Background: Preconception care is one of the preventive strategies in maternal and new-born health as recommended by WHO. However, in sub-Saharan Africa there is poor preconception care practices. This study examined knowledge and perceptions of preconception care among health workers and women of reproductive age group in Mzuzu City, Malawi. Methods: A descriptive cross-sectional study was conducted using a mixed methods approach. Selection of respondents was done through a multistage and purposive sampling techniques respectively. A total of 253 women of reproductive age from nine townships of Mzuzu City responded to the questionnaire and 20 health workers were interviewed. Results: A total of 136 (54%) respondents had heard of preconception care. About 57.7% (n = 146) demonstrated a good level of knowledge of preconception care while 42.3% (n = 107) had poor knowledge. About 72% (n = 105) of those with good of knowledge of preconception care, lacked awareness on possibilities of talking to a health care provider on intentions of getting pregnant. About 74.7% (n = 189) of women had a positive perception towards preconception care. Knowledge of preconception care was a good predictor of positive perception (AOR = 2.5; 95% CI 1.2–5.0), however its predictability was influenced by the academic level attained. Those with secondary (AOR = 10.2; 95% CI 3.2–26.2) and tertiary (AOR = 2.3; 95% CI 1.1–4.9) were more likely to have good knowledge of preconception care than those with primary school education level. About 95% (n = 19) of health workers lacked details about preconception care but they admitted their role in preconception care. Conclusion: Preconception care practice among health workers and women of reproductive age in Mzuzu City was low. However there was positive perception towards preconception care in both parties. There is an opportunity in existing platforms for implementation of interventions targeting identified predictors for increased knowledge and uptake of preconception care.
Malawi as a country is divided into three distinct regions namely; northern, central and southern. The northern region is reported to have the highest antenatal care coverage of 46% and 92% skilled birth attendants [8]. The study was conducted in Mzuzu City which is located in the northern region of Malawi with a land area coverage of 48 km2 and a population of 220,000 people [9]. Atleast 60% of Mzuzu population resides in informal settlements [9]. Study participants were drawn from the nine townships of Mzuzu City based on their geographical area population [10] namely: Chibanja, Chibavi, Mchengautuba, Katoto, Masasa, Zolozolo, Chiputula, Katawa and Luwinga (Fig. 1). The study was conducted from June 2018 to October 2019. Selected study sites within Mzuzu City where respondents for the study were drawn This was a community based cross sectional design employing a mixed method approach. Semi-structured questionnaires (see Additional file 1) and interview guides (see Additional file 2) were used as instruments for collecting quantitative and qualitative data from women of child bearing age and health workers respectively. The minimum sample size for the study was determined by using a single population proportion formula with the following assumptions; P = 23% (50,600 women of the reproductive age group against a population of 220,000, [3], 95% level of significance (α = 0.05), Zα/2 = 1.96, 5% margin of error (d = 0.05), design effect (DEEF) of 3 and 20% non-response rate [11]. The design effect was calculated using the following formula: DEFF = 1 + δ (n − 1). where: δ = intraclass correlation coefficient, n = average size of clusters. The intraclass correlation coefficient for this study was 0.2 and the average cluster size was 6.7 giving a final DEEF of 2.6–3 [12]. The total sample size was 245. A multistage cluster sampling was employed to draw women of child bearing age from nine townships of Mzuzu City while purposive sampling technique was used to select 20 skilled birth attendants. There are basically 15 wards in Mzuzu city with at least two block leaders per ward [13]. The 15 wards were stratified based on their geographical location into three stratums of five wards each. Three wards were randomly selected from each stratum to give a total of nine wards. The selected wards were divided into clusters based on block leadership. Sample size was proportionally allocated to the selected nine wards. Selection of the respondents from the clusters were through a systematic random sampling based on a block leader’s list of women of reproductive age. Semi-structured questionnaire adapted from different literature sources [14–17] was pretested on 10% of respondents outside the target population, modified and used to collect demographic characteristics, level of knowledge on preconception care. Women’s Knowledge of preconception care was assessed using the individual respondent’s correct response to 16 items (Screening for hypertension, anaemia, diabetes mellitus, sexually transmitted infections, blood group, obesity, hepatitis B; HIV/AIDS testing and counselling; taking a balanced diet and vitamins; avoiding smoking and drinking alcohol; consulting a gynecologist or health care practitioner for advice; discussing with husband when to have a baby; having routine body exercises; awareness of issues that affect fetal development such as trauma, over the counter drugs, lack of vitamins/folic acid, natural herbs/chemicals; awareness about folic acid tablets and when they are to be taken; awareness of a baby being born with problems) [18, 19]. A score of 1 and 0 were used for correct and incorrect answers respectively. A composite knowledge score was generated through summing up 1 score for YES answers from 16 questions. Women who scored half and above (≥ 8 correct responses to the 16 questions) were regarded as ‘women with good knowledge of PCC’ whereas those who scored below 50% (< 8 incorrect responses to the 16 questions) were considered as ‘women with poor knowledge of PCC [12]. Health worker’s knowledge of preconception care was assessed using question one to six. Perception was assessed through asking women whether they felt that preconception care is beneficial; whether discussing with husband and health care worker on intentions to get pregnant is good; whether going for screening for medical conditions with husband before conception is good, whether they feel practicing family planning is good. A score of 1 and 0 was used for good and not good respectively. Women who scored 50% and above (≥ 2 out of 4 items) were rated as having positive perception and those that scored below 50% (< 2 out of 4 items) were rated as having negative perception. The quantitative study used questionnaires [12, 20], whilst the qualitative study used interview guides for data collection. The questionnaire was developed in excel then uploaded on field task software capturing demographic data, level of knowledge on preconception care and factors that can influence access to preconception care from women of child bearing age. The questions asked were related to knowledge of folic acid, promotion of good pregnancy, factors that can affect fetal development and awareness of fetus developing congenital anomalies. Semi-structured interviews were used to collect data on knowledge and perceptions of health workers on preconception care. Interviews were recorded using a tape recorder. Quantitative data was analysed using a statistical product for service solutions (SPSS) version 20. Descriptive statistics involved generation of frequency distributions of demographic characteristics. Inferential statistics through a Pearson Chi-square test was used to measure the association of age, marital status, education level, number of children family planning history with perception and knowledge level. A multivariable logistic regression was performed to identify factors that were significantly associated with perception and knowledge level at bivariate level of analysis (p < 0.05) to determine adjusted odds ratios (AOR). The odds ratios (OR) associated with these factors were reported as a measure of strength, together with the respective 95% confidence intervals. Qualitative data from key informant interviews transcriptions were analyzed thematically and were presented as textual expressions and direct quotations.
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