Knowledge and Attitude of Women of Reproductive Age (15–49 years) on Maternal Capabilities and Infant Nutrition in the First 1000 Days of Life in Umuahia South LocalGovernment Area, Abia State

Knowledge and Attitude of Women of Reproductive Age (15–49 years) on Maternal Capabilities and Infant Nutrition in the First 1000 Days of Life in Umuahia South LocalGovernment Area, Abia State | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Knowledge and Attitude of Women of Reproductive Age (15–49 years) on Maternal Capabilities and Infant Nutrition in the First 1000 Days of Life in Umuahia South LocalGovernment Area, Abia State Ijioma Okorie, Blessing Osegbo, Chinyere Confidence Ojinika This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7313620/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Maternal capabilities refer to some of the attributes such as decision-making autonomy, gender-norm attitude, social support and self-efficacy, possessed by mothers to adequately care for themselves and their children. This paper aims assess the maternal capabilities, knowledge, and attitudes of women of reproductive age (WRA) regarding infant nutrition during the first 1000 days of life in Umuahia South Local Government Area (LGA). Methodology A community-based cross-sectional design was used to recruit 193 WRA from 6 communities in both semi-urban and rural areas of the LGA. A semi-structured questionnaire was used to obtain demographic and socioeconomic data, knowledge and attitudes of WRA on infant nutrition. Maternal capabilities survey tool was adopted for the study. Data were analysed using descriptive statistics (frequency, percentage, mean and standard deviation), and linear regression, while level of significance was set at p < 0.05. Results More (53.8%) of the WRA had lower decision-making autonomy, 90.3% had lower levels of social support, and 88.7% had low self-efficacy. Also, 52.2% of WRA had good knowledge, while 54.3% had positive attitudes regarding infant nutrition. Unemployment had significant influence ( p < 0.05 ) on both social support and mental health. Higher income statistically influence ( p < 0.05 ) maternal self-efficacy, with 21% variability. Conclusion Most of the respondents had lower levels of social support and self-efficacy. Unemployment was strongly linked to lower social support and mental health, while higher income levels increased self-efficacy. attitudes infant nutrition knowledge maternal capabilities women of reproductive age Figures Figure 1 Figure 2 INTRODUCTION Maternal capabilities refer some of the attributes such as decision-making autonomy, gender-norm attitude, social support and self-efficacy, possessed by mothers to adequately care for themselves and their children. Maternal nutrition plays a key role in shaping the health outcomes of both the mother and the child. Malnutrition during pregnancy and early childhood can have long-term consequences on the physical and cognitive development of the child [ 1 ]. Establishing healthy eating habits in infants and toddlers is crucial for their overall growth, as well as social, emotional, and cognitive development [ 2 , 3 ]. Therefore, guidance on infant and toddler nutrition should encompass not only recommended foods but also strategies for creating an environment that fosters healthy eating habits. Infancy, which lasts from birth to two years, is particularly important because it establishes the foundation for long-term food choices, dietary patterns, and obesity risk [ 4 , 5 ]. The first 1000 days of life, from conception to age two, offer a critical window of opportunity to prevent the long-term effects of under-nutrition. Recognizing the importance of this period is crucial for improving child health and well-being globally. During fetal life and early childhood, the body undergoes rapid growth and development, making this a vital phase for establishing a strong foundation for lifelong health [ 6 ]. The global importance of maternal knowledge, attitudes, and child-feeding practices cannot be overstated. Breastfeeding is a critical component of infant health, and the timing of breastfeeding initiation can significantly impact neonatal outcomes [ 7 ]. The World Health Organization (WHO) and United Nations Children’s Fund (UNICEF) [ 7 ] launched a global initiative to promote best practices for infant feeding. The strategy aims to address suboptimal feeding practices among women of reproductive age by recommending that breastfeeding begin within the first hour of birth, be exclusive for the first six months of life, and introduce nutritious, safe, and age-appropriate complementary foods while breastfeeding for at least two years and beyond. This holistic strategy attempts to provide the optimum nutrition for infants’ growth, development, and health. Despite global guidelines for healthy infant feeding, actual nutrition practices during the critical first 1,000 days of life are significantly shaped by a combination of factors. These include maternal knowledge and attitudes regarding infant nutrition, alongside maternal capabilities such as decision-making autonomy, self-efficacy, prevailing gender norms, social support, and mental health. [ 7 , 8 ]. Empowering women of reproductive age through nutrition education and autonomous decision-making can significantly improve maternal and child health outcomes, ultimately promoting optimal growth and development [ 9 , 10 ]. To overcome this, informed policies and interventions are required to promote maternal capabilities, knowledge, and attitudes toward improved infant nutrition. This paper aims to assess knowledge and attitude of women of reproductive age (15–49 years) on maternal capabilities and infant nutrition in the first 1000 days of fife in Umuahia South Local Government Area, Abia State. METHODS Study design A community-based cross-sectional design was used to collect quantitative data on maternal capabilities, knowledge, and attitudes of women of reproductive age (WRA) (15–49 years) on infant nutrition in Umuahia South Local Government Area. Study population and sample size The study population was 186 WRA living in communities in Umuahia South Local Government of Abia State. Pregnant women, lactating mothers and other WRA who were sick at the time of the study were excluded. The sample size for the study was estimated using Cochran’s formula described by Araoye [ 11 ]. n = \(\:\frac{{Z}^{2}P\:(100-P)}{e²}\) margin of tolerable sampling error applied was 5% P = prevalence of attitudes on good nutrition WRA in rural Nigeria, 86.89% according to Fasola et al. [ 12 ]. N = \(\:\frac{{1.96}^{2\:}X\:86.89(100-86.89)}{{5}^{2}}\) = \(\:\frac{3.8416\:X\:\:86.89\left(13.11\right)}{25}\) = \(\:\:\frac{3.8416x1139.1279}{25}\) = 175.04 = 175. To calculate the attrition rate, 10% of the initial sample size of 175 was added. This calculation is as follows: 175 x 0.10 = 17.5 Adding this to the initial sample size: 175 + 17.5 = 192.5 Rounding up to the nearest whole number: 192.5 ≈ 193. Therefore, the adjusted sample size to account for attrition is 193. Design effect (Deff) was estimated to take care of design features. Thus, 193 x 1.1 = 212.3. Therefore, the adjusted sample size was approximately 212. Sampling procedure The study took place in Umuahia South LGA, employing a multi-stage cluster sampling method. To begin, the LGA was divided into semi-urban and rural areas to ensure representation was proportional. The sample size of 212 women was then allocated between these areas, with 60% from semi-urban areas and 40% from rural areas. In the next stage, six clusters were randomly chosen from a list of wards and communities. Three semi-urban clusters (Olokoro, Ubakala, and Umuahia semi-urban) and three rural clusters (Amuzu, Okporoenyi, and Nnono) were selected. Households within each cluster were then systematically sampled, with approximately 127 women chosen from semi-urban clusters and 85 from rural clusters. To ensure equal representation, a random starting point was chosen in each cluster, and every 5th household was selected. In households with multiple eligible women, simple random sampling by balloting without replacement was used to select one respondent. Ultimately, 212 women of reproductive age were recruited for the study. Data collection tool A validated and pretested semi-structured questionnaire was used to collect quantitative data on background information, and socioeconomic characteristics of women of reproductive age. WHO/UNICEF [ 13 ] maternal, infant and young child nutrition construct was used to measure knowledge and attitudes of women of reproductive age towards infant and young child nutrition, while maternal capabilities construct developed by Stoltzfus et al. [ 14 ] was adopted for the study. Data collection The sample size was originally 212 but 12% of them drooped out. The achieved number of responses was thus 186. The respondents were interviewed using a semi-structured questionnaire to obtain background information. To assess knowledge and attitudes, the following methods were used: Knowledge Assessment: 7 questions were asked to evaluate knowledge. Correct answers were assigned 1 mark, while incorrect answers received 0 marks. The results were standardized to allow for a maximum score of 70% and a minimum score of 0%. Knowledge levels were categorized as follows: Good knowledge: 35–70%. Poor knowledge: 0-34.99%. 6 questions were asked to evaluate attitudes, with responses coded on a 3-point Likert scale (agree, undecided, and don’t know). Correct answers were assigned 1 mark, while incorrect answers received 0 marks Attitude levels were categorized as follows: Positive attitudes: 30–60%; Negative attitudes: 0-29.99%. Maternal capabilities construct include; decision-making autonomy: A 5-question assessment was used, with responses coded as 0 (no) or 1 (yes). The score was calculated by summing the responses. Gender norm attitudes: A 6-question assessment was used, with responses rated on a 5-point Likert scale (1 = restrictive, 5 = egalitarian). The score was calculated by averaging the responses. Maternal depressive symptoms: A 10-question assessment was used, with responses rated on a 4-point Likert scale (0 = lowest, 30 = highest). The score was calculated by summing the responses. Mothering self-efficacy: A 6-question assessment was used, with responses rated on a 5-point Likert scale (1 = low, 5 = high). The score was calculated by averaging the responses. Perceived health status: An 11-question assessment was used, with responses recoded on a 0–5 scale (0 = least healthy, 5 = most healthy). The score was calculated by averaging sub-scores, following the source instructions. Perceived social support: A 16-question assessment was used, with responses rated on a 5-point Likert scale (1 = low, 5 = high). The score was calculated by averaging the responses. Perceived time stress contained 5 questions with 5-point Likert scale, where 1 = low levels of stress and 5 = high levels of stress. Score calculated as means of 5 responses. Statistical analysis Descriptive statistics, namely frequency and percentage, as well as mean and standard deviation were used for the background information/socioeconomic characteristics, knowledge, and attitudes towards infant nutrition, and maternal capabilities variables. Regression analysis was conducted to examine the influence of socioeconomic characteristics on maternal capabilities, knowledge of, and attitudes towards infant nutrition. A significant difference was declared at p < 0.05. The IBM-SPSS software version 27 was used for the analysis. Study variables The independent variables in this paper are the socioeconomic data such as education, occupation and income. They were further categorized into, low education (respondents with no formal education, and with primary education) and high education (respondents with secondary and tertiary education); unemployed and employed; and low income levels (< 30,000 – 50,000) and high income levels (above 50,000). While in this paper, dependent variables are the components of maternal capabilities, such as decision-making autonomy, gender norm attitude, social support, perceived health status, mothering self-efficacy, perceived time stress, and maternal mental health, knowledge and attitudes towards infant nutrition. Components of maternal capabilities, knowledge and attitudes were further categorized as shown in Tables 1 and 2 , respectively. However, in this paper we also determined the influence of attitudes (as independent variable) on maternal capabilities (self-efficacy) (as the dependent variable). Table 1 Categorical variables Categorical variables Level Decision-making autonomy Lower decision-making autonomy Greater decision-making autonomy 0.00–3.00 3.10–5.00 Gender- norm attitude Restrictive gender-norm attitude Egalitarian gender-norm attitude 0.00–3.00 3.10–6.00 Social support Low levels of social support High levels of social support 0.00–3.00 3.10–5.00 Perceived health status Least healthy Healthy 0.00–3.00 3.10–5.00 Mothering self-efficacy Low self-efficacy High self-efficacy 0.00–3.00 3.10–5.00 Perceived time stress Low levels of time stress High levels of time stress 0.00–3.00 3.10–5.00 Maternal mental health Low depressive symptoms High depressive symptoms 0.00–9.99 ≥ 10 Stoltzfus et al. [ 14 ]. Table 2 Categorical variables continued Categorical variables Level Knowledge Poor knowledge Good knowledge 0–34.99% 35–70% Attitude Negative attitude Positive attitude 0–29.99 30–60 The authors developed the levels to meet the paper needs, as highlighted in the data collection section. RESULTS Table 3 presents the background information and socioeconomic characteristics of the respondents (women of reproductive age). The respondents’ age ranged from 15 to 35 years, with a mean age of 27.94 years. Some of the respondents were aged, 30–35 years (33.9%), 25–29 years (31.7%), and 20–24 years (26.3%). It was found that 44.6% of the respondents were married, with 38.7% of them living with their spouses, while 55.4% were not married. In terms of education, 70.4% of the respondents had tertiary education, some had secondary education (14.5%), primary education (7.5%), while 7.5% no formal education. The respondents’ occupations varied, with 23.7% unemployed, 24.7% engaged in business/trading, 16.7% artisans/skilled workers, 17.2% students, and 15.1% in civil/public service. Regarding income, 41.9% of the respondents earned less than 30,000 per month, while only 8.6% of the respondents earned 91,000 and above per month. Table 3 Background information and socioeconomic characteristics of women of reproductive age Variables Frequency (n = 186) Percentage (%) Mean age (27.94 ± 7.14) Age range 15–19 years 15 8.1 20–24 years 49 26.3 25–29 years 59 31.7 30–35 years 63 33.9 Marital status Married 83 44.6 Not married 103 55.4 Living with spouse 72 38.7 Not living with spouse 11 5.9 Level of education No primary education 14 7.5 Primary education 14 7.5 Secondary education 27 14.5 Tertiary education 131 70.4 Occupation Unemployed 44 23.7 Business/Trading 46 24.7 Civil/Public servant 28 15.1 Artisan/Skill worker 31 16.7 Students 32 17.2 Others (sales girl) 5 2.7 Income level < 30,000 78 41.9 30,000 – 50,000 48 25.8 51,000 – 70,000 21 11.3 71,000 – 90,000 23 12.4 91,000 and above 16 8.6 Table 4 shows maternal capabilities (decision-making autonomy, gender-norm attitude, social support, perceived health, mothering self-efficacy, perceived time stress, and maternal mental health) of the respondents. A little above half (53.8%) of the respondents had lower decision-making autonomy, while 46.2% had greater decision-making autonomy. Also, 55.9% of the respondents held restrictive gender-norm attitudes, which suggests adherence to traditional gender roles, while 46.2% held egalitarian gender-norm attitudes, that is, a significant proportion held more progressive views. The respondents’ social support levels varied, with 90.3% experienced low levels of social support, while only 9.7% had high levels of social support. Majority (98.4%) of the respondents perceived themselves as healthy, while 1.6% reported being in poor health (least healthy). The paper also showed that, 88.7% of respondents had low self-efficacy, while 11.3% had high self-efficacy. The paper found that 52.7% of the respondents reported low levels of time stress, while 45.2% reported high levels of time stress. For mental health status, 62.7% of respondents reported low depressive symptoms, while 37.3% reported high depressive symptoms. Table 4 Maternal capabilities of women of reproductive age Maternal capabilities Frequency (n = 186) Percentage % Mean score Decision-making autonomy 3.51 ± 1.32 Lower decision-making autonomy 100 53.8 Greater decision-making autonomy 86 46.2 Gender-norm attitude 3.08 ± 0.60 Restrictive gender-norm attitude 104 55.9 Egalitarian gender-norm attitude 82 44.1 Social support 2.02 ± 0.61 Low levels of social support 168 90.3 High levels of social support 18 9.7 Perceived health status 1.52 ± 0.24 Least healthy 3 1.6 Healthy 183 98.4 Mothering self-efficacy 3.13 ± 0.47 Low self-efficacy 165 88.7 High self-efficacy 21 11.3 Perceived time stress 2.13 ± 0.81 Low levels of time stress 98 52.7 High levels of time stress 84 45.2 Maternal mental health status 8.54 ± 3.58 Low depressive symptoms 52 62.7 High depressive symptoms 31 37.3 Figure 1 shows knowledge of women of reproductive age on infant nutrition. A little above half (52.2%) of respondents had good knowledge of infant nutrition, while 47.8% had poor knowledge of infant nutrition during the first 1,000 days of life. Figure 2 shows attitude of women of reproductive age towards infant nutrition. Similarly, 54.3% respondents had positive attitudes, while 45.7% had negative attitudes toward infant nutrition during the first 1,000 days of life. Table 5 shows the influence of socioeconomic characteristics on maternal capabilities, knowledge and attitudes of women of reproductive age towards infant and young child feeding. Socioeconomic characteristics were significant predictor of maternal capabilities, and knowledge. The paper however, showed that among the socioeconomic characteristics studied, being unemployed was the strongest predictor (p < 0.05) of social support and mental health, and contributed 2.7% and 4.2%, respectively, variability in the social support and mental health status. Furthermore, unemployed respondents were 0.219 less likely to have social support than their employed counterparts, while unemployed respondents were 2.465 more likely to experience depressive symptoms than those employed. High income had a significant influence (p < 0.05) on self-efficacy, with 13.2% variability, which indicated that respondents with high income were 0.210 more likely to have high self-efficacy than those with low income status. Employment had a strong influence (p < 0.05) on knowledge, which contributed 4.8% variability in the knowledge status. This suggests that employed respondents were 0.027 more likely to have good knowledge of infant and young child nutrition than their unemployed counterparts. However, attitudes had a strong prediction (p < 0.05) on self-efficacy, with 78.1% variability. This suggests that respondents with negative attitudes towards infant nutrition were 4.801 more likely to have low self-efficacy than their counterparts with positive attitudes. Table 5 The influence of socioeconomic characteristics on maternal capabilities, knowledge and attitude of women of reproductive age on infant and young child feeding Variables Unstandardized Coefficients R square t Sig. B Std. Error (Constant) 2.028 0.123 16.538 0.000 Social support Unemployed -0.219 0.126 0.027 -2.148 0.033 (Constant) 9.653 1.101 8.771 0.000 Mental health Unemployed -2.465 0.915 0.042 -2.693 0.008 (Constant) 1.808 0.147 12.284 0.000 Self-efficacy Higher income level 0.210 0.104 0.132 2.026 0.040 (constant) 0.973 0.014 70.731 0.000 Knowledge Employed 0.027 0.011 0.048 2.317 0.022 (constant) 4.138 1.157 3.577 0.000 Self-efficacy Negative attitude -4.801 1.083 0.781 -4.431 0.003 DISCUSSION Maternal capabilities play a crucial role in shaping infant nutrition in the first 1000 days of life for ensuring improve nutritional and health outcomes among women and their children. This study examined that, and knowledge and attitudes regarding infant nutrition among women of reproductive age (WRA) in an area in Nigeria. A plurality (33.9%) of the WRA in our sample were in mid-adulthood, aged 30–35 years. The mid-adulthood is crucial for conception nutrition particularly related to nutrition practice in the first 1000 days of life. Most respondents who participated in this study were unmarried, which was surprising given their age range, indicating low prevalence of early marriage in the area. Similar outcome was reported by Okorie et al. [ 15 ]. Despite the respondents’ high education level, most were traders, unemployed or working in low-wage occupations. This is unsurprising given Abia State’s high unemployment rate of 31.6% [ 16 , 15 ]. While most respondents demonstrated good knowledge and positive attitudes towards infant nutrition, they faced challenges in decision-making autonomy, social support, self-efficacy, mental health (including depressive symptoms and stress), and restrictive gender norms. These low capabilities are likely to impair appropriate infant nutrition practices. This highlights the need for targeted interventions to empower women of reproductive age, ultimately improving nutrition practices during the critical first 1000 days of life. Unemployment was associated with both decreased social support and mental health. This presumably limits respondents’ capacity to follow global recommendations on infant nutrition. When women’s mental health is compromised, it adversely affects child nutrition, interfering with mother’s ability to care for her child. Also, lack of support from family or absence of social support systems may contribute to non-adherence to recommended infant nutrition during the first 1,000 days of life. This, in turn, could result in incorrect infant feeding, increasing the risk of infant malnutrition. This is consistent with the findings of Surkan et al. [ 17 ] and Okorie et al. [ 18 ], who investigated the influence of postpartum depression on childcare, inadequate breastfeeding, and poor complementary practices, all of which contribute to infant malnutrition. Furthermore, studies by Reddy et al. [ 19 ] and Balogun et al. [ 20 ] reported poor social systems as one of the identified barriers for continuing exclusive breastfeeding for 6 months. Knowledge about infant is essential for making informed feeding decisions during the first 1,000 days of a child’s life. This paper revealed that being employed positively influenced respondents’ knowledge of infant nutrition. This implies that respondents are likely to make informed food choices due to improved access to information, education, and workplace interactions about child health and nutrition. This outcome may ultimately lead to better nutrition in the first 1000 days of life. This finding is consistent with different studies in Bangladesh, Nepal, and Nigeria [ 21 , 22 , 23 ] on maternal employment and knowledge of infant nutrition. They further reported that employed mothers had higher levels of awareness on infant nutrition, contributing to a better nutrition outcomes for their children. In addition, higher income levels increased respondents’ self-efficacy. However, negative attitude towards infant nutrition was associated with lower self-efficacy among respondents, which may undermine their confidence in making appropriate nutrition decisions during the first 1000 days of life. Also, lack of supportive family and/or community network can negatively affect maternal confidence and reduce adherence to recommended nutrition practices in the first 1000 days of life. Another study found that counselling sessions improved infant nutrition by addressing gaps in maternal self-efficacy and social support [ 24 ]. In another study, women with positive attitudes were more likely to follow recommended nutrition practices [ 25 ]. Similarly, in rural Nigeria, women with positive attitudes were more proactive in adopting recommended infant nutrition compared to their counterparts with negative attitudes, who introduced water and other foods early to their children [ 26 ]. The analysis underscores that socioeconomic factors significantly impact maternal capabilities, which directly influence nutrition practices within the first 1,000 days of life. Employment and income status empower women of reproductive age with knowledge, self-efficacy, and social support, enabling them to adhere to optimal infant nutrition. Conversely, unemployment, low income and negative attitudes can restrict maternal capabilities such as mental health, leading to suboptimal infant nutrition. Previous studies have also reported lower socioeconomic conditions, poor social support and experiencing physical violence as contributing factors to high prevalence of maternal mental health in developing countries [ 27 , 28 ]. Therefore, a health promotion approach such as health literacy, quality nutrition services and context specific nutrition strategies and directives on maternal and child nutrition programs at multi-level is required [ 29 ]. LIMITATIONS The present study did not examine infant and young child feeding practices by the respondents and thus could not determine if they were practicing appropriate infant and young child feeding. The cross-sectional nature of the study prevented us from taking long-term effect of maternal capabilities on knowledge and attitudes about infant nutrition into account. CONCLUSION A substantial number of women of reproductive age (WRA) in this area were in their mid-adulthood, and more than half were single. These women exhibited lower maternal capabilities, such as decision-making autonomy, social support, self-efficacy, mental health (including depressive symptoms and stress), and restrictive gender norms. Some of the WRA were unemployed, and this was linked to lower social support and mental health. Employment was associated with good knowledge of infant nutrition. Higher income levels increased maternal self-efficacy, while negative attitudes about infant nutrition were linked to lower self-efficacy. More research is necessary to explore maternal capabilities and infant feeding practices in Nigeria. This will inform the development of targeted frameworks and interventions that enhance women’s abilities and promote better feeding practices, ultimately improving the health and wel-being of infants and young children. Declarations Ethical Consideration and Approval the study was carried out according to the declaration of Helsinki – ethical principles involving human subjects. More so, the process of data collection during the study involving human subjects was non-invasive, and the ethical approval to conduct the study was obtained from the Health and Research Ethics Committee (HREC), Federal Medical Centre (FMC) Umuahia, Abia State, Nigeria, with reference number (FMC/QEH/G.596/Vol.10/775). An approval letter was also obtained from the Heads of Communities to allow the researchers carry out the study in their communities, while oral consent was also obtained from the study participants themselves. Human Ethics and Consent to participate declaration Informed consent to participate was obtained from the women of reproductive age before the commencement of the study, and no biomedical, clinical and biometric data were collected. Clinical Trial Number Clinical trial number not applicable. Consent for publication Not Applicable. Conflicts of interest: There authors declare that they have no other potential conflicts of interest. Funding: There are no external funding for the study. Author Contribution Conceptualization (O.I); Methodology (O.I.; O.B); Validation (O.I.; O.B.; O.C.C); Formal Analysis (O.I); Investigation (O.I; O.B); Resources (O.I.; O.B; O.C.C), Data Curation (O.I; O.B; O.C.C); Writing – Original Draft Preparation (O.I); Writing – Review & Editing (O.I; O.B; O.C.C); Visualization (O.I); Supervision (O.I; O.B); Project Administration (O.I); Funding Acquisition (O.I; O.B; O.C.C). Acknowledgements: The authors wish to acknowledge the Department of Human Nutrition and Dietetics, Michael Okpara University of Agriculture, research assistants, and the typist. Data Availability Statement: Data that support the findings of this study are not openly available due to some sensitivity and are available from the corresponding author upon reason request. References Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, de Onis M, Uauy R. 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Infant and young child feeding practices among mothers of under 2 years children in rural areas of Kavrepalanchok District, Nepal: A community-based cross-sectional study. Int Breastfeed J. 2019;14(1):42. https://doi.org/10.1186/s13006-019-0234-7 . Haider R, Rasheed S, Alim MA. Barriers to and facilitators of exclusive breastfeeding in sub Saharan Africa: A systematic review. BMC Public Health. 2017;17:961. 10.1186/s12889-017-4855-3 . Senbanjo IO, Black RE, Brown KH, de Onis M, Ezzati M, Mathers C, Koplan JP. Maternal and child undernutrition: Global and regional exposures and health consequences. Lancet. 2014;384:427–51. https://doi.org/10.1016/S0140-6736(13)60937- . Fisher J, Cabral de Mello M, Patel V, Rahman A, Tran T, Holton S. Prevalence and determinants of common perinatal mental disorders in women in low- and lower-middle-income countries: a systematic review. Bull World Health Organ. 2012;90(2):g139–49. pmid:22423165. Nguyen PH, Saha KK, Ali D, Menon P, Manohar S, Mai LT. Maternal mental health is associated with child undernutrition and illness in Bangladesh, Vietnam and Ethiopia. Public Health Nutr. 2014;17(6):1318–27. pmid:23642497. Koirala DM, Dhital SR, Owens KCBB, Khadka V, H.R. and, Gyawali P. (2022). Successful health promotion, its challenges and the way forward in Nepal. Global Health Promotion . 2022;30(1):68–71. 10.1177/17579759221117792 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7313620","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":508690973,"identity":"41be6616-91fa-4c76-9199-b73858076bb9","order_by":0,"name":"Ijioma Okorie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYBACNoaDDUDKhoeNmfkAkCEhQ6yWNDl+9rYEkBYeYi07bCzZc8YAxCKshY/xcOOjGzXMiRtu5Hx+daPGgoeB/fDRDQQc1mycc4wNqCV3m3XOMaDDeNLSbhDQ0iadw8YD1mKcwwbUIsFjRoSWfxIghz0zBjKI1JLbZgDyPvPj3DbitDQb5/YlgALZjDm3T4KHjZBf5Gccf/g459t/UFQ+/pzzrQ6o9/AxvFoYJA4gbJSA2EsI8DfAmcwfCKoeBaNgFIyCEQkAN8lJPAQtTEEAAAAASUVORK5CYII=","orcid":"","institution":"Michael Okpara University of Agriculture Umudike","correspondingAuthor":true,"prefix":"","firstName":"Ijioma","middleName":"","lastName":"Okorie","suffix":""},{"id":508690974,"identity":"632753d7-2d5e-46a4-a634-7b0036348a68","order_by":1,"name":"Blessing Osegbo","email":"","orcid":"","institution":"Michael Okpara University of Agriculture Umudike","correspondingAuthor":false,"prefix":"","firstName":"Blessing","middleName":"","lastName":"Osegbo","suffix":""},{"id":508690975,"identity":"0aa375d6-a16d-4650-9f70-b4f020b7e26e","order_by":2,"name":"Chinyere Confidence Ojinika","email":"","orcid":"","institution":"Federal Ministry of Health","correspondingAuthor":false,"prefix":"","firstName":"Chinyere","middleName":"Confidence","lastName":"Ojinika","suffix":""}],"badges":[],"createdAt":"2025-08-07 01:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7313620/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7313620/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90470818,"identity":"51f0c15e-26e6-461b-aeda-68a4f436cefb","added_by":"auto","created_at":"2025-09-03 06:16:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":28853,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7313620/v1/be44c7ddff404eba7f795ecb.png"},{"id":90470821,"identity":"ff45197e-6413-48ef-b114-ac2c70a0e2b4","added_by":"auto","created_at":"2025-09-03 06:16:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27431,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7313620/v1/14f16843de482ffeb0f1935a.png"},{"id":93047784,"identity":"d974d6fc-7f75-4cae-af74-9f33f5c96a48","added_by":"auto","created_at":"2025-10-08 13:38:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1050317,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7313620/v1/802295ae-09eb-4b48-bdd1-1b80c617b37d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Knowledge and Attitude of Women of Reproductive Age (15–49 years) on Maternal Capabilities and Infant Nutrition in the First 1000 Days of Life in Umuahia South LocalGovernment Area, Abia State","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMaternal capabilities refer some of the attributes such as decision-making autonomy, gender-norm attitude, social support and self-efficacy, possessed by mothers to adequately care for themselves and their children. Maternal nutrition plays a key role in shaping the health outcomes of both the mother and the child. Malnutrition during pregnancy and early childhood can have long-term consequences on the physical and cognitive development of the child [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Establishing healthy eating habits in infants and toddlers is crucial for their overall growth, as well as social, emotional, and cognitive development [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Therefore, guidance on infant and toddler nutrition should encompass not only recommended foods but also strategies for creating an environment that fosters healthy eating habits. Infancy, which lasts from birth to two years, is particularly important because it establishes the foundation for long-term food choices, dietary patterns, and obesity risk [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The first 1000 days of life, from conception to age two, offer a critical window of opportunity to prevent the long-term effects of under-nutrition. Recognizing the importance of this period is crucial for improving child health and well-being globally. During fetal life and early childhood, the body undergoes rapid growth and development, making this a vital phase for establishing a strong foundation for lifelong health [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The global importance of maternal knowledge, attitudes, and child-feeding practices cannot be overstated. Breastfeeding is a critical component of infant health, and the timing of breastfeeding initiation can significantly impact neonatal outcomes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe World Health Organization (WHO) and United Nations Children\u0026rsquo;s Fund (UNICEF) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] launched a global initiative to promote best practices for infant feeding. The strategy aims to address suboptimal feeding practices among women of reproductive age by recommending that breastfeeding begin within the first hour of birth, be exclusive for the first six months of life, and introduce nutritious, safe, and age-appropriate complementary foods while breastfeeding for at least two years and beyond. This holistic strategy attempts to provide the optimum nutrition for infants\u0026rsquo; growth, development, and health. Despite global guidelines for healthy infant feeding, actual nutrition practices during the critical first 1,000 days of life are significantly shaped by a combination of factors. These include maternal knowledge and attitudes regarding infant nutrition, alongside maternal capabilities such as decision-making autonomy, self-efficacy, prevailing gender norms, social support, and mental health. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Empowering women of reproductive age through nutrition education and autonomous decision-making can significantly improve maternal and child health outcomes, ultimately promoting optimal growth and development [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo overcome this, informed policies and interventions are required to promote maternal capabilities, knowledge, and attitudes toward improved infant nutrition. This paper aims to assess knowledge and attitude of women of reproductive age (15\u0026ndash;49 years) on maternal capabilities and infant nutrition in the first 1000 days of fife in Umuahia South Local Government Area, Abia State.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design\u003c/h2\u003e\u003cp\u003e A community-based cross-sectional design was used to collect quantitative data on maternal capabilities, knowledge, and attitudes of women of reproductive age (WRA) (15\u0026ndash;49 years) on infant nutrition in Umuahia South Local Government Area.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy population and sample size\u003c/h3\u003e\n\u003cp\u003eThe study population was 186 WRA living in communities in Umuahia South Local Government of Abia State. Pregnant women, lactating mothers and other WRA who were sick at the time of the study were excluded.\u003c/p\u003e\u003cp\u003eThe sample size for the study was estimated using Cochran\u0026rsquo;s formula described by Araoye [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003en = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{Z}^{2}P\\:(100-P)}{e\u0026sup2;}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003emargin of tolerable sampling error applied was 5%\u003c/p\u003e\u003cp\u003e P\u0026thinsp;=\u0026thinsp;prevalence of attitudes on good nutrition WRA in rural Nigeria, 86.89% according to Fasola et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eN = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{1.96}^{2\\:}X\\:86.89(100-86.89)}{{5}^{2}}\\)\u003c/span\u003e\u003c/span\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{3.8416\\:X\\:\\:86.89\\left(13.11\\right)}{25}\\)\u003c/span\u003e\u003c/span\u003e =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:\\frac{3.8416x1139.1279}{25}\\)\u003c/span\u003e\u003c/span\u003e = 175.04 = 175.\u003c/p\u003e\u003cp\u003eTo calculate the attrition rate, 10% of the initial sample size of 175 was added. This calculation is as follows:\u003c/p\u003e\u003cp\u003e175 x 0.10\u0026thinsp;=\u0026thinsp;17.5\u003c/p\u003e\u003cp\u003eAdding this to the initial sample size:\u003c/p\u003e\u003cp\u003e175\u0026thinsp;+\u0026thinsp;17.5\u0026thinsp;=\u0026thinsp;192.5\u003c/p\u003e\u003cp\u003eRounding up to the nearest whole number:\u003c/p\u003e\u003cp\u003e192.5\u0026thinsp;\u0026asymp;\u0026thinsp;193.\u003c/p\u003e\u003cp\u003eTherefore, the adjusted sample size to account for attrition is 193.\u003c/p\u003e\u003cp\u003eDesign effect (Deff) was estimated to take care of design features. Thus, 193 x 1.1\u0026thinsp;=\u0026thinsp;212.3. Therefore, the adjusted sample size was approximately 212.\u003c/p\u003e\n\u003ch3\u003eSampling procedure\u003c/h3\u003e\n\u003cp\u003eThe study took place in Umuahia South LGA, employing a multi-stage cluster sampling method. To begin, the LGA was divided into semi-urban and rural areas to ensure representation was proportional. The sample size of 212 women was then allocated between these areas, with 60% from semi-urban areas and 40% from rural areas. In the next stage, six clusters were randomly chosen from a list of wards and communities. Three semi-urban clusters (Olokoro, Ubakala, and Umuahia semi-urban) and three rural clusters (Amuzu, Okporoenyi, and Nnono) were selected. Households within each cluster were then systematically sampled, with approximately 127 women chosen from semi-urban clusters and 85 from rural clusters. To ensure equal representation, a random starting point was chosen in each cluster, and every 5th household was selected. In households with multiple eligible women, simple random sampling by balloting without replacement was used to select one respondent. Ultimately, 212 women of reproductive age were recruited for the study.\u003c/p\u003e\n\u003ch3\u003eData collection tool\u003c/h3\u003e\n\u003cp\u003eA validated and pretested semi-structured questionnaire was used to collect quantitative data on background information, and socioeconomic characteristics of women of reproductive age. WHO/UNICEF [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] maternal, infant and young child nutrition construct was used to measure knowledge and attitudes of women of reproductive age towards infant and young child nutrition, while maternal capabilities construct developed by Stoltzfus et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] was adopted for the study.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eThe sample size was originally 212 but 12% of them drooped out. The achieved number of responses was thus 186. The respondents were interviewed using a semi-structured questionnaire to obtain background information. To assess knowledge and attitudes, the following methods were used: Knowledge Assessment: 7 questions were asked to evaluate knowledge. Correct answers were assigned 1 mark, while incorrect answers received 0 marks. The results were standardized to allow for a maximum score of 70% and a minimum score of 0%. Knowledge levels were categorized as follows: Good knowledge: 35\u0026ndash;70%. Poor knowledge: 0-34.99%. 6 questions were asked to evaluate attitudes, with responses coded on a 3-point Likert scale (agree, undecided, and don\u0026rsquo;t know). Correct answers were assigned 1 mark, while incorrect answers received 0 marks Attitude levels were categorized as follows: Positive attitudes: 30\u0026ndash;60%; Negative attitudes: 0-29.99%.\u003c/p\u003e\u003cp\u003eMaternal capabilities construct include; decision-making autonomy: A 5-question assessment was used, with responses coded as 0 (no) or 1 (yes). The score was calculated by summing the responses. Gender norm attitudes: A 6-question assessment was used, with responses rated on a 5-point Likert scale (1\u0026thinsp;=\u0026thinsp;restrictive, 5\u0026thinsp;=\u0026thinsp;egalitarian). The score was calculated by averaging the responses. Maternal depressive symptoms: A 10-question assessment was used, with responses rated on a 4-point Likert scale (0\u0026thinsp;=\u0026thinsp;lowest, 30\u0026thinsp;=\u0026thinsp;highest). The score was calculated by summing the responses. Mothering self-efficacy: A 6-question assessment was used, with responses rated on a 5-point Likert scale (1\u0026thinsp;=\u0026thinsp;low, 5\u0026thinsp;=\u0026thinsp;high). The score was calculated by averaging the responses. Perceived health status: An 11-question assessment was used, with responses recoded on a 0\u0026ndash;5 scale (0\u0026thinsp;=\u0026thinsp;least healthy, 5\u0026thinsp;=\u0026thinsp;most healthy). The score was calculated by averaging sub-scores, following the source instructions. Perceived social support: A 16-question assessment was used, with responses rated on a 5-point Likert scale (1\u0026thinsp;=\u0026thinsp;low, 5\u0026thinsp;=\u0026thinsp;high). The score was calculated by averaging the responses. Perceived time stress contained 5 questions with 5-point Likert scale, where 1\u0026thinsp;=\u0026thinsp;low levels of stress and 5\u0026thinsp;=\u0026thinsp;high levels of stress. Score calculated as means of 5 responses.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics, namely frequency and percentage, as well as mean and standard deviation were used for the background information/socioeconomic characteristics, knowledge, and attitudes towards infant nutrition, and maternal capabilities variables. Regression analysis was conducted to examine the influence of socioeconomic characteristics on maternal capabilities, knowledge of, and attitudes towards infant nutrition. A significant difference was declared at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The IBM-SPSS software version 27 was used for the analysis.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy variables\u003c/h3\u003e\n\u003cp\u003eThe independent variables in this paper are the socioeconomic data such as education, occupation and income. They were further categorized into, low education (respondents with no formal education, and with primary education) and high education (respondents with secondary and tertiary education); unemployed and employed; and low income levels (\u0026lt;\u0026thinsp;30,000 \u0026ndash; 50,000) and high income levels (above 50,000). While in this paper, dependent variables are the components of maternal capabilities, such as decision-making autonomy, gender norm attitude, social support, perceived health status, mothering self-efficacy, perceived time stress, and maternal mental health, knowledge and attitudes towards infant nutrition. Components of maternal capabilities, knowledge and attitudes were further categorized as shown in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, respectively. However, in this paper we also determined the influence of attitudes (as independent variable) on maternal capabilities (self-efficacy) (as the dependent variable).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCategorical variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCategorical variables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLevel\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDecision-making autonomy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLower decision-making autonomy\u003c/p\u003e\u003cp\u003eGreater decision-making autonomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.00\u0026ndash;3.00\u003c/p\u003e\u003cp\u003e3.10\u0026ndash;5.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender- norm attitude\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRestrictive gender-norm attitude\u003c/p\u003e\u003cp\u003eEgalitarian gender-norm attitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.00\u0026ndash;3.00\u003c/p\u003e\u003cp\u003e3.10\u0026ndash;6.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial support\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow levels of social support\u003c/p\u003e\u003cp\u003eHigh levels of social support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.00\u0026ndash;3.00\u003c/p\u003e\u003cp\u003e3.10\u0026ndash;5.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePerceived health status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeast healthy\u003c/p\u003e\u003cp\u003eHealthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.00\u0026ndash;3.00\u003c/p\u003e\u003cp\u003e3.10\u0026ndash;5.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMothering self-efficacy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow self-efficacy\u003c/p\u003e\u003cp\u003eHigh self-efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.00\u0026ndash;3.00\u003c/p\u003e\u003cp\u003e3.10\u0026ndash;5.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePerceived time stress\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow levels of time stress\u003c/p\u003e\u003cp\u003eHigh levels of time stress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.00\u0026ndash;3.00\u003c/p\u003e\u003cp\u003e3.10\u0026ndash;5.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMaternal mental health\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow depressive symptoms\u003c/p\u003e\u003cp\u003eHigh depressive symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.00\u0026ndash;9.99\u003c/p\u003e\u003cp\u003e\u0026ge;\u0026thinsp;10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eStoltzfus et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCategorical variables continued\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCategorical variables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLevel\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eKnowledge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoor knowledge\u003c/p\u003e\u003cp\u003eGood knowledge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u0026ndash;34.99%\u003c/p\u003e\u003cp\u003e35\u0026ndash;70%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAttitude\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative attitude\u003c/p\u003e\u003cp\u003ePositive attitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u0026ndash;29.99\u003c/p\u003e\u003cp\u003e30\u0026ndash;60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe authors developed the levels to meet the paper needs, as highlighted in the data collection section.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the background information and socioeconomic characteristics of the respondents (women of reproductive age). The respondents\u0026rsquo; age ranged from 15 to 35 years, with a mean age of 27.94 years. Some of the respondents were aged, 30\u0026ndash;35 years (33.9%), 25\u0026ndash;29 years (31.7%), and 20\u0026ndash;24 years (26.3%). It was found that 44.6% of the respondents were married, with 38.7% of them living with their spouses, while 55.4% were not married. In terms of education, 70.4% of the respondents had tertiary education, some had secondary education (14.5%), primary education (7.5%), while 7.5% no formal education. The respondents\u0026rsquo; occupations varied, with 23.7% unemployed, 24.7% engaged in business/trading, 16.7% artisans/skilled workers, 17.2% students, and 15.1% in civil/public service. Regarding income, 41.9% of the respondents earned less than 30,000 per month, while only 8.6% of the respondents earned 91,000 and above per month.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBackground information and socioeconomic characteristics of women of reproductive age\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency (n\u0026thinsp;=\u0026thinsp;186)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMean age\u003c/b\u003e (27.94\u0026thinsp;\u0026plusmn;\u0026thinsp;7.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge range\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u0026ndash;19 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u0026ndash;24 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;29 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u0026ndash;35 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot married\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e55.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiving with spouse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot living with spouse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLevel of education\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo primary education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTertiary education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e131\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e70.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBusiness/Trading\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCivil/Public servant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArtisan/Skill worker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers (sales girl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIncome level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt; 30,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30,000 \u0026ndash; 50,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e51,000 \u0026ndash; 70,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e71,000 \u0026ndash; 90,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e91,000 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows maternal capabilities (decision-making autonomy, gender-norm attitude, social support, perceived health, mothering self-efficacy, perceived time stress, and maternal mental health) of the respondents. A little above half (53.8%) of the respondents had lower decision-making autonomy, while 46.2% had greater decision-making autonomy. Also, 55.9% of the respondents held restrictive gender-norm attitudes, which suggests adherence to traditional gender roles, while 46.2% held egalitarian gender-norm attitudes, that is, a significant proportion held more progressive views. The respondents\u0026rsquo; social support levels varied, with 90.3% experienced low levels of social support, while only 9.7% had high levels of social support. Majority (98.4%) of the respondents perceived themselves as healthy, while 1.6% reported being in poor health (least healthy). The paper also showed that, 88.7% of respondents had low self-efficacy, while 11.3% had high self-efficacy. The paper found that 52.7% of the respondents reported low levels of time stress, while 45.2% reported high levels of time stress. For mental health status, 62.7% of respondents reported low depressive symptoms, while 37.3% reported high depressive symptoms.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMaternal capabilities of women of reproductive age\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaternal capabilities\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;186)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercentage\u003c/p\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean score\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDecision-making autonomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e3.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLower decision-making autonomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGreater decision-making autonomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender-norm attitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e3.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRestrictive gender-norm attitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e55.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEgalitarian gender-norm attitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow levels of social support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e90.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh levels of social support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived health status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeast healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e98.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMothering self-efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e3.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow self-efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e88.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh self-efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived time stress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow levels of time stress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh levels of time stress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaternal mental health status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e8.54\u0026thinsp;\u0026plusmn;\u0026thinsp;3.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow depressive symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh depressive symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows knowledge of women of reproductive age on infant nutrition. A little above half (52.2%) of respondents had good knowledge of infant nutrition, while 47.8% had poor knowledge of infant nutrition during the first 1,000 days of life.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows attitude of women of reproductive age towards infant nutrition. Similarly, 54.3% respondents had positive attitudes, while 45.7% had negative attitudes toward infant nutrition during the first 1,000 days of life.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the influence of socioeconomic characteristics on maternal capabilities, knowledge and attitudes of women of reproductive age towards infant and young child feeding. Socioeconomic characteristics were significant predictor of maternal capabilities, and knowledge. The paper however, showed that among the socioeconomic characteristics studied, being unemployed was the strongest predictor \u003cem\u003e(p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/em\u003e of social support and mental health, and contributed 2.7% and 4.2%, respectively, variability in the social support and mental health status. Furthermore, unemployed respondents were 0.219 less likely to have social support than their employed counterparts, while unemployed respondents were 2.465 more likely to experience depressive symptoms than those employed. High income had a significant influence \u003cem\u003e(p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/em\u003e on self-efficacy, with 13.2% variability, which indicated that respondents with high income were 0.210 more likely to have high self-efficacy than those with low income status.\u003c/p\u003e\u003cp\u003eEmployment had a strong influence \u003cem\u003e(p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/em\u003e on knowledge, which contributed 4.8% variability in the knowledge status. This suggests that employed respondents were 0.027 more likely to have good knowledge of infant and young child nutrition than their unemployed counterparts. However, attitudes had a strong prediction \u003cem\u003e(p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/em\u003e on self-efficacy, with 78.1% variability. This suggests that respondents with negative attitudes towards infant nutrition were 4.801 more likely to have low self-efficacy than their counterparts with positive attitudes.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe influence of socioeconomic characteristics on maternal capabilities, knowledge and attitude of women of reproductive age on infant and young child feeding\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eR square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSig.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(Constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e16.538\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial support\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.219\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-2.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(Constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.771\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMental health\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.465\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.915\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-2.693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(Constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.808\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12.284\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSelf-efficacy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigher income level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.973\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e70.731\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eKnowledge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.577\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSelf-efficacy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative attitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-4.801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.083\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.781\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-4.431\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eMaternal capabilities play a crucial role in shaping infant nutrition in the first 1000 days of life for ensuring improve nutritional and health outcomes among women and their children. This study examined that, and knowledge and attitudes regarding infant nutrition among women of reproductive age (WRA) in an area in Nigeria.\u003c/p\u003e\u003cp\u003eA plurality (33.9%) of the WRA in our sample were in mid-adulthood, aged 30\u0026ndash;35 years. The mid-adulthood is crucial for conception nutrition particularly related to nutrition practice in the first 1000 days of life. Most respondents who participated in this study were unmarried, which was surprising given their age range, indicating low prevalence of early marriage in the area. Similar outcome was reported by Okorie et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Despite the respondents\u0026rsquo; high education level, most were traders, unemployed or working in low-wage occupations. This is unsurprising given Abia State\u0026rsquo;s high unemployment rate of 31.6% [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile most respondents demonstrated good knowledge and positive attitudes towards infant nutrition, they faced challenges in decision-making autonomy, social support, self-efficacy, mental health (including depressive symptoms and stress), and restrictive gender norms. These low capabilities are likely to impair appropriate infant nutrition practices. This highlights the need for targeted interventions to empower women of reproductive age, ultimately improving nutrition practices during the critical first 1000 days of life.\u003c/p\u003e\u003cp\u003eUnemployment was associated with both decreased social support and mental health. This presumably limits respondents\u0026rsquo; capacity to follow global recommendations on infant nutrition. When women\u0026rsquo;s mental health is compromised, it adversely affects child nutrition, interfering with mother\u0026rsquo;s ability to care for her child. Also, lack of support from family or absence of social support systems may contribute to non-adherence to recommended infant nutrition during the first 1,000 days of life. This, in turn, could result in incorrect infant feeding, increasing the risk of infant malnutrition. This is consistent with the findings of Surkan et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and Okorie et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], who investigated the influence of postpartum depression on childcare, inadequate breastfeeding, and poor complementary practices, all of which contribute to infant malnutrition. Furthermore, studies by Reddy et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and Balogun et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] reported poor social systems as one of the identified barriers for continuing exclusive breastfeeding for 6 months.\u003c/p\u003e\u003cp\u003eKnowledge about infant is essential for making informed feeding decisions during the first 1,000 days of a child\u0026rsquo;s life. This paper revealed that being employed positively influenced respondents\u0026rsquo; knowledge of infant nutrition. This implies that respondents are likely to make informed food choices due to improved access to information, education, and workplace interactions about child health and nutrition. This outcome may ultimately lead to better nutrition in the first 1000 days of life. This finding is consistent with different studies in Bangladesh, Nepal, and Nigeria [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] on maternal employment and knowledge of infant nutrition. They further reported that employed mothers had higher levels of awareness on infant nutrition, contributing to a better nutrition outcomes for their children.\u003c/p\u003e\u003cp\u003eIn addition, higher income levels increased respondents\u0026rsquo; self-efficacy. However, negative attitude towards infant nutrition was associated with lower self-efficacy among respondents, which may undermine their confidence in making appropriate nutrition decisions during the first 1000 days of life. Also, lack of supportive family and/or community network can negatively affect maternal confidence and reduce adherence to recommended nutrition practices in the first 1000 days of life. Another study found that counselling sessions improved infant nutrition by addressing gaps in maternal self-efficacy and social support [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In another study, women with positive attitudes were more likely to follow recommended nutrition practices [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Similarly, in rural Nigeria, women with positive attitudes were more proactive in adopting recommended infant nutrition compared to their counterparts with negative attitudes, who introduced water and other foods early to their children [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe analysis underscores that socioeconomic factors significantly impact maternal capabilities, which directly influence nutrition practices within the first 1,000 days of life. Employment and income status empower women of reproductive age with knowledge, self-efficacy, and social support, enabling them to adhere to optimal infant nutrition. Conversely, unemployment, low income and negative attitudes can restrict maternal capabilities such as mental health, leading to suboptimal infant nutrition. Previous studies have also reported lower socioeconomic conditions, poor social support and experiencing physical violence as contributing factors to high prevalence of maternal mental health in developing countries [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Therefore, a health promotion approach such as health literacy, quality nutrition services and context specific nutrition strategies and directives on maternal and child nutrition programs at multi-level is required [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eLIMITATIONS\u003c/h2\u003e\u003cp\u003eThe present study did not examine infant and young child feeding practices by the respondents and thus could not determine if they were practicing appropriate infant and young child feeding. The cross-sectional nature of the study prevented us from taking long-term effect of maternal capabilities on knowledge and attitudes about infant nutrition into account.\u003c/p\u003e\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eA substantial number of women of reproductive age (WRA) in this area were in their mid-adulthood, and more than half were single. These women exhibited lower maternal capabilities, such as decision-making autonomy, social support, self-efficacy, mental health (including depressive symptoms and stress), and restrictive gender norms. Some of the WRA were unemployed, and this was linked to lower social support and mental health. Employment was associated with good knowledge of infant nutrition. Higher income levels increased maternal self-efficacy, while negative attitudes about infant nutrition were linked to lower self-efficacy. More research is necessary to explore maternal capabilities and infant feeding practices in Nigeria. This will inform the development of targeted frameworks and interventions that enhance women\u0026rsquo;s abilities and promote better feeding practices, ultimately improving the health and wel-being of infants and young children.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthical Consideration and Approval\u003c/h2\u003e\u003cp\u003e the study was carried out according to the declaration of Helsinki \u0026ndash; ethical principles involving human subjects. More so, the process of data collection during the study involving human subjects was non-invasive, and the ethical approval to conduct the study was obtained from the Health and Research Ethics Committee (HREC), Federal Medical Centre (FMC) Umuahia, Abia State, Nigeria, with reference number (FMC/QEH/G.596/Vol.10/775). An approval letter was also obtained from the Heads of Communities to allow the researchers carry out the study in their communities, while oral consent was also obtained from the study participants themselves.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eHuman Ethics and Consent to participate declaration\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eInformed consent to participate was obtained from the women of reproductive age before the commencement of the study, and no biomedical, clinical and biometric data were collected.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e\u003cp\u003eClinical trial number not applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003e\u003cb\u003eNot Applicable.\u003c/b\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConflicts of interest:\u003c/h2\u003e\u003cp\u003eThere authors declare that they have no other potential conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThere are no external funding for the study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization (O.I); Methodology (O.I.; O.B); Validation (O.I.; O.B.; O.C.C); Formal Analysis (O.I); Investigation (O.I; O.B); Resources (O.I.; O.B; O.C.C), Data Curation (O.I; O.B; O.C.C); Writing \u0026ndash; Original Draft Preparation (O.I); Writing \u0026ndash; Review \u0026amp; Editing (O.I; O.B; O.C.C); Visualization (O.I); Supervision (O.I; O.B); Project Administration (O.I); Funding Acquisition (O.I; O.B; O.C.C).\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\u003cp\u003eThe authors wish to acknowledge the Department of Human Nutrition and Dietetics, Michael Okpara University of Agriculture, research assistants, and the typist.\u003c/p\u003e\u003ch2\u003eData Availability Statement:\u003c/h2\u003e\u003cp\u003eData that support the findings of this study are not openly available due to some sensitivity and are available from the corresponding author upon reason request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBlack RE, Victora CG, Walker SP, Bhutta ZA, Christian P, de Onis M, Uauy R. 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Successful health promotion, its challenges and the way forward in Nepal. \u003cem\u003eGlobal Health Promotion\u003c/em\u003e. 2022;30(1):68\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/17579759221117792\u003c/span\u003e\u003cspan address=\"10.1177/17579759221117792\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"attitudes, infant nutrition, knowledge, maternal capabilities, women of reproductive age","lastPublishedDoi":"10.21203/rs.3.rs-7313620/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7313620/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMaternal capabilities refer to some of the attributes such as decision-making autonomy, gender-norm attitude, social support and self-efficacy, possessed by mothers to adequately care for themselves and their children. This paper aims assess the maternal capabilities, knowledge, and attitudes of women of reproductive age (WRA) regarding infant nutrition during the first 1000 days of life in Umuahia South Local Government Area (LGA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA community-based cross-sectional design was used to recruit 193 WRA from 6 communities in both semi-urban and rural areas of the LGA. A semi-structured questionnaire was used to obtain demographic and socioeconomic data, knowledge and attitudes of WRA on infant nutrition. Maternal capabilities survey tool was adopted for the study. Data were analysed using descriptive statistics (frequency, percentage, mean and standard deviation), and linear regression, while level of significance was set at p \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMore (53.8%) of the WRA had lower decision-making autonomy, 90.3% had lower levels of social support, and 88.7% had low self-efficacy. Also, 52.2% of WRA had good knowledge, while 54.3% had positive attitudes regarding infant nutrition. Unemployment had significant influence (\u003cem\u003ep \u0026lt; 0.05\u003c/em\u003e) on both social support and mental health. Higher income statistically influence (\u003cem\u003ep \u0026lt; 0.05\u003c/em\u003e) maternal self-efficacy, with 21% variability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMost of the respondents had lower levels of social support and self-efficacy. Unemployment was strongly linked to lower social support and mental health, while higher income levels increased self-efficacy.\u003c/p\u003e","manuscriptTitle":"Knowledge and Attitude of Women of Reproductive Age (15–49 years) on Maternal Capabilities and Infant Nutrition in the First 1000 Days of Life in Umuahia South LocalGovernment Area, Abia State","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 06:16:12","doi":"10.21203/rs.3.rs-7313620/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7aad45b0-b59b-4b02-bb02-7107a9bf1ec7","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-08T13:38:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-03 06:16:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7313620","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7313620","identity":"rs-7313620","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}