The Impact of Public Health and Social Determinants on Maternal Factors for Academic Nurturance and the Cognitive Development of Preschool Children: A Cross-sectional Research Study

The Impact of Public Health and Social Determinants on Maternal Factors for Academic Nurturance and the Cognitive Development of Preschool Children: A Cross-sectional Research Study | 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 The Impact of Public Health and Social Determinants on Maternal Factors for Academic Nurturance and the Cognitive Development of Preschool Children: A Cross-sectional Research Study Prakash Sharma, Niki Syrou, Ali Guma, Chitra Bahadur Budhathoki, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5760180/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: The importance of the impact of public health and social determinants on maternal factors for academic nurturing and the cognitive development of preschool children for family-based and institutional nutrition interventions reveals a concerning prevalence of suboptimal behaviours across all countries. Early intervention strategies to cultivate healthy habits, particularly in preschool and childcare settings, highlight the importance of addressing socioeconomic barriers that prevent families from adopting health-promoting behaviours. Methods: Creating engaging learning experiences, providing emotional warmth, and fostering social interactions are essential for nurturing children's cognitive development. This study explored the factors influencing cognitive development in 389 preschool children (aged 3-5) in Rupandehi District, Nepal. A cross-sectional survey design employing multistage random sampling was used to collect socioeconomic and demographic data, alongside caregivers' academic nurturance practices, through validated instruments and interviews. Data analysis was conducted via IBM SPSS version 26, with significance set at p<0.05. Results: Forty-eight percent of thefamilies were economically disadvantaged, and only 15.5% of the caregivers exhibited high levels of academic nurturance. While academic nurturance itself did not have a direct effect on cognitive development, the unadjusted analysis revealedpositive associations between cognitive development and wealth status, maternal education, family structure, caste/ethnicity and the age of children. Multivariate analysis confirmed that family type, caste/ethnicity and the age of the childwere key factors in predicting cognitive development. The economic status predictor of cognitive development (β = -0.254, p = 0.000), negative association with lower economic status, and poorer cognitive development academic nurturance were added as predictors (β = -0.003, p = 0.954), accounting for 8.0% of the variance in cognitive development (R² = 8.0%), with an F-statistic of 4.667 (p = 0.000). Conclusion: Addressing these socioeconomic determinants could lead to significant improvements in children's cognitive outcomes. Finally, the study emphasizes the complex link between maternal characteristics, social determinants, and treatments in determining preschool children's caring and cognitive development. The findings highlight the need for targeted public health interventions that address these interconnected elements, emphasizing the importance of fostering social determinants and public health principles in increasing maternal involvement, and reducing socioeconomic barriers to optimal child development. Cognitive development Academic nurturance Preschool children Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Public health is concerned with the social conditions and determinants of sickness, as well as how society defines and addresses such conditions. Maternal health is a significant factor in the cognitive development of a preschool child[ 1 ]. Preschool children's cognitive development influences their preparation to begin school, and the quality of public education influences state and national social and economic issues[ 2 ], as well as public health. The emerging medical health literature considers maternal health in the context of public health[ 3 ]. The physical and emotional health of mothers, which has an impact on a fragile and dependent child, is of public importance. Research has demonstrated that early disadvantages frequently lead to childhood disease and developmental issues[ 4 ]. A young child who is ill or inadequately nurtured is frequently fussy, angry, and weeping, and many people struggle with childrearing [ 5 ]. For child-rearing to be most community-optimal, the child requires developmental-stage-appropriate care[ 6 ]. An increasingly rigorous empirical literature has demonstrated that maternal behaviors can be harmful to child development[ 7 ]. Future avenues of inquiry will help inform society, policy, and services about what influences a mother and whether there are additional reasons for extra community assistance [ 8 ], as well as public health and maternal factors of concern [ 9 ]. Public health research seeks to identify elements within the social ecology model that can enhance people's lives; nevertheless, the effects of public health and social determinants on mothers are frequently researched separately from the children they bring into the world and raise [ 10 ]. The conceptual framework is crucial for understanding how women's socioecological context influences preconception, pregnancy, and nursing, as well as health outcomes [ 11 ]. Public health has a major impact on maternal characteristics connected to nurturance and, as a result, the cognitive development of preschool children, with implications for policies and programs aimed at improving early children's health[ 12 ]. The majority of research in this area has been undertaken by scholars, with the goal of comparing women's health behaviours, health state, and access to care, as well as health status and care utilization among low-income mothers [ 13 ]. There is a need to do more to promote mothers' health, and this strategy should prioritize community-based services and family support [ 14 ]. Early childhood is a critical period for cognitive development, laying the foundation for lifelong learning and well-being[ 15 ]. Research indicates that the quality of academic nurturance provided during this stage significantly influences children's cognitive, social, and emotional growth. Academic nurturance, encompassing the emotional, instructional, and material support provided to young learners, plays a vital role in shaping their cognitive abilities, problem-solving skills, and readiness for formal education [ 16 ]. In the context of Nepal, particularly in the Rupandehi District, the role of academic nurturance in preschool settings has garnered increasing attention. As the country progresses toward enhancing early childhood education, understanding the interplay between nurturing environments and cognitive development becomes imperative. Despite national efforts to expand early childhood education programs, disparities in access, quality of instruction, and caregiver involvement persist, potentially affecting children's developmental outcomes. Rupandehi District, known for its diverse population and socioeconomic variability, presents a unique setting for exploring how academic nurturance impacts preschool children's cognitive development. Many children in the district experience varying levels of educational stimulation, which may be correlated with factors such as parental education, teacher training, and the availability of learning resources. This study aims to investigate the relationship between academic nurturance and the cognitive development of preschool children in Rupandehi District. By identifying key factors that contribute to or hinder cognitive growth, this research seeks to provide insights for educators, policymakers, and caregivers to foster enriched learning environments for early childhood development. The purpose of this study was to investigate the intricate interactions among public health variables, socioeconomic determinants, and maternal nurturance to better understand their involvement in cognitive development impairment in infants. The study is expected to produce empirical findings that will be useful to policymakers and public health professionals working in early childhood mental development, programs for women's health, and maternal care at local county health departments. Methods Study Design and Setting The study utilized a cross-sectional descriptive survey design, targeting primary caregivers of preschool-aged children as participants. Data collection was conducted between February 4th and April 12th, 2021, across Rupandehi District, Nepal, from 14,358 children in government-operated early childhood development (ECD) centres, reflecting a rich tapestry of ethnic, cultural, and socioeconomic diversity[15,16]. The sample size was calculated via Yamane's formula[17]. n= N / [1+N (e 2 )] where ‘n’ represents the sample population, N= total population and ‘e’ = 5% allowable error. This calculation yielded a sample of 389 children. The sampling process followed a multistage approach to ensure representativeness and rigor. Initially, three local administrative units were randomly selected from distinct strata, encompassing a sub metropolitan city, a municipality, and a rural municipality, to capture diverse geographic and socioeconomic contexts. In the subsequent phase, comprehensive records of schools and Early Childhood Development (ECD) centers were obtained from the selected local units. A simple random sampling method (lottery technique) was subsequently applied to draw five ECD centers from each local unit. In the final stage, the Population Proportionate Sampling (PPS) technique was utilized to allocate participants, resulting in a sample of 389 primary caregivers of preschool-aged children. If a primary caregiver was unavailable or unable to provide necessary information, a close family member was consulted as an alternative respondent. The study exclusively included caregivers who accompanied their preschool children to the respective ECD centres or schools during the data collection period. Participants who were unwilling to respond or provide data were excluded, along with ECD centres and schools that participated in pretesting the research instruments to minimize bias in the final analysis[18]. Data collection Data collection was conducted via a self-administered questionnaire with two sections. Section A assessed caregivers' academic nurturance practices, focusing on behaviors that contribute to emotional and cognitive development. The questionnaire included a series of questions to evaluate the extent of caregivers' involvement in stimulating their children's learning. For example, caregivers were asked how often they or someone else read stories to their child in a week, with response options ranging from 2–5 times to 0–1 times. Caregivers were also asked whether they asked questions about the stories they read to their child and how many children’s books the child owned, with responses indicating 2 or more books or none. Additional questions addressed whether caregivers or others taught their child about numbers, the alphabet, colours, and shapes and sizes. Furthermore, caregivers were asked if they discussed TV or YouTube programs with their child while watching and how often a family member took the child outings, with options ranging from 2-5 times per month to none. Finally, caregivers were asked how often a family member took the child to a museum in a year, with responses indicating 2–5 times or none [19]. Each question was scored as 1 for a "yes" answer and 0 for a "no" answer [20]. This structured tool provides a detailed assessment of caregivers' involvement in cognitive stimulation, aiming to understand their role in fostering academic nurturance. In addition, Section A included socioeconomic variables such as the child's gender and age, family structure, caste/ethnicity, maternal education level and family economic standing, recognizing these factors as potential determinants of cognitive and academic development. Economic status was measured via a tool from the 2016 Nepal Demographic and Health Survey (NDHS), which evaluated household assets and living conditions [21]. Wealth scores were then classified into quartiles—poorest, poor, rich, and richest—on the basis of specific score ranges[22]. These socioeconomic factors were included to account for their possible influence on the developmental outcomes of the children in the study. Section B measured cognitive development via a standardized tool developed at the National Psychological Corporation of India, grounded in Piaget’s theory of developmental psychology[23]. This instrument, designed for assessing children aged 3 to 5 years in the preoperational stage, converts raw scores into age-specific standard scores and includes tasks focused on symbolic play and basic problem-solving skills. To ensure the tool's clarity, relevance, and cultural suitability, a pilot test was conducted with 10% of the sample, leading to minor revisions on the basis of participant feedback to improve contextual accuracy. The reliability of the cognitive development tool was confirmed, with a Cronbach’s alpha of 0.90, whereas the academic nurturing tool had an alpha of 0.80. Data Analysis The data were meticulously entered into Microsoft Excel and analysed via IBM SPSS version 26 to ensure robust statistical examination. Descriptive statistics were calculated for both continuous and categorical variables, including means and standard deviations for the former and frequencies for the latter. To facilitate group comparisons, independent sample t tests and ANOVA were employed, with a threshold of p < 0.05 set for statistical significance. The normality of the data distribution and thorough screening for outliers were performed, leading to a refined dataset of 389 valid cases. To identify key factors influencing cognitive development, multiple linear regression analysis was conducted. This analysis controlled for potential confounding variables to isolate significant predictors, providing a more accurate understanding of the relationships between variables. Additionally, the use of rigorous statistical techniques ensured the reliability and validity of the results, offering a comprehensive exploration of the determinants of cognitive development in the study population. Figure 1 shows the normal Q‒Q plot diagram of the total cognitive score values of the study's. Results Demographic characteristics The study sample included N=389 children, with 50.6% male and 49.4% female participants. The age distribution revealed that 8.7% were three years old, whereas the majority were four (45.8%) or five years old (45.5%). Most families (72%) had two or fewer children. In terms of family structure, 52.4% lived in joint families, whereas 47.6% were part of nuclear households. Caste and ethnicity data indicated that 13.1% of the respondents were from the Dalit community, whereas 35.2% were from the advantageous caste. Educational background revealed that 23.4% of mothers were illiterate, whereas 8% had attained higher education. With respect to economic status, 24.7% of the respondents were categorized as the poorest, and 20.8% were categorized as the richest (Tables 1 & 2). Determinants of academic nurturance Table 1 illustrates the analysis of academic nurturance scores across various demographic variables. The findings highlight significant variations in mean nurturance scores based on critical factors. Notably, the number of children in the family (p=0.0001), caste (p=0.0001), mothers' education level (p=0.0001), and wealth status (p=0.0001) were strongly associated with differences in nurturance outcomes. Children from families with two or fewer children presented higher nurturance scores (M=5.28, SD=2.15) than did those from larger families (M=4.01, SD=2.36). Similarly, children from the advantageous caste had significantly greater nurturance (M=6.00, SD=2.05) than did Dalit children (M=3.88, SD=1.99). Maternal education showed a progressive increase in scores, with children of mothers with higher education achieving the highest nurturance (M=7.41, SD=1.76) compared with those whose mothers were illiterate (M=3.63, SD=2.21). Wealth status also demonstrated a positive trend, where children from the richest families had the highest nurturance scores (M=6.27, SD=1.66) compared with children from the poorest households (M=3.08, SD=2.08). However, no significant differences were observed in nurturance scores based on gender (p=0.819), age (p=0.623), or family structure (p=0.383). Table 1 Analysis of Academic Nurturance across Demographic Variables (Ν=389) Variables Category N % Mean SD 95% CI P value Gender of children Male Female 197 192 50.6 49.4 4.95 4.90 2.16 2.41 -0.40/0.50 -0.40/0.51 .819 Age of children Three years Four years Five years 34 178 177 8.7 45.8 45.5 5.11 4.80 5.01 2.19 2.37 2.21 4.35/5.88 4.45/5.16 4.68/5.34 .623 Number of children Two or less More than two 280 109 72 28 5.28 4.01 2.15 2.36 0.77/1.77 1.12/2.98 .0001*** Types of family Nuclear Joint 185 204 47.6 52.4 4.82 5.02 2.18 2.37 -.65/0.25 -.65/0.25 .383 Castes Dalit Janajati Non-Dalit Tarai Advantageous caste 51 110 91 137 13.1 28.3 23.4 35.2 3.88 4.80 4.03 6.00 1.99 1.85 2.55 2.05 3.32/4.44 4.45/5.15 3.50/4.56 5.65/6.35 .0001*** Mothers’ education Illiterate Basic level Secondary Higher Education 91 175 87 31 23.4 45 22.4 8 3.63 4.70 5.93 7.41 2.21 1.94 1.92 1.76 3.17/4.09 4.41/4.99 5.52/6.34 6.77/8.06 .0001*** Wealth status Poorest Poor Rich Richest 96 99 113 81 24.7 25.4 29 20.8 3.08 4.61 5.80 6.27 2.08 1.92 2.03 1.66 2.66/3.50 4.23/5.00 5.42/6.18 5.90/6.64 .0001*** Total 389 100 Note: *p<0.05, **p<0.01, ***p<0.0001, p - value calculated via t tests and one-way ANOVA. Determinants of cognitive development Table 2 presents the analysis of the cognitive development scores across various demographic variables. There was no statistically significant difference in cognitive development between male (M=101.74, SD=15.35) and female children (M=102.21, SD=15.52), with a p value of 0.766. This suggests that gender does not play a significant role in determining cognitive development within the sample population. Age was significantly associated with cognitive development (p=0.016). Children aged three years had the highest mean cognitive scores (M=108.94, SD=21.60), followed by four-year-olds (M=101.92, SD=12.93) and five-year-olds (M=100.68, SD=16.05). The number of children in the family did not significantly impact cognitive development (p=0.278). Children from families with two or fewer children had slightly higher scores (M=102.50, SD=15.36) than those from larger families did (M=100.61, SD=15.57), but the difference was not statistically significant. A significant difference in cognitive development was observed between children from nuclear and joint families (p=0.013). Children from nuclear families presented higher cognitive scores (M=104.00, SD=14.33) than did those from joint families (M=100.13, SD=16.16). Caste/ethnicity was highly significantly associated with cognitive development (p=0.0001). Children from advantageous castes had the highest cognitive scores (M=107.68, SD=14.57), whereas Dalit children recorded the lowest mean scores (M=99.49, SD=15.13). Janajati and non-Dalit Tarai caste children had intermediate scores (M=98.41, SD=14.72 and M=99.07, SD=15.42, respectively). Maternal education was significantly associated with cognitive development (p=0.002). Children of mothers with higher education levels achieved the highest cognitive scores (M=109.12, SD=16.19), whereas children whose mothers were illiterate recorded the lowest scores (M=99.79, SD=13.68). Wealth status had a significant effect on cognitive development (p=0.038). Children from the richest families had higher cognitive scores (M=103.35, SD=17.75) than those from the poorest households did (M=99.63, SD=14.12). Table 2. Analysis of Cognitive Development across Demographic Variables (N=389) Variables Category N % Mean SD 95% CI P value Gender of children Male Female 197 192 50.6 49.4 101.74 102.21 15.35 15.52 -3.54/2.61 -3.54/2.61 .766 Age of children Three years Four years Five years 34 178 177 8.7 45.8 45.5 108.94 101.92 100.68 21.60 12.93 16.05 101.40/116.47 100.01/103.8498.30/103.07 .016 * Number of children Two or less More than two 280 109 72 28 102.50 100.61 15.36 15.57 -1.53/5.31 -1.56/5.34 .278 Types of family Nuclear Joint 185 204 47.6 52.4 104.00 100.13 14.33 16.16 0.80/6.92 0.82/6.90 .013 * Castes Dalit Janajati Non-Dalit Tarai caste Advantageous caste 51 110 91 137 13.1 28.3 23.4 35.2 99.49 98.41 99.07 107.68 15.13 14.72 15.42 14.57 95.23/103.74 95.63/101.20 95.86/102.28 105.22/110.14 .0001*** Mothers’ education Illiterate Basic level Secondary Higher Education 91 175 87 31 23.4 45 22.4 8 99.79 100.38 105.21 109.12 13.68 15.94 14.73 16.19 96.94/102.64 98.00/102.76 102.07/108.35103.18/115.06 .002** Wealth status Poorest Poor Rich Richest 96 99 113 81 24.7 25.4 29 20.8 99.63 99.90 104.78 103.35 14.12 14.67 14.95 17.75 96.77/102.49 96.98/102.83 102.00/107.5799.43/107.28 .038* Total 389 100 The Dalit caste holds the lowest social status, often associated with untouchability. Janajati and non-Dalit Tarai castes rank above Dalits but below advantaged castes in the social hierarchy in Nepal [24].The Figure 2 shows the Diagram of Detrended Normal Q-QPlot of cognitive total score. Multiple Regression Analysis: Predictors of Cognitive Development Table 3 presents the results of multiple regression models that examine the relationships between various predictors and cognitive development. The analysis is split into two models: Model 1 assesses the impact of socioeconomic factors on cognitive development, whereas Model 2 incorporates both socioeconomic factors and academic nurturance. In Model 1 , economic status is a significant predictor of cognitive development (β = -0.254, p = 0.000), with a negative association indicating that lower economic status is linked to poorer cognitive development. Conversely, advantageous caste was also a significant predictor, with a negative coefficient (β = -0.147, p = 0.004), suggesting that children from advantageous caste backgrounds had lower cognitive development scores. The number of children in the family and mothers’ illiteracy did not significantly affect cognitive development (p > 0.05). The model explains 8.2% of the variance in cognitive development (R² = 8.2%), with an F statistic of 5.608 (p = 0.000). In Model 2 , when academic nurturance was added as a predictor, it did not have a significant effect (β = -0.003, p = 0.954). However, family structure was a significant predictor, as children from joint families presented significantly lower cognitive development scores (β = -0.148, p = 0.004). The age of the child also had a marginally significant negative effect (β = -0.107, p = 0.035), suggesting that older children may experience different developmental trajectories. Advantageous caste, which was significant in Model 1, remained a significant predictor of cognitive development in this model (β = 0.195, p = 0.000). The model explains 8.0% of the variance in cognitive development (R² = 8.0%), with an F statistic of 4.667 (p = 0.000). The Figure 3 shows the Histogram of the study's the correlations of frequency and cognitive total score. Table 3. Multiple regression model independent variables predicting cognitive Predictors Standardized Coefficients β (95%CI) Model 1 p value Standardize Coefficients β (95%CI) Model 2 p value Economic status -0.254 (-1.001/-0.394) .0001 *** 0.108 (-0.099/ 4.093) 0.062 Joint family 0.034 (-0.297/0.609) 0.500 -0.148 (-7.591/-1.493) 0.004 ** Mother's illiteracy 0.003 (-0.579/0.615) 0.953 0.008 (-3.739/4.294) 0.892 Advantageous caste -0.147(-1.145 /-0.222) .0001 *** 0.195 (2.935/9.218) .0001 *** Number of children 0.016 (-0.456/0.619) 0.766 0.042 (-2.187/5.048) 0.437 Age of child 0.048 (-0.182/0.524) 0.342 -0.107 (-4.935/-0.181) .035 * Academic nurturance -0.003 (-0.701/0.661) 0.954 R Square 8.2% 8.0% Std. Error 2.21 14.897 F (P value) 5.608 0.0001 *** 4.667 0.0001 *** Note: *p<0.05, **p<0.01, ***p<0.0001 . Model-I: Academic nurturance score adjusted for socioeconomic factors Model - II: Cognitive development score adjusted for socioeconomic factors and the academic nurturance index, the Table 4 shows the Cognitive total score of the quintiles confidence interval means. Table 4. Cognitive total score of the quintiles confidence interval means. Descriptives Cognitive_total_score N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum Lower Bound Upper Bound 4th quintile 96 99.6354 14.12062 1.44118 96.7743 102.4965 64.00 141.00 3rd quintile 99 99.9091 14.67824 1.47522 96.9816 102.8366 67.00 138.00 2nd quintile 113 104.7876 14.95437 1.40679 102.0002 107.5750 72.00 138.00 1st quintile 81 103.3580 17.75479 1.97275 99.4321 107.2839 62.00 138.00 Total 389 101.9769 15.42514 .78209 100.4392 103.5145 62.00 141.00 The Figure 5 shows the classifications of Mothers education mean values of cognitive stimulations scores. Discussion and findings of the research Public health focuses on lifespan, highlighting the importance of mothers’ health in preschool-aged children's well-being[25]. Healthcare disparities between affluent and underprivileged women, influenced by cultural practices and beliefs, persist[26]. Women from diverse backgrounds, including African American women, face barriers to timely prenatal care[27,28]. Despite public health initiatives improving access, disadvantaged sociodemographic groups still lack access to these services[29,30]. The findings from Tables shows that children from families with two or fewer children had significantly higher nurturance scores than those from larger families. Compared with Dalit children, children from the advantageous caste had higher nurturance scores. Maternal education level showed a progressive increase in academic nurturance scores. Wealth status also had a significant effect, with children from the richest families having the highest nurturance scores, which is supported by the global literature. During the early years of life, children's brain volume expands, affecting their cognitive and language skills[31]. Early interactions with mothers and exposure to richer language, particularly nonverbal vocabulary, contribute to cognitive development[32]. Even slight variations in maternal care can significantly impact cognitive growth until adolescence, and interactions with mothers are particularly significant[33]. The richer mental states significantly correlate with enhanced cognitive growth in children, especially regarding their nonverbal vocabulary related to understanding a wide range of emotions[34]. The findings from Tables of the study show that age was significantly associated with cognitive development. Three-year-old children presented the highest cognitive scores, whereas five-year-olds presented slightly lower scores. This suggests that cognitive advantages may diminish slightly with age in the sample. Children from nuclear families achieved higher cognitive scores than those from joint families did. Significant differences in cognitive development were evident across caste groups. Children from advantageous castes recorded the highest cognitive scores, whereas Dalit children scored lowest. Maternal education levels were significantly associated with cognitive development. Compared with children of illiterate mothers, children of mothers with higher education levels had superior cognitive outcomes. Economic status influences cognitive development. Children from the wealthiest families presented higher cognitive scores than those from the poorest families did, which is in line with the findings of the global literature. Public health interventions have a restricted effect on the factors that contribute to maternal nurturing, among the various social determinants, only maternal mental health was identified as having a significant influence on positive outcomes, which is highlighted in the key findings from the regression analyses[33,35]. The discussion centers on how sociodemographic factors can either positively or negatively affect aspects of maternal nurturance, as well as maternal cognitive development[36]. This is accompanied by tables that summarize the significant determinants identified through different analytical models (1 and 2). Additionally, the results section includes an examination of other factors affecting maternal cognitive development. The findings from the multiple regression analysis (Table 3) and Model 1 show that the analysis of socioeconomic factors as predictors of academic nurturance revealed that economic status was a significant negative predictor, with lower economic status being linked to poorer academic nurturance. Additionally, caste was significant, with children from disadvantageous caste backgrounds having lower academic nurturance scores. The findings from Model 2 concerning family structure became a significant predictor, with children from joint families exhibiting lower cognitive development scores. Age had a marginally significant negative impact, indicating that as children grew older, their cognitive development slightly decreased. This could be attributed to the tendency for caregivers to provide less nurturing as children grow older, often redirecting attention and resources toward younger siblings. Additionally, older children may assume more care for younger family members, which could reduce the time and energy available for their own cognitive development[23]. Advantageous caste remains a significant predictor of cognitive development. The findings from Model Explanation are that the models explained 8.2% (Model 1) and 8.0% (Model 2) of the variance in cognitive development, with both models having significant F-statistics (p=0.000), the above supported with the global literature. One of the critical insights from the literature is the notion that socioeconomic status significantly influences dietary behaviours and health outcomes. Families with lower socioeconomic status face greater challenges in adopting health-promoting behaviours, which can lead to a higher incidence of chronic no communicable diseases among their children[38]. This connection emphasizes the need for targeted interventions that not only promote healthy eating but also address the socioeconomic barriers that hinder access to nurturance [39]. The critical role of maternal involvement in child development frames it within the broader context of social determinants such as socioeconomic status and mental health[40]. Effective maternal‒child communication is identified as essential for optimal developmental outcomes, with a lack of engagement leading to delays in cognitive and emotional growth[41]. The impact of public health inequities that manifest early in life points to factors and social deprivation that adversely affect both maternal well-being and child development [42]. Additionally, the implications of maternal mental health for child development are addressed, emphasizing that maternal anxiety and depression can severely hinder a mother’s ability to provide adequate care, thereby compromising the child's developmental trajectory[43]. Ultimately, a crucial aspect of the impact of public health and social determinants on maternal factors for academic nurturance and ethical considerations involves addressing the cognitive development of preschool children, preventing burnout syndrome, increasing job satisfaction[44,45], and reducing occupational stress, particularly in the context of the COVID-19 pandemic, [46,47] and the ongoing climate crisis in teaching staff and caregivers[48,49]. Effective training, education, and competent management of healthcare and public health services are essential[50,51] for ensuring the quality of hospital care and public health initiatives, which are supported by strategic policy interventions[52-55]. Implications for practice This study contributes to the field of maternal and child health by informing both clinical and public health practices throughout the life course and highlighting the connection between maternal nurturance and cognitive development in preschool children. The results will pave the way for future longitudinal studies, necessitating a more thorough exploration and refinement of the elements in the proposed model. The findings will also guide future research directions and inform program development and implementation. This study underscores the crucial role of interventions to enhance maternal health and well-being, fostering more nurturing environments. First, increasing and diversifying resources for public health interventions, along with providing financial support for women experiencing high levels of stress or potential abuse, could significantly improve nurturing conditions. Furthermore, offering educational tools and expanding support services, parenting workshops, and access to family support professionals could benefit mothers. However, for these classes or professionals to make meaningful differences, they must be designed to effectively reduce stress and promote positive interactions between parents and children. Simply offering information without practical resources will not lead to immediate changes. Additionally, this research highlights the necessity of addressing social determinants. The findings suggest that policymakers should consider funding initiatives that explore the broader impact of social determinants on maternal health. Limitations of the study This study acknowledges its limitations while highlighting potential applications for database improvements. The current datasets provide a foundation for further exploration of this topic. By thoroughly analysing the initial research outcomes, the understanding of maternal and child health, public health, and the social determinants of health can be enriched. The main conclusions of this research support this hypothesis, which suggests that areas with social disarray tend to have a greater number of mothers exhibiting negative maternal characteristics acquired from domestic environments. Conclusion The findings of this research highlight the significant role that family size, caste, maternal education, and wealth status play in shaping academic nurturance. Children from smaller families, advantageous castes, and wealthier backgrounds consistently demonstrated higher levels of academic nurturance and cognitive development. Although academic nurturance itself does not have a direct effect on cognitive development, this study reveals that socioeconomic factors, particularly ethnicity, family structure and the age of children, are crucial predictors of children's cognitive outcomes. These results emphasize the need for targeted interventions to address disparities in educational access and outcomes. The study advocates for policies that focus on improving parental education, reducing economic inequalities, and creating inclusive learning environments to foster equitable academic and cognitive growth for all children. Declarations Acknowledgements We would like to extend our heartfelt gratitude to all the individuals who actively participated in this study. Additionally, we would like to express our appreciation to the Editors, and reviewers for their valuable feedback and insightful suggestions for improving this article. Authors' contributions: Conceptualization and writing of the first draft edited and reviewed the manuscript. PS and IA, Principal Investigators PS and IA, designed the research question and analytical approach from PS, IA, NS and AG. PS and IA conducted all analyses and wrote the final version of the manuscript with contributions from PS, IA, AG and NS. Supervision IA, Project Administration IA and PS. All the authors reviewed, edited, and approved the final manuscript. Funding The study received no grants or funding from any source. Availability of data and materials: Due to privacy restrictions, the data presented in this study are available upon request from the corresponding authors upon reasonable request. Declarations The authors declare no conflicts of interest. Ethical approval and consent to participate Ethical approval for the study was secured from the Board of Ethical Review at the Nepal Health Research Council (NHRC: No. 2078-56/2021), following prior authorization from the Office of the Dean, Faculty of Education, Tribhuvan University. Additionally, all previous research and scholarly contributions relevant to the study were appropriately acknowledged, and their works were thoroughly cited throughout the research. Consent for publication The authors give consent for publication. Competing interests The authors declare that they have no competing interests. References Ekholuenetale M, Barrow A, Ekholuenetale CE, Tudeme G. Impact of stunting on early childhood cognitive development in Benin: evidence from Demographic and Health Survey. Egyptian Pediatric Association Gazette. 2020 Dec;68:1-1. Chaparro J, Sojourner A, Wiswall MJ. Early childhood care and cognitive development. 2020. Kumar M, Huang KY. Impact of being an adolescent mother on subsequent maternal health, parenting, and child development in Kenyan low-income and high adversity informal settlement, PloS one. 2021. Wreyford N, Newsinger J, Kennedy H, Aust R. Locked down and locked out: mothers and UKTV work during the COVID-19 pandemic. Feminist Media Studies. 2024 Nov 16;24(8):1894-913. Webb N, Moloney LJ, Smyth BM, Murphy RL. Allegations of child sexual abuse: An empirical analysis of published judgements from the Family Court of Australia 2012–2019. Australian Journal of Social Issues. 2021 Sep;56(3):322-43. Mathews F, Ford TJ, White S, Ukoumunne OC, Newlove-Delgado T. Children and young people’s reported contact with professional services for mental health concerns: a secondary data analysis. European Child & Adolescent Psychiatry. 2024 Jan 4:1-9. Tracy LM, Capell E, Cleland HJ, Edgar DW, Singer Y, Teague WJ, Gabbe BJ. Feasibility of collecting long-term patient-reported outcome data in burns patients using a centralized approach. Burns. 2025 Feb 1;51(1):107304. Hendry D, Straker L, Bourne B, Coshan S, Kumwembe N, McCarthy C, Zabatiero J. Parental practices and perspectives on health and digital technology use information seeking for children aged 0–36 months. Health Promotion Journal of Australia. 2024 Feb 21. Wen LM, Xu H, Jawad D, Buchanan L, Rissel C, Phongsavan P, Baur LA, Taki S. Ethnicity matters in perceived impacts and information sources of COVID-19 among mothers with young children in Australia: a cross-sectional study. BMJ open. 2021 Nov 1;11(11):e050557. Kim P. How stress can influence brain adaptations to motherhood. Frontiers in Neuroendocrinology. 2021. Komalasari R. Harmonizing Midlife Motherhood: Navigating the Intersection of First-Time Maternity and Perimenopause. IGI Global, InUtilizing AI Techniques for the Perimenopause to Menopause Transition 2024 (pp. 148-179). Koshy B, Srinivasan M, Bose A, John S, Mohan VR, Roshan R, Ramanujam K, Kang G. Developmental trends in early childhood and their predictors from an Indian birth cohort. BMC public health. 2021 Dec;21:1-8. Sally I, Kuo C, Poore HE, Barr PB, Chirico IS, Aliev F, Bucholz KK, Chan G, Kamarajan C, Kramer JR, McCutcheon VV. The role of parental genotype in the intergenerational transmission of externalizing behavior: Evidence for genetic nurturance. Development and psychopathology. 2022 Dec;34(5):1865-75. Nas Z, Herle M, Kininmonth AR, Smith AD, Bryant‐Waugh R, Fildes A, Llewellyn CH. Nature and nurture in fussy eating from toddlerhood to early adolescence: findings from the Gemini twin cohort. Journal of Child Psychology and Psychiatry. 2024 Sep 19. Sharma, P., & , Chitra Bahadur Budhathoki, P. T. (2024). Factors Associated with Psychosocial Stimulation Development of Preschool Children in Rupandehi District of Nepal. KMC Journal, 6(1), 241–259. Sharma, P., Budhathoki, C. B., Devkota, B., & Singh, J. K. (2024). Healthy eating encouragement and sociodemographic factors associated with cognitive development among preschoolers: a cross-sectional evaluation in Nepal. European Journal of Public Health, 34(2), 230–236. https://doi.org/10.1093/eurpub/ckae018 Yamane, T. (2009). An Introductory analysis. In HARPER & ROW, NEW YORK, EVANSTON & LONDON AND JOHN WEATHERHILL, INC., TOKYO. https://doi.org/10.2307/2311831 Sharma, P., Budhathoki, C. B., Maharjan, R. K., & Singh, J. K. (2023). Nutritional status and psychosocial stimulation associated with cognitive development in preschool children: A cross-sectional study at Western Terai, Nepal. PLoS ONE, 18(3 March), 1–14. https://doi.org/10.1371/journal.pone.0280032 Widick, C., Parker, C. A., & Knefelkamp, L. (1978). Erik Erikson and psychosocial development. New Directions for Student Services, 1978(4), 1–17. https://doi.org/10.1002/ss.37119780403 Bureau of Labor Statistics, U.S. Department of Labor, and N. I. for C. H. and H. D. (2016). Children of the NLSY79. In Center for Human Resource Research (CHRR), The Ohio State University. Columbus, OH: 2019. Ministry of Health, N. E. and I. (2017). Nepal Demographic and Health Survey 2016. In Ministry of Health, Nepal. Sharma, P., Adamopoulos, I., Syrou, N., et al. The Impact of Health-Caregivers Emotional Nurturance on Cognitive Development in Preschoolers: A Nationwide Public Health Cross-Sectional Study, 12 December 2024, available at Research Square. https://doi.org/10.21203/rs.3.rs-5600588/v1 Pandey, H. (1991). Impact of preschool education component in integrated child development services programme on the cognitive development of children. Journal of Tropical Pediatrics, 37(5), 235–239. https://doi.org/10.1093/tropej/37.5.235 Contributors, W. (n.d.). Caste system in Nepal - Wikipedia, Google Scholar. At: https://en.wikipedia.org/wiki/Caste_system_in_Nepal[Accssesed 11-12-2024]. Jeong J, Franchett EE, Ramos de Oliveira CV, Rehmani K, Yousafzai AK. Parenting interventions to promote early child development in the first three years of life: A global systematic review and meta-analysis. PLoS medicine. 2021 May 10;18(5):e1003602. Likhar A, Patil MS. Importance of maternal nutrition in the first 1,000 days of life and its effects on child development: a narrative review. Daelmans B, Manji SA, Raina N. Nurturing care for early childhood development: global perspective and guidance. Indian Pediatrics. 2021. Sentenac M, Benhammou V, Aden U, Ancel PY, Bakker LA, Bakoy H, Barros H, Baumann N, Bilsteen JF, Boerch K, Croci I. Maternal education and cognitive development in 15 European very-preterm birth cohorts from the RECAP Preterm platform. International journal of epidemiology. 2021 Dec 1;50(6):1824-39. Black MM, Behrman JR, Daelmans B, Prado EL, Richter L, Tomlinson M, Trude AC, Wertlieb D, Wuermli AJ, Yoshikawa H. The principles of Nurturing Care promote human capital and mitigate adversities from preconception through adolescence. BMJ Global Health. 2021 Apr 1;6(4):e004436. Trude AC, Richter LM, Behrman JR, Stein AD, Menezes AM, Black MM. Effects of responsive caregiving and learning opportunities during preschool ages on the association of early adversities and adolescent human capital: an analysis of birth cohorts in two middle-income countries. The Lancet Child & Adolescent Health. 2021 Jan 1;5(1):37-46. McCormick BJ, Caulfield LE, Richard SA, Pendergast L, Seidman JC, Maphula A, Koshy B, Blacy L, Roshan R, Nahar B, Shrestha R. Early life experiences and trajectories of cognitive development. Pediatrics. 2020 Sep 1;146(3). Venancio SI, Teixeira JA, de Bortoli MC, Bernal RT. Factors associated with early childhood development in municipalities of Ceará, Brazil: a hierarchical model of contexts, environments, and nurturing care domains in a cross-sectional study. The Lancet Regional Health–Americas. 2022 Jan 1;5. Yang Q, Yang J, Zheng L, Song W et al. Impact of home parenting environment on cognitive and psychomotor development in children under 5 years old: A meta-analysis. Frontiers in pediatrics. 2021. Welch MG, Barone JL, Porges SW, Hane AA, Kwon KY, Ludwig RJ, Stark RI, Surman AL, Kolacz J, Myers MM. Family nurture intervention in the NICU increases autonomic regulation in mothers and children at 4-5 years of age: Follow-up results from a randomized controlled trial. PLoS One. 2020 Aug 4;15(8):e0236930. Bliznashka L, Udo IE, Sudfeld CR, Fawzi WW, Yousafzai AK. Associations between women’s empowerment and child development, growth, and nurturing care practices in sub-Saharan Africa: A cross-sectional analysis of demographic and health survey data. PLoS medicine. 2021 Sep 16;18(9):e1003781. Cooper K, Stewart K. Does household income affect children's outcomes? A systematic review of the evidence. Child Indicators Research. 2021. Bliznashka L, Udo IE, Sudfeld CR, Fawzi WW, Yousafzai AK. Associations between women’s empowerment and child development, growth, and nurturing care practices in sub-Saharan Africa: A cross-sectional analysis of demographic and health survey data. PLoS medicine. 2021 Sep 16;18(9):e1003781 Mahmood L, Flores-Barrantes P, Moreno LA, Manios Y, Gonzalez-Gil EM. The influence of parental dietary behaviors and practices on children’s eating habits. Nutrients. 2021 Mar 30;13(4):1138. Vilela S, Muresan I, Correia D, Severo M, Lopes C. The role of socioeconomic factors in food consumption of Portuguese children and adolescents: results from the National Food, Nutrition and Physical Activity Survey 2015–2016. British Journal of Nutrition. 2020 Sep;124(6):591-601. Penna AL, de Aquino CM, Pinheiro… MSN. Impact of the COVID-19 pandemic on maternal mental health, early childhood development, and parental practices: a global scoping review. BMC public health. 2023. Shumba C, Maina R, Mbuthia G, Kimani R, Mbugua S, Shah S, Abubakar A, Luchters S, Shaibu S, Ndirangu E. Reorienting nurturing care for early childhood development during the COVID-19 pandemic in Kenya: a review. International Journal of Environmental Research and Public Health. 2020 Oct;17(19):7028. Jeong J, Pitchik HO, Fink G. Short-term, medium-term and long-term effects of early parenting interventions in low-and middle-income countries: a systematic review. BMJ Global Health. 2021. Singh K, Kondal D, Mohan S, Jaganathan S, Deepa M, Venkateshmurthy NS, Jarhyan P, Anjana RM, Narayan KV, Mohan V, Tandon N. Health, psychosocial, and economic impacts of the COVID-19 pandemic on people with chronic conditions in India: a mixed methods study. BMC public health. 2021 Dec;21:1-5. Adamopoulos I, Frantzana A, Syrou N. Climate crises associated with epidemiological, environmental, and ecosystem effects of a storm: Flooding, landslides, and damage to urban and rural areas (Extreme weather events of Storm Daniel in Thessaly, Greece). Med Sci Forum. 2024;25(1):7. https://doi.org/10.3390/msf2024025007 Adamopoulos I, Lamnisos D, Syrou N, Boustras G. Public health and work safety pilot study: Inspection of job risks, burn out syndrome and job satisfaction of public health inspectors in Greece. Safety Science. 2022. Adamopoulos I, Syrou N, Lamnisos D, Boustras G., 2023. Cross-sectional nationwide study in occupational safety & health: Inspection of job risks context, burn out syndrome and job satisfaction of public health Inspectors in the period of the COVID-19 pandemic in Greece. Saf Sci. 2023 Feb;158:105960. Adamopoulos I, Syrou N, Lamnisos D, Dounias G. Public Health Inspectors Classification and Assessment of Environmental, Psychosocial, Organizational Risks and Workplace Hazards in the Context of the Global Climate Crisis. Preprints 2024, 2024120639. https://doi.org/10.20944/preprints202412.0639.v1 Adamopoulos I., Lamnisos D., Syrou N., Boustras G., Training Needs and Quality of Public Health Inspectors in Greece during the COVID-19 pandemic, European Journal of Public Health, Volume 32, Issue Supplement_3, October 2022, ckac131.373, https://doi.org/10.1093/eurpub/ckac131.373 Adamopoulos IP, Frantzana AA, Syrou NF. General practitioners, health inspectors, and occupational physicians’ burnout syndrome during COVID-19 pandemic and job satisfaction: A systematic review. EUR J ENV PUBLIC HLT. 2024;8(3):em0160. https://doi.org/10.29333/ejeph/14997 Adamopoulos IP, Frantzana AA, Syrou NF. Medical educational study burnout and job satisfaction among general practitioners and occupational physicians during the COVID-19 epidemic. Electr J Med Educ Technol. 2024; 17(1):em2402. https://doi.org/10.29333/ejmets/14299 Hegedűs M, Szivós E, Adamopoulus I, Dávid LD. (2024). Hospital integration to improve the chances of recovery for decubitus (pressure ulcer) patients through centralized procurement procedures. Journal of Infrastructure, Policy and Development. 8(10): 7273. https://doi.org/10.24294/jipd.v8i10.7273 Thapa P, Adamopoulos IP, Sharma P, Lordkipanidze R. Public hygiene and the awareness of beauty parlor: A study of consumer perspective. EUR J ENV PUBLIC HLT. 2024;8(2):em0157. https://doi.org/10.29333/ejeph/14738 Ali G, Mijwil MM, Adamopoulos I, Buruga BA, Gök M, Sallam M. Harnessing the Potential of Artificial Intelligence in Managing Viral Hepatitis. Mesopotamian Journal of Big Data [Internet]. 2024 Aug. 15 [cited 2024 Dec. 29];2024:128-63. https://mesopotamian.press/journals/index.php/bigdata/article/view/484 Khan, A. J. J.; Yar, S.; Fayyaz, S.; Adamopoulos, I.; Syrou, N.; Jahangir, A. From Pressure to Performance, and Health Risks Control: Occupational Stress Management and Employee Engagement in Higher Education. Preprints 2024 , 2024121329. https://doi.org/10.20944/preprints202412.1329.v1 Adamopoulos, I.; Syrou, N.; Lamnisos, D.; Dounias, G. Public Health Inspectors Classification and Assessment of Environmental, Psychosocial, Organizational Risks and Workplace Hazards in the Context of the Global Climate Crisis. Preprints 2024 , 2024120639. https://doi.org/10.20944/preprints202412.0639.v1 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5760180","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":399852393,"identity":"d1ee09f6-1554-4da4-ad2d-15952fa75e73","order_by":0,"name":"Prakash Sharma","email":"","orcid":"","institution":"Tribhuvan University","correspondingAuthor":false,"prefix":"","firstName":"Prakash","middleName":"","lastName":"Sharma","suffix":""},{"id":399852394,"identity":"5ba57faa-349d-4516-9aa2-4a2a2f2a6692","order_by":1,"name":"Niki Syrou","email":"","orcid":"","institution":"University of 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07:49:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46568,"visible":true,"origin":"","legend":"\u003cp\u003eDiagram of Detrended Normal Q-Q Plot of cognitive total score values.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5760180/v1/0de4301cc3380bd34ee4094a.png"},{"id":74423853,"identity":"656f2246-22a4-4137-bf6f-08f1dd02a0fb","added_by":"auto","created_at":"2025-01-22 07:49:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":29952,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eThe Histogram of the study's the correlations of frequency and cognitive total score.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5760180/v1/88cd0222d055c58065a8a4d6.png"},{"id":74423852,"identity":"5c59783a-3777-4ff0-b576-b33542f08cf1","added_by":"auto","created_at":"2025-01-22 07:49:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":34497,"visible":true,"origin":"","legend":"\u003cp\u003eCognitive total scores of the study's recorded for economic ranking\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5760180/v1/ca6f728a81ff06d9c9db9d64.png"},{"id":74426023,"identity":"503852cb-afeb-4643-ad78-9801b832ec56","added_by":"auto","created_at":"2025-01-22 08:05:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":44084,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eThe classifications of Mothers education mean values of cognitive stimulations scores.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5760180/v1/a427c241b7264b1be0cc36d2.png"},{"id":82041792,"identity":"db04c8ee-361c-4934-b41b-ad3edcf7c3ba","added_by":"auto","created_at":"2025-05-06 09:08:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1576438,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5760180/v1/90d8911d-4c45-4eae-9029-c3a5e63798d2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Public Health and Social Determinants on Maternal Factors for Academic Nurturance and the Cognitive Development of Preschool Children: A Cross-sectional Research Study","fulltext":[{"header":"Background","content":"\u003cp\u003ePublic health is concerned with the social conditions and determinants of sickness, as well as how society defines and addresses such conditions. Maternal health is a significant factor in the cognitive development of a preschool child[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Preschool children's cognitive development influences their preparation to begin school, and the quality of public education influences state and national social and economic issues[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], as well as public health. The emerging medical health literature considers maternal health in the context of public health[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe physical and emotional health of mothers, which has an impact on a fragile and dependent child, is of public importance. Research has demonstrated that early disadvantages frequently lead to childhood disease and developmental issues[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. A young child who is ill or inadequately nurtured is frequently fussy, angry, and weeping, and many people struggle with childrearing [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. For child-rearing to be most community-optimal, the child requires developmental-stage-appropriate care[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. An increasingly rigorous empirical literature has demonstrated that maternal behaviors can be harmful to child development[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Future avenues of inquiry will help inform society, policy, and services about what influences a mother and whether there are additional reasons for extra community assistance [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], as well as public health and maternal factors of concern [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePublic health research seeks to identify elements within the social ecology model that can enhance people's lives; nevertheless, the effects of public health and social determinants on mothers are frequently researched separately from the children they bring into the world and raise [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The conceptual framework is crucial for understanding how women's socioecological context influences preconception, pregnancy, and nursing, as well as health outcomes [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePublic health has a major impact on maternal characteristics connected to nurturance and, as a result, the cognitive development of preschool children, with implications for policies and programs aimed at improving early children's health[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The majority of research in this area has been undertaken by scholars, with the goal of comparing women's health behaviours, health state, and access to care, as well as health status and care utilization among low-income mothers [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. There is a need to do more to promote mothers' health, and this strategy should prioritize community-based services and family support [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEarly childhood is a critical period for cognitive development, laying the foundation for lifelong learning and well-being[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Research indicates that the quality of academic nurturance provided during this stage significantly influences children's cognitive, social, and emotional growth. Academic nurturance, encompassing the emotional, instructional, and material support provided to young learners, plays a vital role in shaping their cognitive abilities, problem-solving skills, and readiness for formal education [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the context of Nepal, particularly in the Rupandehi District, the role of academic nurturance in preschool settings has garnered increasing attention. As the country progresses toward enhancing early childhood education, understanding the interplay between nurturing environments and cognitive development becomes imperative. Despite national efforts to expand early childhood education programs, disparities in access, quality of instruction, and caregiver involvement persist, potentially affecting children's developmental outcomes.\u003c/p\u003e \u003cp\u003eRupandehi District, known for its diverse population and socioeconomic variability, presents a unique setting for exploring how academic nurturance impacts preschool children's cognitive development. Many children in the district experience varying levels of educational stimulation, which may be correlated with factors such as parental education, teacher training, and the availability of learning resources.\u003c/p\u003e \u003cp\u003eThis study aims to investigate the relationship between academic nurturance and the cognitive development of preschool children in Rupandehi District. By identifying key factors that contribute to or hinder cognitive growth, this research seeks to provide insights for educators, policymakers, and caregivers to foster enriched learning environments for early childhood development. The purpose of this study was to investigate the intricate interactions among public health variables, socioeconomic determinants, and maternal nurturance to better understand their involvement in cognitive development impairment in infants.\u003c/p\u003e \u003cp\u003eThe study is expected to produce empirical findings that will be useful to policymakers and public health professionals working in early childhood mental development, programs for women's health, and maternal care at local county health departments.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eStudy Design and Setting\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study utilized a cross-sectional descriptive survey design, targeting primary caregivers of preschool-aged children as participants. Data collection was conducted between February 4th and April 12th, 2021, across Rupandehi District, Nepal, from 14,358 children in government-operated early childhood development (ECD) centres, reflecting a rich tapestry of ethnic, cultural, and socioeconomic diversity[15,16].\u003c/p\u003e\n\u003cp\u003eThe sample size was calculated via Yamane\u0026apos;s formula[17].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;n= N\u003c/strong\u003e/\u003cstrong\u003e[1+N (e\u003csup\u003e2\u003c/sup\u003e)]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ewhere \u0026lsquo;n\u0026rsquo; represents the sample population, N= total population and \u0026lsquo;e\u0026rsquo; = 5% allowable error. This calculation yielded a sample of 389 children.\u003c/p\u003e\n\u003cp\u003eThe sampling process followed a multistage approach to ensure representativeness and rigor. Initially, three local administrative units were randomly selected from distinct strata, encompassing a sub metropolitan city, a municipality, and a rural municipality, to capture diverse geographic and socioeconomic contexts. In the subsequent phase, comprehensive records of schools and Early Childhood Development (ECD) centers were obtained from the selected local units. A simple random sampling method (lottery technique) was subsequently applied to draw five ECD centers from each local unit. In the final stage, the Population Proportionate Sampling (PPS) technique was utilized to allocate participants, resulting in a sample of 389 primary caregivers of preschool-aged children. If a primary caregiver was unavailable or unable to provide necessary information, a close family member was consulted as an alternative respondent.\u003c/p\u003e\n\u003cp\u003eThe study exclusively included caregivers who accompanied their preschool children to the respective ECD centres or schools during the data collection period. Participants who were unwilling to respond or provide data were excluded, along with ECD centres and schools that participated in pretesting the research instruments to minimize bias in the final analysis[18].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eData\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ecollection\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eData collection was conducted via a self-administered questionnaire with two sections. Section A assessed caregivers\u0026apos; academic nurturance practices, focusing on behaviors that contribute to emotional and cognitive development. The questionnaire included a series of questions to evaluate the extent of caregivers\u0026apos; involvement in stimulating their children\u0026apos;s learning. For example, caregivers were asked how often they or someone else read stories to their child in a week, with response options ranging from 2\u0026ndash;5 times to 0\u0026ndash;1 times.\u003c/p\u003e\n\u003cp\u003eCaregivers were also asked whether they asked questions about the stories they read to their child and how many children\u0026rsquo;s books the child owned, with responses indicating 2 or more books or none. Additional questions addressed whether caregivers or others taught their child about numbers, the alphabet, colours, and shapes and sizes. Furthermore, caregivers were asked if they discussed TV or YouTube programs with their child while watching and how often a family member took the child outings, with options ranging from 2-5 times per month to none. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Finally, caregivers were asked how often a family member took the child to a museum in a year, with responses indicating 2\u0026ndash;5 times or none [19]. Each question was scored as 1 for a \u0026quot;yes\u0026quot; answer and 0 for a \u0026quot;no\u0026quot; answer [20].\u003c/p\u003e\n\u003cp\u003eThis structured tool provides a detailed assessment of caregivers\u0026apos; involvement in cognitive stimulation, aiming to understand their role in fostering academic nurturance. In addition, Section A included socioeconomic variables such as the child\u0026apos;s gender and age, family structure, caste/ethnicity, maternal education level and family economic standing, recognizing these factors as potential determinants of cognitive and academic development. Economic status was measured via a tool from the 2016 Nepal Demographic and Health Survey (NDHS), which evaluated household assets and living conditions [21].\u003c/p\u003e\n\u003cp\u003eWealth scores were then classified into quartiles\u0026mdash;poorest, poor, rich, and richest\u0026mdash;on the basis of specific score ranges[22].\u0026nbsp;These\u0026nbsp;socioeconomic\u0026nbsp;factors were included to account for their possible influence on the developmental outcomes of the children in the study. Section B measured cognitive development\u0026nbsp;via\u0026nbsp;a standardized tool developed at the National Psychological Corporation of India, grounded in Piaget\u0026rsquo;s theory of developmental psychology[23].\u003c/p\u003e\n\u003cp\u003eThis instrument, designed for assessing children aged 3 to 5 years in the preoperational stage, converts raw scores into age-specific standard scores and includes tasks focused on symbolic play and basic problem-solving skills. To ensure the tool\u0026apos;s clarity, relevance, and cultural suitability, a pilot test was conducted with 10% of the sample, leading to minor revisions on the basis of participant feedback to improve contextual accuracy. The reliability of the cognitive development tool was confirmed, with a Cronbach\u0026rsquo;s alpha of 0.90, whereas the academic nurturing tool had an alpha of 0.80.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data were meticulously entered into Microsoft Excel and analysed via IBM SPSS version 26 to ensure robust statistical examination. Descriptive statistics were calculated for both continuous and categorical variables, including means and standard deviations for the former and frequencies for the latter. To facilitate group comparisons, independent sample t tests and ANOVA were employed, with a threshold of p \u0026lt; 0.05 set for statistical significance. The normality of the data distribution and thorough screening for outliers were performed, leading to a refined dataset of 389 valid cases.\u003c/p\u003e\n\u003cp\u003eTo identify key factors influencing cognitive development, multiple linear regression analysis was conducted. This analysis controlled for potential confounding variables to isolate significant predictors, providing a more accurate understanding of the relationships between variables. Additionally, the use of rigorous statistical techniques ensured the reliability and validity of the results, offering a comprehensive exploration of the determinants of cognitive development in the study population. Figure 1 shows the normal Q‒Q plot diagram of the total cognitive score values of the study\u0026apos;s.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e\u003cem\u003eDemographic\u0026nbsp;\u003c/em\u003e\u003cem\u003echaracteristics\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe study sample included N=389 children, with 50.6% male and 49.4% female participants. The age distribution revealed that 8.7% were three years old, whereas the majority were four (45.8%) or five years old (45.5%). Most families (72%) had two or fewer children. In terms of family structure, 52.4% lived in joint families, whereas 47.6% were part of nuclear households. Caste and ethnicity data indicated that 13.1% of the respondents were from the Dalit community, whereas 35.2% were from the advantageous caste. Educational background revealed that 23.4% of mothers were illiterate, whereas 8% had attained higher education. With respect to economic status, 24.7% of the respondents were categorized as the poorest, and 20.8% were categorized as the richest (Tables 1 \u0026amp; 2).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eDeterminants\u0026nbsp;\u003c/em\u003e\u003cem\u003eof academic nurturance\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eTable 1 illustrates the analysis of academic nurturance scores across various demographic variables. The findings highlight significant variations in mean nurturance scores based on critical factors. Notably, the number of children in the family (p=0.0001), caste (p=0.0001), mothers\u0026apos; education level (p=0.0001), and wealth status (p=0.0001) were strongly associated with differences in nurturance outcomes.\u003c/p\u003e\n\u003cp\u003eChildren from families with two or fewer children presented higher nurturance scores (M=5.28, SD=2.15) than did those from larger families (M=4.01, SD=2.36). Similarly, children from the advantageous caste had significantly greater nurturance (M=6.00, SD=2.05) than did Dalit children (M=3.88, SD=1.99). Maternal education showed a progressive increase in scores, with children of mothers with higher education achieving the highest nurturance (M=7.41, SD=1.76) compared with those whose mothers were illiterate (M=3.63, SD=2.21).\u003c/p\u003e\n\u003cp\u003eWealth status also demonstrated a positive trend, where children from the richest families had the highest nurturance scores (M=6.27, SD=1.66) compared with children from the poorest households (M=3.08, SD=2.08). However, no significant differences were observed in nurturance scores based on gender (p=0.819), age (p=0.623), or family structure (p=0.383).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u0026nbsp;\u003c/strong\u003eAnalysis of Academic Nurturance across Demographic Variables (\u0026Nu;=389)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"559\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2057%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender of children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e197\u003c/p\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e50.6\u003c/p\u003e\n \u003cp\u003e49.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e4.95\u003c/p\u003e\n \u003cp\u003e4.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e2.16\u003c/p\u003e\n \u003cp\u003e2.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2057%;\"\u003e\n \u003cp\u003e-0.40/0.50\u003c/p\u003e\n \u003cp\u003e-0.40/0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e.819\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge of children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThree years\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFour years\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFive years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e8.7\u003c/p\u003e\n \u003cp\u003e45.8\u003c/p\u003e\n \u003cp\u003e45.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e5.11\u003c/p\u003e\n \u003cp\u003e4.80\u003c/p\u003e\n \u003cp\u003e5.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2057%;\"\u003e\n \u003cp\u003e4.35/5.88\u003c/p\u003e\n \u003cp\u003e4.45/5.16\u003c/p\u003e\n \u003cp\u003e4.68/5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e.623\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTwo or less\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMore than two\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e280\u003c/p\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e5.28\u003c/p\u003e\n \u003cp\u003e4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003cp\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2057%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.77/1.77\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;1.12/2.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e.0001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypes of family\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNuclear\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eJoint\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003cp\u003e204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e47.6\u003c/p\u003e\n \u003cp\u003e52.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e4.82\u003c/p\u003e\n \u003cp\u003e5.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2057%;\"\u003e\n \u003cp\u003e-.65/0.25\u003c/p\u003e\n \u003cp\u003e-.65/0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e.383\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCastes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDalit\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eJanajati\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNon-Dalit Tarai\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAdvantageous caste\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e13.1\u003c/p\u003e\n \u003cp\u003e28.3\u003c/p\u003e\n \u003cp\u003e23.4\u003c/p\u003e\n \u003cp\u003e35.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e3.88\u003c/p\u003e\n \u003cp\u003e4.80\u003c/p\u003e\n \u003cp\u003e4.03\u003c/p\u003e\n \u003cp\u003e6.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003cp\u003e2.55\u003c/p\u003e\n \u003cp\u003e2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2057%;\"\u003e\n \u003cp\u003e3.32/4.44\u003c/p\u003e\n \u003cp\u003e4.45/5.15\u003c/p\u003e\n \u003cp\u003e3.50/4.56\u003c/p\u003e\n \u003cp\u003e5.65/6.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e.0001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMothers\u0026rsquo; education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIlliterate\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBasic level\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSecondary\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHigher Education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e23.4\u003c/p\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003cp\u003e22.4\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e3.63\u003c/p\u003e\n \u003cp\u003e4.70\u003c/p\u003e\n \u003cp\u003e5.93\u003c/p\u003e\n \u003cp\u003e7.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003cp\u003e1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2057%;\"\u003e\n \u003cp\u003e3.17/4.09\u003c/p\u003e\n \u003cp\u003e4.41/4.99\u003c/p\u003e\n \u003cp\u003e5.52/6.34\u003c/p\u003e\n \u003cp\u003e6.77/8.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e.0001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoorest\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePoor\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRich\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRichest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e24.7\u003c/p\u003e\n \u003cp\u003e25.4\u003c/p\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003cp\u003e20.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e3.08\u003c/p\u003e\n \u003cp\u003e4.61\u003c/p\u003e\n \u003cp\u003e5.80\u003c/p\u003e\n \u003cp\u003e6.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e2.08\u003c/p\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003cp\u003e2.03\u003c/p\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2057%;\"\u003e\n \u003cp\u003e2.66/3.50\u003c/p\u003e\n \u003cp\u003e4.23/5.00\u003c/p\u003e\n \u003cp\u003e5.42/6.18\u003c/p\u003e\n \u003cp\u003e5.90/6.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e.0001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2057%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.0001, p\u003cdel cite=\"mailto:Editor%202\" datetime=\"2025-01-03T13:15\"\u003e-\u003c/del\u003e value calculated via t tests and one-way ANOVA.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eDeterminants of cognitive development\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eTable 2 presents the analysis of the cognitive development scores across various demographic variables. There was no statistically significant difference in cognitive development between male (M=101.74, SD=15.35) and female children (M=102.21, SD=15.52), with a p value of 0.766. This suggests that gender does not play a significant role in determining cognitive development within the sample population. Age was significantly associated with cognitive development (p=0.016). Children aged three years had the highest mean cognitive scores (M=108.94, SD=21.60), followed by four-year-olds (M=101.92, SD=12.93) and five-year-olds (M=100.68, SD=16.05). The number of children in the family did not significantly impact cognitive development (p=0.278). Children from families with two or fewer children had slightly higher scores (M=102.50, SD=15.36) than those from larger families did (M=100.61, SD=15.57), but the difference was not statistically significant. A significant difference in cognitive development was observed between children from nuclear and joint families (p=0.013). Children from nuclear families presented higher cognitive scores (M=104.00, SD=14.33) than did those from joint families (M=100.13, SD=16.16). Caste/ethnicity was highly significantly associated with cognitive development (p=0.0001). Children from advantageous castes had the highest cognitive scores (M=107.68, SD=14.57), whereas Dalit children recorded the lowest mean scores (M=99.49, SD=15.13). Janajati and non-Dalit Tarai caste children had intermediate scores (M=98.41, SD=14.72 and M=99.07, SD=15.42, respectively). Maternal education was significantly associated with cognitive development (p=0.002). Children of mothers with higher education levels achieved the highest cognitive scores (M=109.12, SD=16.19), whereas children whose mothers were illiterate recorded the lowest scores (M=99.79, SD=13.68). Wealth status had a significant effect on cognitive development (p=0.038). Children from the richest families had higher cognitive scores (M=103.35, SD=17.75) than those from the poorest households did (M=99.63, SD=14.12).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003e\u003cem\u003eAnalysis of Cognitive Development across Demographic Variables (N=389)\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"559\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1002%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.839%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender of children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e197\u003c/p\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e50.6\u003c/p\u003e\n \u003cp\u003e49.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e101.74\u003c/p\u003e\n \u003cp\u003e102.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e15.35\u003c/p\u003e\n \u003cp\u003e15.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1002%;\"\u003e\n \u003cp\u003e-3.54/2.61\u003c/p\u003e\n \u003cp\u003e-3.54/2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.839%;\"\u003e\n \u003cp\u003e.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge of children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThree years\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFour years\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFive years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e8.7\u003c/p\u003e\n \u003cp\u003e45.8\u003c/p\u003e\n \u003cp\u003e45.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e108.94\u003c/p\u003e\n \u003cp\u003e101.92\u003c/p\u003e\n \u003cp\u003e100.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e21.60\u003c/p\u003e\n \u003cp\u003e12.93\u003c/p\u003e\n \u003cp\u003e16.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1002%;\"\u003e\n \u003cp\u003e101.40/116.47\u003c/p\u003e\n \u003cp\u003e100.01/103.8498.30/103.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.839%;\"\u003e\n \u003cp\u003e.016\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTwo or less\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMore than two\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e280\u003c/p\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e102.50\u003c/p\u003e\n \u003cp\u003e100.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e15.36\u003c/p\u003e\n \u003cp\u003e15.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1002%;\"\u003e\n \u003cp\u003e\u0026nbsp;-1.53/5.31\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;-1.56/5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.839%;\"\u003e\n \u003cp\u003e.278\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypes of family\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNuclear\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eJoint\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003cp\u003e204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e47.6\u003c/p\u003e\n \u003cp\u003e52.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e104.00\u003c/p\u003e\n \u003cp\u003e100.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e14.33\u003c/p\u003e\n \u003cp\u003e16.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1002%;\"\u003e\n \u003cp\u003e0.80/6.92\u003c/p\u003e\n \u003cp\u003e0.82/6.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.839%;\"\u003e\n \u003cp\u003e.013\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCastes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDalit\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eJanajati\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNon-Dalit Tarai caste\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAdvantageous caste\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e13.1\u003c/p\u003e\n \u003cp\u003e28.3\u003c/p\u003e\n \u003cp\u003e23.4\u003c/p\u003e\n \u003cp\u003e35.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e99.49\u003c/p\u003e\n \u003cp\u003e98.41\u003c/p\u003e\n \u003cp\u003e99.07\u003c/p\u003e\n \u003cp\u003e107.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e15.13\u003c/p\u003e\n \u003cp\u003e14.72\u003c/p\u003e\n \u003cp\u003e15.42\u003c/p\u003e\n \u003cp\u003e14.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1002%;\"\u003e\n \u003cp\u003e95.23/103.74\u003c/p\u003e\n \u003cp\u003e95.63/101.20\u003c/p\u003e\n \u003cp\u003e95.86/102.28\u003c/p\u003e\n \u003cp\u003e105.22/110.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.839%;\"\u003e\n \u003cp\u003e.0001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMothers\u0026rsquo; education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIlliterate\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBasic level\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSecondary\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHigher Education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e23.4\u003c/p\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003cp\u003e22.4\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e99.79\u003c/p\u003e\n \u003cp\u003e100.38\u003c/p\u003e\n \u003cp\u003e105.21\u003c/p\u003e\n \u003cp\u003e109.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e13.68\u003c/p\u003e\n \u003cp\u003e15.94\u003c/p\u003e\n \u003cp\u003e14.73\u003c/p\u003e\n \u003cp\u003e16.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1002%;\"\u003e\n \u003cp\u003e96.94/102.64\u003c/p\u003e\n \u003cp\u003e98.00/102.76\u003c/p\u003e\n \u003cp\u003e102.07/108.35103.18/115.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.839%;\"\u003e\n \u003cp\u003e.002**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoorest\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePoor\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRich\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRichest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e24.7\u003c/p\u003e\n \u003cp\u003e25.4\u003c/p\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003cp\u003e20.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e99.63\u003c/p\u003e\n \u003cp\u003e99.90\u003c/p\u003e\n \u003cp\u003e104.78\u003c/p\u003e\n \u003cp\u003e103.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e14.12\u003c/p\u003e\n \u003cp\u003e14.67\u003c/p\u003e\n \u003cp\u003e14.95\u003c/p\u003e\n \u003cp\u003e17.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1002%;\"\u003e\n \u003cp\u003e96.77/102.49\u003c/p\u003e\n \u003cp\u003e96.98/102.83\u003c/p\u003e\n \u003cp\u003e102.00/107.5799.43/107.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.839%;\"\u003e\n \u003cp\u003e.038*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8479%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.1181%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.08229%;\"\u003e\n \u003cp\u003e389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.8712%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7335%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.40787%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1002%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe Dalit caste holds the lowest social status, often associated with untouchability. Janajati and non-Dalit Tarai castes rank above Dalits but below advantaged castes in the social hierarchy in Nepal [24].The Figure 2 shows the Diagram of Detrended Normal Q-QPlot of cognitive total score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMultiple Regression Analysis: Predictors of Cognitive Development\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 presents the results of multiple regression models that examine the relationships between various predictors and cognitive development. The analysis is split into two models: Model 1 assesses the impact of socioeconomic factors on cognitive development, whereas Model 2 incorporates both socioeconomic factors and academic nurturance.\u003c/p\u003e\n\u003cp\u003eIn \u003cstrong\u003e\u003cem\u003eModel 1\u003c/em\u003e\u003c/strong\u003e, economic status is a significant predictor of cognitive development (\u0026beta; = -0.254, p = 0.000), with a negative association indicating that lower economic status is linked to poorer cognitive development. Conversely, advantageous caste was also a significant predictor, with a negative coefficient (\u0026beta; = -0.147, p = 0.004), suggesting that children from advantageous caste backgrounds had lower cognitive development scores. The number of children in the family and mothers\u0026rsquo; illiteracy did not significantly affect cognitive development (p \u0026gt; 0.05). The model explains 8.2% of the variance in cognitive development (R\u0026sup2; = 8.2%), with an F\u003cins cite=\"mailto:Editor%202\" datetime=\"2025-01-03T13:15\"\u003e\u0026nbsp;\u003c/ins\u003estatistic of 5.608 (p = 0.000).\u003c/p\u003e\n\u003cp\u003eIn \u003cstrong\u003e\u003cem\u003eModel 2\u003c/em\u003e\u003c/strong\u003e, when academic nurturance was added as a predictor, it did not\u0026nbsp;have a significant effect (\u0026beta; = -0.003, p = 0.954). However, family structure was a significant predictor, as children from joint families presented significantly lower cognitive development scores (\u0026beta; = -0.148, p = 0.004). The age of the child also had a marginally significant negative effect (\u0026beta; = -0.107, p = 0.035), suggesting that older children may experience different developmental trajectories. Advantageous caste, which was significant in Model 1, remained a significant predictor of cognitive development in this model (\u0026beta; = 0.195, p = 0.000). The model explains 8.0% of the variance in cognitive development (R\u0026sup2; = 8.0%), with an F statistic of 4.667 (p = 0.000). The Figure 3 shows the Histogram of the study\u0026apos;s the correlations of frequency and cognitive total score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3.\u0026nbsp;\u003c/strong\u003e\u003cem\u003eMultiple regression model independent variables predicting cognitive\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"589\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandardized Coefficients \u0026beta; (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandardize Coefficients \u0026beta; (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEconomic status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e-0.254 (-1.001/-0.394)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e.0001\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e0.108 (-0.099/ \u0026nbsp; \u0026nbsp; \u0026nbsp; 4.093)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint family\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e0.034 (-0.297/0.609)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e-0.148 (-7.591/-1.493)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e0.004\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMother\u0026apos;s illiteracy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e0.003 (-0.579/0.615)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e0.953\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e0.008 (-3.739/4.294)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdvantageous caste\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e-0.147(-1.145 \u0026nbsp; \u0026nbsp; \u0026nbsp; /-0.222)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e.0001\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e0.195 (2.935/9.218)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e.0001\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e0.016 (-0.456/0.619)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e0.042 (-2.187/5.048)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e0.437\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge of child\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e0.048 (-0.182/0.524)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e0.342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e-0.107 (-4.935/-0.181)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e.035\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcademic nurturance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e-0.003 (-0.701/0.661)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR Square\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e8.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e8.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd. Error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e14.897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF (P value)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.146%;\"\u003e\n \u003cp\u003e5.608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.2054%;\"\u003e\n \u003cp\u003e0.0001\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.5229%;\"\u003e\n \u003cp\u003e4.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3752%;\"\u003e\n \u003cp\u003e\u0026nbsp; 0.0001\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNote:\u003c/em\u003e\u003c/strong\u003e \u003cem\u003e*p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.0001\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eModel-I:\u003c/em\u003e\u003c/strong\u003e Academic nurturance score adjusted for socioeconomic factors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eModel\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e-\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eII:\u003c/em\u003e\u003c/strong\u003e Cognitive development score adjusted for socioeconomic factors and the academic nurturance\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eindex, the Table 4 shows the \u0026nbsp;Cognitive total score of the quintiles confidence interval means.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 4.\u003c/strong\u003e \u003cem\u003eCognitive total score of the quintiles confidence interval means.\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 642px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescriptives\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"bottom\" style=\"width: 642px;\"\u003e\n \u003cp\u003eCognitive_total_score \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003eStd. Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 158px;\"\u003e\n \u003cp\u003e95% Confidence Interval for Mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003eLower Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUpper Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4th quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e99.6354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e14.12062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e1.44118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e96.7743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e102.4965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e64.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e141.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3rd quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e99.9091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e14.67824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e1.47522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e96.9816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e102.8366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e67.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e138.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2nd quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e104.7876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e14.95437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e1.40679\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e102.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e107.5750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e72.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e138.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1st quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e103.3580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e17.75479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e1.97275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e99.4321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e107.2839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e62.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e138.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e101.9769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e15.42514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e.78209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e100.4392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e103.5145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e62.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e141.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe Figure 5 shows the classifications of Mothers education mean values of cognitive stimulations scores.\u003c/p\u003e"},{"header":"Discussion and findings of the research","content":"\u003cp\u003ePublic health focuses on lifespan, highlighting the importance of mothers\u0026rsquo; health in preschool-aged children\u0026apos;s well-being[25]. Healthcare disparities between affluent and underprivileged women, influenced by cultural practices and beliefs, persist[26]. Women from diverse backgrounds, including African American women, face barriers to timely prenatal care[27,28]. Despite public health initiatives improving access, disadvantaged sociodemographic groups still lack access to these services[29,30].\u003cstrong\u003e\u003cdel cite=\"mailto:Editor%202\" datetime=\"2025-01-03T13:15\"\u003e \u003c/del\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings from Tables shows that children from families with two or fewer children had significantly higher nurturance scores than those from larger families. Compared with Dalit children, children from the advantageous caste had higher nurturance scores. Maternal education level showed a progressive increase in academic nurturance scores. Wealth status also had a significant effect, with children from the richest families having the highest nurturance scores, which is supported by the global literature. \u003c/p\u003e\n\u003cp\u003eDuring the early years of life, children\u0026apos;s brain volume expands, affecting their cognitive and language skills[31]. Early interactions with mothers and exposure to richer language, particularly nonverbal vocabulary, contribute to cognitive development[32]. Even slight variations in maternal care can significantly impact cognitive growth until adolescence, and interactions with mothers are particularly significant[33]. The richer mental states significantly correlate with enhanced cognitive growth in children, especially regarding their nonverbal vocabulary related to understanding a wide range of emotions[34].\u003c/p\u003e\n\u003cp\u003eThe findings from Tables of the study show that age was significantly associated with cognitive development. Three-year-old children presented the highest cognitive scores, whereas five-year-olds presented slightly lower scores. This suggests that cognitive advantages may diminish slightly with age in the sample. Children from nuclear families achieved higher cognitive scores than those from joint families did. Significant differences in cognitive development were evident across caste groups. Children from advantageous castes recorded the highest cognitive scores, whereas Dalit children scored lowest. Maternal education levels were significantly associated with cognitive development. Compared with children of illiterate mothers, children of mothers with higher education levels had superior cognitive outcomes. Economic status influences cognitive development. Children from the wealthiest families presented higher cognitive scores than those from the poorest families did, which is in line with the findings of the global literature.\u003c/p\u003e\n\u003cp\u003ePublic health interventions have a restricted effect on the factors that contribute to maternal nurturing, among the various social determinants, only maternal mental health was identified as having a significant influence on positive outcomes, which is highlighted in the key findings from the regression analyses[33,35]. The discussion centers on how sociodemographic factors can either positively or negatively affect aspects of maternal nurturance, as well as maternal cognitive development[36]. This is accompanied by tables that summarize the significant determinants identified through different analytical models (1 and 2). Additionally, the results section includes an examination of other factors affecting maternal cognitive development.\u003c/p\u003e\n\u003cp\u003eThe findings from the multiple regression analysis (Table 3) and Model 1 show that the analysis of socioeconomic factors as predictors of academic nurturance revealed that economic status was a significant negative predictor, with lower economic status being linked to poorer academic nurturance. Additionally, caste was significant, with children from disadvantageous caste backgrounds having lower academic nurturance scores.\u003c/p\u003e\n\u003cp\u003eThe findings from Model 2 concerning family structure became a significant predictor, with children from joint families exhibiting lower cognitive development scores.\u003c/p\u003e\n\u003cp\u003eAge had a marginally significant negative impact, indicating that as children grew older, their cognitive development slightly decreased. This could be attributed to the tendency for caregivers to provide less nurturing as children grow older, often redirecting attention and resources toward younger siblings. Additionally, older children may assume more care for younger family members, which could reduce the time and energy available for their own cognitive development[23]. Advantageous caste remains a significant predictor of cognitive development. The findings from Model Explanation are that the models explained 8.2% (Model 1) and 8.0% (Model 2) of the variance in cognitive development, with both models having significant F-statistics (p=0.000), the above supported with the global literature. One of the critical insights from the literature is the notion that socioeconomic status significantly influences dietary behaviours and health outcomes. Families with lower socioeconomic status face greater challenges in adopting health-promoting behaviours, which can lead to a higher incidence of chronic no communicable diseases among their children[38]. This connection emphasizes the need for targeted interventions that not only promote healthy eating but also address the socioeconomic barriers that hinder access to nurturance [39].\u003c/p\u003e\n\u003cp\u003eThe critical role of maternal involvement in child development frames it within the broader context of social determinants such as socioeconomic status and mental health[40]. Effective maternal‒child communication is identified as essential for optimal developmental outcomes, with a lack of engagement leading to delays in cognitive and emotional growth[41]. The impact of public health inequities that manifest early in life points to factors and social deprivation that adversely affect both maternal well-being and child development [42]. Additionally, the implications of maternal mental health for child development are addressed, emphasizing that maternal anxiety and depression can severely hinder a mother\u0026rsquo;s ability to provide adequate care, thereby compromising the child\u0026apos;s developmental trajectory[43]. Ultimately, a crucial aspect of the impact of public health and social determinants on maternal factors for academic nurturance and ethical considerations involves addressing the cognitive development of preschool children, preventing burnout syndrome, increasing job satisfaction[44,45], and reducing occupational stress, particularly in the context of the COVID-19 pandemic, [46,47] and the ongoing climate crisis in teaching staff and caregivers[48,49]. Effective training, education, and competent management of healthcare and public health services are essential[50,51] for ensuring the quality of hospital care and public health initiatives, which are supported by strategic policy interventions[52-55].\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eImplications for practice\u003cdel cite=\"mailto:Editor%202\" datetime=\"2025-01-03T13:15\"\u003e \u003c/del\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study contributes to the field of maternal and child health by informing both clinical and public health practices throughout the life course and highlighting the connection between maternal nurturance and cognitive development in preschool children. The results will pave the way for future longitudinal studies, necessitating a more thorough exploration and refinement of the elements in the proposed model. The findings will also guide future research directions and inform program development and implementation. This study underscores the crucial role of interventions to enhance maternal health and well-being, fostering more nurturing environments. First, increasing and diversifying resources for public health interventions, along with providing financial support for women experiencing high levels of stress or potential abuse, could significantly improve nurturing conditions. Furthermore, offering educational tools and expanding support services, parenting workshops, and access to family support professionals could benefit mothers. However, for these classes or professionals to make meaningful differences, they must be designed to effectively reduce stress and promote positive interactions between parents and children. Simply offering information without practical resources will not lead to immediate changes. Additionally, this research highlights the necessity of addressing social determinants. The findings suggest that policymakers should consider funding initiatives that explore the broader impact of social determinants on maternal health.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLimitations\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e \u003c/em\u003e\u003cstrong\u003e\u003cem\u003eof the study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study acknowledges its limitations while highlighting potential applications for database improvements. The current datasets provide a foundation for further exploration of this topic. By thoroughly analysing the initial research outcomes, the understanding of maternal and child health, public health, and the social determinants of health can be enriched. The main conclusions of this research support this hypothesis, which suggests that areas with social disarray tend to have a greater number of mothers exhibiting negative maternal characteristics acquired from domestic environments.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of this research highlight the significant role that family size, caste, maternal education, and wealth status play in shaping academic nurturance. Children from smaller families, advantageous castes, and wealthier backgrounds consistently demonstrated higher levels of academic nurturance and cognitive development. Although academic nurturance itself does not have a direct effect on cognitive development, this study reveals that socioeconomic factors, particularly ethnicity, family structure and the age of children, are crucial predictors of children's cognitive outcomes. These results emphasize the need for targeted interventions to address disparities in educational access and outcomes. The study advocates for policies that focus on improving parental education, reducing economic inequalities, and creating inclusive learning environments to foster equitable academic and cognitive growth for all children.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to extend our heartfelt gratitude to all the individuals who actively participated in this study. Additionally, we would like to express our appreciation to the Editors, and reviewers for their valuable feedback and insightful suggestions for improving this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConceptualization and writing of the first draft edited and reviewed the manuscript. PS and IA, Principal Investigators PS and IA, designed the research question and analytical approach from PS, IA, NS and AG. PS and IA conducted all analyses and wrote the final version of the manuscript with contributions from PS, IA, AG and NS. Supervision IA, Project Administration IA and PS. All the authors reviewed, edited, and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received no grants or funding from any source.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDue to privacy restrictions, the data presented in this study are available upon request from the corresponding authors upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations The authors declare no conflicts of interest.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for the study was secured from the Board of Ethical Review at the Nepal Health Research Council (NHRC: No. 2078-56/2021), following prior authorization from the Office of the Dean, Faculty of Education, Tribhuvan University. Additionally, all previous research and scholarly contributions relevant to the study were appropriately acknowledged, and their works were thoroughly cited throughout the research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors give consent for publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEkholuenetale M, Barrow A, Ekholuenetale CE, Tudeme G. Impact of stunting on early childhood cognitive development in Benin: evidence from Demographic and Health Survey. Egyptian Pediatric Association Gazette. 2020 Dec;68:1-1.\u003c/li\u003e\n\u003cli\u003eChaparro J, Sojourner A, Wiswall MJ. Early childhood care and cognitive development. 2020.\u003c/li\u003e\n\u003cli\u003eKumar M, Huang KY. Impact of being an adolescent mother on subsequent maternal health, parenting, and child development in Kenyan low-income and high adversity informal settlement, PloS one. 2021.\u003c/li\u003e\n\u003cli\u003eWreyford N, Newsinger J, Kennedy H, Aust R. Locked down and locked out: mothers and UKTV work during the COVID-19 pandemic. Feminist Media Studies. 2024 Nov 16;24(8):1894-913.\u003c/li\u003e\n\u003cli\u003eWebb N, Moloney LJ, Smyth BM, Murphy RL. Allegations of child sexual abuse: An empirical analysis of published judgements from the Family Court of Australia 2012\u0026ndash;2019. Australian Journal of Social Issues. 2021 Sep;56(3):322-43.\u003c/li\u003e\n\u003cli\u003eMathews F, Ford TJ, White S, Ukoumunne OC, Newlove-Delgado T. Children and young people\u0026rsquo;s reported contact with professional services for mental health concerns: a secondary data analysis. European Child \u0026amp; Adolescent Psychiatry. 2024 Jan 4:1-9.\u003c/li\u003e\n\u003cli\u003eTracy LM, Capell E, Cleland HJ, Edgar DW, Singer Y, Teague WJ, Gabbe BJ. Feasibility of collecting long-term patient-reported outcome data in burns patients using a centralized approach. Burns. 2025 Feb 1;51(1):107304.\u003c/li\u003e\n\u003cli\u003eHendry D, Straker L, Bourne B, Coshan S, Kumwembe N, McCarthy C, Zabatiero J. Parental practices and perspectives on health and digital technology use information seeking for children aged 0\u0026ndash;36 months. Health Promotion Journal of Australia. 2024 Feb 21.\u003c/li\u003e\n\u003cli\u003eWen LM, Xu H, Jawad D, Buchanan L, Rissel C, Phongsavan P, Baur LA, Taki S. Ethnicity matters in perceived impacts and information sources of COVID-19 among mothers with young children in Australia: a cross-sectional study. BMJ open. 2021 Nov 1;11(11):e050557.\u003c/li\u003e\n\u003cli\u003eKim P. How stress can influence brain adaptations to motherhood. Frontiers in Neuroendocrinology. 2021.\u003c/li\u003e\n\u003cli\u003eKomalasari R. Harmonizing Midlife Motherhood: Navigating the Intersection of First-Time Maternity and Perimenopause. IGI Global, InUtilizing AI Techniques for the Perimenopause to Menopause Transition 2024 (pp. 148-179).\u003c/li\u003e\n\u003cli\u003eKoshy B, Srinivasan M, Bose A, John S, Mohan VR, Roshan R, Ramanujam K, Kang G. Developmental trends in early childhood and their predictors from an Indian birth cohort. BMC public health. 2021 Dec;21:1-8.\u003c/li\u003e\n\u003cli\u003eSally I, Kuo C, Poore HE, Barr PB, Chirico IS, Aliev F, Bucholz KK, Chan G, Kamarajan C, Kramer JR, McCutcheon VV. The role of parental genotype in the intergenerational transmission of externalizing behavior: Evidence for genetic nurturance. Development and psychopathology. 2022 Dec;34(5):1865-75.\u003c/li\u003e\n\u003cli\u003eNas Z, Herle M, Kininmonth AR, Smith AD, Bryant‐Waugh R, Fildes A, Llewellyn CH. Nature and nurture in fussy eating from toddlerhood to early adolescence: findings from the Gemini twin cohort. Journal of Child Psychology and Psychiatry. 2024 Sep 19.\u003c/li\u003e\n\u003cli\u003eSharma, P., \u0026amp; , Chitra Bahadur Budhathoki, P. T. (2024). Factors Associated with Psychosocial Stimulation Development of Preschool Children in Rupandehi District of Nepal. KMC Journal, 6(1), 241\u0026ndash;259.\u003c/li\u003e\n\u003cli\u003eSharma, P., Budhathoki, C. B., Devkota, B., \u0026amp; Singh, J. K. (2024). Healthy eating encouragement and sociodemographic factors associated with cognitive development among preschoolers: a cross-sectional evaluation in Nepal. European Journal of Public Health, 34(2), 230\u0026ndash;236. https://doi.org/10.1093/eurpub/ckae018\u003c/li\u003e\n\u003cli\u003eYamane, T. (2009). An Introductory analysis. In HARPER \u0026amp; ROW, NEW YORK, EVANSTON \u0026amp; LONDON AND JOHN WEATHERHILL, INC., TOKYO. https://doi.org/10.2307/2311831\u003c/li\u003e\n\u003cli\u003eSharma, P., Budhathoki, C. B., Maharjan, R. K., \u0026amp; Singh, J. K. (2023). Nutritional status and psychosocial stimulation associated with cognitive development in preschool children: A cross-sectional study at Western Terai, Nepal. PLoS ONE, 18(3 March), 1\u0026ndash;14. https://doi.org/10.1371/journal.pone.0280032\u003c/li\u003e\n\u003cli\u003eWidick, C., Parker, C. A., \u0026amp; Knefelkamp, L. (1978). Erik Erikson and psychosocial development. New Directions for Student Services, 1978(4), 1\u0026ndash;17. https://doi.org/10.1002/ss.37119780403\u003c/li\u003e\n\u003cli\u003eBureau of Labor Statistics, U.S. Department of Labor, and N. I. for C. H. and H. D. (2016). Children of the NLSY79. In Center for Human Resource Research (CHRR), The Ohio State University. Columbus, OH: 2019.\u003c/li\u003e\n\u003cli\u003eMinistry of Health, N. E. and I. (2017). Nepal Demographic and Health Survey 2016. In Ministry of Health, Nepal.\u003c/li\u003e\n\u003cli\u003eSharma, P., Adamopoulos, I., Syrou, N., et al. The Impact of Health-Caregivers Emotional Nurturance on Cognitive Development in Preschoolers: A Nationwide Public Health Cross-Sectional Study, 12 December 2024, available at Research Square. https://doi.org/10.21203/rs.3.rs-5600588/v1\u003c/li\u003e\n\u003cli\u003ePandey, H. (1991). Impact of preschool education component in integrated child development services programme on the cognitive development of children. Journal of Tropical Pediatrics, 37(5), 235\u0026ndash;239. https://doi.org/10.1093/tropej/37.5.235\u003c/li\u003e\n\u003cli\u003eContributors, W. (n.d.). Caste system in Nepal - Wikipedia, Google Scholar. At: https://en.wikipedia.org/wiki/Caste_system_in_Nepal[Accssesed 11-12-2024].\u003c/li\u003e\n\u003cli\u003eJeong J, Franchett EE, Ramos de Oliveira CV, Rehmani K, Yousafzai AK. Parenting interventions to promote early child development in the first three years of life: A global systematic review and meta-analysis. PLoS medicine. 2021 May 10;18(5):e1003602.\u003c/li\u003e\n\u003cli\u003eLikhar A, Patil MS. Importance of maternal nutrition in the first 1,000 days of life and its effects on child development: a narrative review.\u003c/li\u003e\n\u003cli\u003eDaelmans B, Manji SA, Raina N. Nurturing care for early childhood development: global perspective and guidance. Indian Pediatrics. 2021.\u003c/li\u003e\n\u003cli\u003eSentenac M, Benhammou V, Aden U, Ancel PY, Bakker LA, Bakoy H, Barros H, Baumann N, Bilsteen JF, Boerch K, Croci I. Maternal education and cognitive development in 15 European very-preterm birth cohorts from the RECAP Preterm platform. International journal of epidemiology. 2021 Dec 1;50(6):1824-39.\u003c/li\u003e\n\u003cli\u003eBlack MM, Behrman JR, Daelmans B, Prado EL, Richter L, Tomlinson M, Trude AC, Wertlieb D, Wuermli AJ, Yoshikawa H. The principles of Nurturing Care promote human capital and mitigate adversities from preconception through adolescence. BMJ Global Health. 2021 Apr 1;6(4):e004436.\u003c/li\u003e\n\u003cli\u003eTrude AC, Richter LM, Behrman JR, Stein AD, Menezes AM, Black MM. Effects of responsive caregiving and learning opportunities during preschool ages on the association of early adversities and adolescent human capital: an analysis of birth cohorts in two middle-income countries. The Lancet Child \u0026amp; Adolescent Health. 2021 Jan 1;5(1):37-46.\u003c/li\u003e\n\u003cli\u003eMcCormick BJ, Caulfield LE, Richard SA, Pendergast L, Seidman JC, Maphula A, Koshy B, Blacy L, Roshan R, Nahar B, Shrestha R. Early life experiences and trajectories of cognitive development. Pediatrics. 2020 Sep 1;146(3).\u003c/li\u003e\n\u003cli\u003eVenancio SI, Teixeira JA, de Bortoli MC, Bernal RT. Factors associated with early childhood development in municipalities of Cear\u0026aacute;, Brazil: a hierarchical model of contexts, environments, and nurturing care domains in a cross-sectional study. The Lancet Regional Health\u0026ndash;Americas. 2022 Jan 1;5.\u003c/li\u003e\n\u003cli\u003eYang Q, Yang J, Zheng L, Song W et al. Impact of home parenting environment on cognitive and psychomotor development in children under 5 years old: A meta-analysis. Frontiers in pediatrics. 2021.\u003c/li\u003e\n\u003cli\u003eWelch MG, Barone JL, Porges SW, Hane AA, Kwon KY, Ludwig RJ, Stark RI, Surman AL, Kolacz J, Myers MM. Family nurture intervention in the NICU increases autonomic regulation in mothers and children at 4-5 years of age: Follow-up results from a randomized controlled trial. PLoS One. 2020 Aug 4;15(8):e0236930.\u003c/li\u003e\n\u003cli\u003eBliznashka L, Udo IE, Sudfeld CR, Fawzi WW, Yousafzai AK. Associations between women\u0026rsquo;s empowerment and child development, growth, and nurturing care practices in sub-Saharan Africa: A cross-sectional analysis of demographic and health survey data. PLoS medicine. 2021 Sep 16;18(9):e1003781.\u003c/li\u003e\n\u003cli\u003eCooper K, Stewart K. Does household income affect children\u0026apos;s outcomes? A systematic review of the evidence. Child Indicators Research. 2021.\u003c/li\u003e\n\u003cli\u003eBliznashka L, Udo IE, Sudfeld CR, Fawzi WW, Yousafzai AK. Associations between women\u0026rsquo;s empowerment and child development, growth, and nurturing care practices in sub-Saharan Africa: A cross-sectional analysis of demographic and health survey data. PLoS medicine. 2021 Sep 16;18(9):e1003781\u003c/li\u003e\n\u003cli\u003eMahmood L, Flores-Barrantes P, Moreno LA, Manios Y, Gonzalez-Gil EM. The influence of parental dietary behaviors and practices on children\u0026rsquo;s eating habits. Nutrients. 2021 Mar 30;13(4):1138.\u003c/li\u003e\n\u003cli\u003eVilela S, Muresan I, Correia D, Severo M, Lopes C. The role of socioeconomic factors in food consumption of Portuguese children and adolescents: results from the National Food, Nutrition and Physical Activity Survey 2015\u0026ndash;2016. British Journal of Nutrition. 2020 Sep;124(6):591-601.\u003c/li\u003e\n\u003cli\u003ePenna AL, de Aquino CM, Pinheiro\u0026hellip; MSN. Impact of the COVID-19 pandemic on maternal mental health, early childhood development, and parental practices: a global scoping review. BMC public health. 2023.\u003c/li\u003e\n\u003cli\u003eShumba C, Maina R, Mbuthia G, Kimani R, Mbugua S, Shah S, Abubakar A, Luchters S, Shaibu S, Ndirangu E. Reorienting nurturing care for early childhood development during the COVID-19 pandemic in Kenya: a review. International Journal of Environmental Research and Public Health. 2020 Oct;17(19):7028.\u003c/li\u003e\n\u003cli\u003eJeong J, Pitchik HO, Fink G. Short-term, medium-term and long-term effects of early parenting interventions in low-and middle-income countries: a systematic review. BMJ Global Health. 2021.\u003c/li\u003e\n\u003cli\u003eSingh K, Kondal D, Mohan S, Jaganathan S, Deepa M, Venkateshmurthy NS, Jarhyan P, Anjana RM, Narayan KV, Mohan V, Tandon N. Health, psychosocial, and economic impacts of the COVID-19 pandemic on people with chronic conditions in India: a mixed methods study. BMC public health. 2021 Dec;21:1-5.\u003c/li\u003e\n\u003cli\u003eAdamopoulos I, Frantzana A, Syrou N. Climate crises associated with epidemiological, environmental, and ecosystem effects of a storm: Flooding, landslides, and damage to urban and rural areas (Extreme weather events of Storm Daniel in Thessaly, Greece). Med Sci Forum. 2024;25(1):7. https://doi.org/10.3390/msf2024025007\u003c/li\u003e\n\u003cli\u003eAdamopoulos I, Lamnisos D, Syrou N, Boustras G. Public health and work safety pilot study: Inspection of job risks, burn out syndrome and job satisfaction of public health inspectors in Greece. Safety Science. 2022.\u003c/li\u003e\n\u003cli\u003eAdamopoulos I, Syrou N, Lamnisos D, Boustras G., 2023. Cross-sectional nationwide study in occupational safety \u0026amp;amp; health: Inspection of job risks context, burn out syndrome and job satisfaction of public health Inspectors in the period of the COVID-19 pandemic in Greece. Saf Sci. 2023 Feb;158:105960.\u003c/li\u003e\n\u003cli\u003eAdamopoulos I, Syrou N, Lamnisos D, Dounias G. Public Health Inspectors Classification and Assessment of Environmental, Psychosocial, Organizational Risks and Workplace Hazards in the Context of the Global Climate Crisis. Preprints 2024, 2024120639. https://doi.org/10.20944/preprints202412.0639.v1\u003c/li\u003e\n\u003cli\u003eAdamopoulos I., Lamnisos D., Syrou N., Boustras G., Training Needs and Quality of Public Health Inspectors in Greece during the COVID-19 pandemic, European Journal of Public Health, Volume 32, Issue Supplement_3, October 2022, ckac131.373, https://doi.org/10.1093/eurpub/ckac131.373\u003c/li\u003e\n\u003cli\u003eAdamopoulos IP, Frantzana AA, Syrou NF. General practitioners, health inspectors, and occupational physicians\u0026rsquo; burnout syndrome during COVID-19 pandemic and job satisfaction: A systematic review. EUR J ENV PUBLIC HLT. 2024;8(3):em0160. https://doi.org/10.29333/ejeph/14997\u003c/li\u003e\n\u003cli\u003eAdamopoulos IP, Frantzana AA, Syrou NF. Medical educational study burnout and job satisfaction among general practitioners and occupational physicians during the COVID-19 epidemic. Electr J Med Educ Technol. 2024; 17(1):em2402. https://doi.org/10.29333/ejmets/14299\u003c/li\u003e\n\u003cli\u003eHegedűs M, Sziv\u0026oacute;s E, Adamopoulus I, D\u0026aacute;vid LD. (2024). Hospital integration to improve the chances of recovery for decubitus (pressure ulcer) patients through centralized procurement procedures. Journal of Infrastructure, Policy and Development. 8(10): 7273. https://doi.org/10.24294/jipd.v8i10.7273\u003c/li\u003e\n\u003cli\u003eThapa P, Adamopoulos IP, Sharma P, Lordkipanidze R. Public hygiene and the awareness of beauty parlor: A study of consumer perspective. EUR J ENV PUBLIC HLT. 2024;8(2):em0157. https://doi.org/10.29333/ejeph/14738\u003c/li\u003e\n\u003cli\u003eAli G, Mijwil MM, Adamopoulos I, Buruga BA, G\u0026ouml;k M, Sallam M. Harnessing the Potential of Artificial Intelligence in Managing Viral Hepatitis. Mesopotamian Journal of Big Data [Internet]. 2024 Aug. 15 [cited 2024 Dec. 29];2024:128-63. https://mesopotamian.press/journals/index.php/bigdata/article/view/484\u003c/li\u003e\n\u003cli\u003eKhan, A. J. J.; Yar, S.; Fayyaz, S.; Adamopoulos, I.; Syrou, N.; Jahangir, A. From Pressure to Performance, and Health Risks Control: Occupational Stress Management and Employee Engagement in Higher Education. \u003cem\u003ePreprints\u003c/em\u003e \u003cstrong\u003e2024\u003c/strong\u003e, 2024121329. https://doi.org/10.20944/preprints202412.1329.v1\u003c/li\u003e\n\u003cli\u003eAdamopoulos, I.; Syrou, N.; Lamnisos, D.; Dounias, G. Public Health Inspectors Classification and Assessment of Environmental, Psychosocial, Organizational Risks and Workplace Hazards in the Context of the Global Climate Crisis. \u003cem\u003ePreprints\u003c/em\u003e \u003cstrong\u003e2024\u003c/strong\u003e, 2024120639. https://doi.org/10.20944/preprints202412.0639.v1\u003c/li\u003e\n\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":"Cognitive development, Academic nurturance, Preschool children","lastPublishedDoi":"10.21203/rs.3.rs-5760180/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5760180/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThe importance of the impact of public health and social determinants on maternal factors for academic nurturing and the cognitive development of preschool children for family-based and institutional nutrition interventions reveals a concerning prevalence of suboptimal behaviours across all countries. Early intervention strategies to cultivate healthy habits, particularly in preschool and childcare settings, highlight the importance of addressing socioeconomic barriers that prevent families from adopting health-promoting behaviours.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eCreating engaging learning experiences, providing emotional warmth, and fostering social interactions are essential for nurturing children's cognitive development. This study explored the factors influencing cognitive development in 389 preschool children (aged 3-5) in Rupandehi District, Nepal. A cross-sectional survey design employing multistage random sampling was used to collect socioeconomic and demographic data, alongside caregivers' academic nurturance practices, through validated instruments and interviews. Data analysis was conducted via IBM SPSS version 26, with significance set at p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003eResults: Forty-eight percent of thefamilies were economically disadvantaged, and only 15.5% of the caregivers exhibited high levels of academic nurturance. While academic nurturance itself did not have a direct effect on cognitive development, the unadjusted analysis revealedpositive associations between cognitive development and wealth status, maternal education, family structure, caste/ethnicity and the age of children. Multivariate analysis confirmed that family type, caste/ethnicity and the age of the childwere key factors in predicting cognitive development. The economic status predictor of cognitive development (β = -0.254, p = 0.000), negative association with lower economic status, and poorer cognitive development academic nurturance were added as predictors (β = -0.003, p = 0.954), accounting for 8.0% of the variance in cognitive development (R² = 8.0%), with an F-statistic of 4.667 (p = 0.000).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eAddressing these socioeconomic determinants could lead to significant improvements in children's cognitive outcomes. Finally, the study emphasizes the complex link between maternal characteristics, social determinants, and treatments in determining preschool children's caring and cognitive development. The findings highlight the need for targeted public health interventions that address these interconnected elements, emphasizing the importance of fostering social determinants and public health principles in increasing maternal involvement, and reducing socioeconomic barriers to optimal child development.\u003c/p\u003e","manuscriptTitle":"The Impact of Public Health and Social Determinants on Maternal Factors for Academic Nurturance and the Cognitive Development of Preschool Children: A Cross-sectional Research Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-22 07:49:04","doi":"10.21203/rs.3.rs-5760180/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":"3156b1d4-af95-4d6b-bbc9-b51868b2ecff","owner":[],"postedDate":"January 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-06T09:08:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-22 07:49:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5760180","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5760180","identity":"rs-5760180","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}