Neonatal mortality remains high in Zambia and is declining slower than infant and under five mortality. Improved adoption of essential newborn care (ENC) could help mitigate this situation. To determine the adoption of ENC practices in Zambia, cross-sectional data was used to assess ENC practices including baby kept warm, umbilical cord care and breastfeeding. Chi-square was used to assess whether maternal and social demographic factors were related to ENC. Households surveyed were 12,507, which included 5,741 women with children under two years. Findings show that 95.4% of babies were dried immediately after birth, 96.5% wrapped in a cloth/blanket, 76.7% put on mother’s torso and 68.5% head covered (51.6% for all four). Eighty-five-point six percent of baby’s cords were cut with a sharp and clean instrument, 46% cord kept dry and 42.1% cord kept clean (31.2% for all three). Ninety-six-point nine percent of babies were breastfed, 89.3% were initiated within one hour and 93% exclusively breastfed for the first 3 days post-delivery (82% for all three). Babies kept warm were associated with skilled birth attendance (SBA) and province, umbilical cord care with SBA, >4 antenatal care (ANC) visits, marital status and province, and breastfeeding with >4 ANC visits, marital status and province. Early and exclusive breastfeeding is widely prac-ticed. However, appropriate thermal and cord care practices are low. There is need for a scale-up of appropriate newborn care practices in Zambia and SBA could play an important role in this regard.
Ethical clearance for the multi-sectoral end of program evaluation was obtained from the Zambia ERES Converge Ethics Committee (reference number 2021-April- 008). Informed consent was obtained from respondents, and confidentiality was maintained throughout the evaluation. Personal identifiers such as names were removed and the data stored safely with only authorised persons allowed access to it. The study used a cross-sectional design to evaluate a multi-sectoral end of program evaluation in Zambia. The study used data collected for an evaluation of 28 Area Programs (APs) implemented by World Vision Zambia between 2016 and 2021 and which are predominantly in rural areas. The programs implemented in the APs included Health and Nutrition, Livelihoods, Education and Water, Sanitation and Hygiene and covered 28 districts. The specific APs evaluated included Buyantashi in Luwingu/Lupososhi District, Bwacha in Mungwi District, Chikomeni in Lundazi/Lumezi District, Chipapa in Kafue District, Chongwe East in Rufunsa District, Chongwe South and Kapuluwe in Chongwe District, Choongo in Monze District, Hamaundu and Moyo in Pemba District, Kawaza in Katete District, Lunga in Mwinlunga District, Luswepo and Suwila in Isoka District, Magoye in Mazabuka District, Makungwa in Kasenengwa District, Manyinga in Manyinga District, Mbala in Mbala/Senga Hill District, Mbeza in Namwala District, Mporokoso in Mporokoso District, Muchila in Namwala District, Mudanyama in Mwinlunga District, Mufumbwe in Mufumbwe District, Musosolokwe in Kapiri Mposhi District, Mwamba in Kasama District, Nkeyema in Nkeyema District, Nyimba in Nyimba District, Sinazongwe in Sinazongwe District, Twachiyanda in Kalomo District, Twikatane in Mungwi District and Keembe in Chibombo District. Data collection was done by the University of Zambia, Institute of Economic and Social Research who were contracted by World Vision Zambia. The collection of data was done between April and June, 2021, using World Visions Caregiver Survey questionnaire for program evaluations first published in 20138 and revised in 2020 with adaptations made to suit the Zambia context. Data was collected using mobile phones, cleaned and then uploaded into the server. The broad target population of the evaluation consisted of parents/caregivers of children aged 3-6 years, mothers or caregivers of children under five years and women aged 18 to 49 years and pregnant women. The specific target population for this study was mothers of children aged 0-23 months. Information on ANC, delivery and ENC was based on the mother’s reports. The sample size was calculated using the World Vision sample size calculator available in the Baseline Field Guide.9 The sample size was calculated with the statistical power to detect change set at 0.84, a design effect of 2, with the default probability of committing a Type-1 error set at 1.96. The minimum sample size required in order to detect statistically significant differences between proportions between 2 survey domains at AP level was 358 giving a total of 11,098 for all the 31 APs. A two-stage cluster sampling was used to select sample households to be interviewed. All the APs and their respective zones were included within the sample. The first stage of sampling entailed random selection of villages from zones; however, Probability Proportion to Size (PPS) Zones was used to ensure larger villages and zones contributed more households compared to smaller ones. The zones included were selected by first listing all zones alphabetically and then using systematic random sampling to choose the ones to be included. In the second stage, households were selected using the random walk method starting from the centre of the village. Cleaned data in the server was exported to SPSS version 25, which was used for the analysis. The ENC characteristics of interest included 1. Baby kept warm, which had four sub-components (i) whether the baby was dried immediately after birth (ii) baby wrapped in a warm cloth or blanket (iii) baby put skin to skin on mother’s torso and (iv) baby’s head covered. 2. Umbilical cord care, which had three sub-components (i) umbilical cord cut with a sharp and clean instrument, (ii) umbilical cord kept dry and (iii) umbilical cord kept clean. 3. Breastfeeding, which consisted of three components (i) breastfed at all (ii) breastfed within the first hour and (iii) breastfed within the first three days. These ENC practices were compared across social and demographic strata to see if there were any differences. Weighting was done during the analysis to adjust for the uniform sample sizes used at the AP level as opposed to proportions based on population size.
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