low level of happiness. CONCLUSION: Approximately one-fourth of the pregnant women had a low level of pregnancy happiness. Mothers who were exposed to unintended pregnancy encountered intimate partner violence, who were in the third trimester were the most significant variables associated with a low level of happiness. Governmental and non-governmental organizations work on women's reproduction rights and the zonal health department with local health offices should educate on the prevention of intimate partner violence and unintended pregnancy and its consequences and also empower women to cope with changes and challenges of pregnancy and childbirth.
ABSTRACT
BACKGROUND: After prematurity, intrauterine growth restriction (IUGR) is the second leading cause of perinatal mortality. IUGR has significant consequences in fetal, neonatal, and adult life. Currently, Ethiopia lacks information on IUGR's prevalence and its determinants. This study aimed to assess the proportion of IUGR at birth and its associated factors. METHODS: A cross-sectional study was carried out among women who give birth in four hospitals of south Gonder zone from November 2018 to February 2019. Multi-stage sampling was applied to select the required samples. IUGR was assessed using a standardized cutoff percentile/mean for each measurement. Data were collected by trained MSc clinical midwives. Bi-variable and multivariable logistic analyses were deployed to identify the association. RESULTS: A total of 803 maternity women were participating in this study with a response rate of 95%. The proportion of IUGR 23.5% (95% CI: 20.7-26.6), low birth weight 13.3%, small-for- gestational-age 19.7%,and preterm birth 23.16%. Women who was unable to read and write, (AOR; 2.46, 95% CI: 1.02-5.92), total family size ≥7 (AOR; 1.67, 95% CI: 1.04-2.66), maternal mid-upper arm circumference (MUAC) < 23 cm (AOR; 2.10, 95% CI: 1.39-3.01), body mass index (BMI) < 18.5 kg/m2 (AOR; 2.57, 95% CI: 1.72-3.83), altitude > 3000 m (AOR; 1.89 95% CI: 1.19-3.01), small placental size (< 350 g) (AOR; 2.42, 95% CI: 1.67-3.54) and small-for-gestational-age (AOR; 1.94, 95% CI:1.86-4.52) were the most predictors of IUGR. CONCLUSIONS: IUGR was a major public health concern in this study. Women who were unable to read and write, small-for-gestational-age, maternal BMI < 18.5 kg/m2, family size ≥7, maternal MUAC < 23 cm, small placental size, and altitude > 3000 m were found the most predictor variables. Strengthen female education, nutritional intervention before and during pregnancy, and routine maternity care is critical. Further clinical follow-up research is essential which includes maternal, fetal, and placental gens.
ABSTRACT
BACKGROUND: Measurements of erect height in older people, hospitalized and bedridden patients, and people with skeletal deformity is difficult. As a result, using body mass index for assessing nutritional status is not valid. Height estimated from linear body measurements such as arm span, knee height, and half arm span was shown to be useful surrogate measures of stature. However, the relationship between linear body measurements and stature varies across populations implying the need for the development of population-specific prediction equation. The objective of this study was to develop a formula that predicts height from arm span, half arm span, and knee height for Ethiopian adults and assess its agreement with measured height. METHODS: A cross-sectional study was conducted from March 15 to April 21, 2016 in Jimma University among a total of 660 (330 females and 330 males) subjects aged 18-40 years. A two-stage sampling procedure was employed to select study participants. Data were collected using interviewer-administered questionnaire and measurement of anthropometric parameters. The data were edited and entered into Epi Data version 3.1 and exported to SPSS for windows version 20 for cleaning and analyses. Linear regression model was fitted to predict height from knee height, half arm span, and arm span. Bland-Altman analysis was employed to see the agreement between actual height and predicted heights. P values < 0.05 was used to declare as statistically significance. RESULTS: On multivariable linear regression analyses after adjusting for age and sex, arm span (ß = 0.63, p < 0.001, R2 = 87%), half arm span (ß = 1.05, p < 0.001, R2 = 83%), and knee height (ß = 1.62, p < 0.001, R2 = 84%) predicted height significantly. The Bland-Altman analyses showed a good agreement between measured height and predicted height using all the three linear body measurements. CONCLUSION: The findings imply that in the context where height cannot be measured, height predicted from arm span, half arm span, and knee height is a valid proxy indicator of height. Arm span was found to be the best predictor of height. The prediction equations can be used to assess the nutritional status of hospitalized and/or bedridden patients, people with skeletal deformity, and elderly population in Ethiopia.
