Childhood malnutrition and maternal nutritional anemia remain two of the most pressing yet under-recognized public health challenges in India, collectively contributing to a vicious cycle of poor health outcomes across generations. Despite steady improvements in health service coverage, India continues to account for a disproportionately high share of the global burden of stunting, wasting, and underweight among children under five, alongside widespread anemia in women of reproductive age [1-3]. According to the National Family Health Survey–5 (2019–21), 35.5% of Indian children under five are stunted, 19.3% are wasted, and 32.1% are underweight, while over 57% of women aged 15–49 years suffer from some degree of anemia. These conditions are not isolated; maternal undernutrition increases the risk of low birth weight, impaired child growth, and developmental delays, perpetuating an intergenerational cycle of malnutrition often referred to as “hidden hunger [4-7].”                

Shimla, the capital of Himachal Pradesh, presents a unique epidemiological context. While the district benefits from relatively high literacy rates and established primary health infrastructure, geographical barriers, socio-economic inequalities, and entrenched dietary misconceptions continue to limit optimal maternal and child nutrition practices. Nutritional challenges are compounded by cultural feeding norms, seasonal food availability, and varying access to antenatal and child health services in rural versus urban settings. Importantly, misconceptions such as withholding colostrum, early introduction of non-milk feeds, inadequate meal frequency for young children, and beliefs that anemia affects only the poor persist even among literate populations, undermining programmatic gains [8-12].

The Government of India’s flagship initiatives such as Poshan Abhiyaan, Anemia Mukt Bharat, and the Integrated Child Development Services (ICDS) advocate for early and exclusive breastfeeding, timely initiation of complementary feeding, dietary diversity, regular growth monitoring, iron-folic acid (IFA) supplementation, and deworming. However, their success hinges on the depth and accuracy of community-level knowledge, as well as the dismantling of harmful myths and practices. Periodic, localized knowledge assessments are therefore critical to guide targeted behavior change communication (BCC) strategies [13-18].

This study aims to assess the awareness and misconceptions regarding childhood malnutrition and maternal nutritional anemia among women in Shimla district, and to identify socio-demographic and maternal health determinants associated with good overall knowledge. By highlighting knowledge gaps within a setting of relatively high literacy, this research seeks to inform more nuanced, context-specific interventions that can accelerate progress toward the Sustainable Development Goals (SDGs) of ending all forms of malnutrition by 2030.

Study Design and Setting

This investigation employed a community-based, descriptive cross-sectional design to assess knowledge levels and misconceptions regarding childhood malnutrition and maternal nutritional anemia among women in Shimla district, Himachal Pradesh, India. The study was conducted between March and May 2025. Shimla, a high-altitude district with a mix of rural and urban settlements, offers relatively high literacy rates compared to national averages, yet exhibits nutritional disparities influenced by terrain, seasonal food accessibility, and socio-cultural feeding norms. The design was chosen to provide a snapshot of the prevailing knowledge landscape, allowing identification of critical gaps to inform targeted interventions.

Study Population and Eligibility Criteria

The study population comprised women aged ≥18 years, either currently pregnant or mothers of at least one child aged 0–59 months, who had been permanent residents of Shimla for a minimum of six months. Exclusion criteria included healthcare professionals (to avoid overestimation of knowledge), individuals engaged in nutrition education programs, and those unwilling or unable to provide informed consent.

Sample Size Determination and Sampling Strategy

The minimum required sample size (n = 384) was calculated using the single population proportion formula:

n=Z²×p(1−p)/d²

where, Z = 1.96 for 95% confidence, p = 0.5 (assumed prevalence of good knowledge to maximize sample size), and d = 0.05 (margin of error). To account for potential incomplete responses, the sample size was rounded to 400. A purposive-cum-snowball sampling technique was adopted to ensure balanced representation from both rural and urban areas. Key community intermediaries, including Accredited Social Health Activists (ASHAs) and Anganwadi workers, facilitated outreach to eligible participants.

Development of the Data Collection Tool

A structured, bilingual (English and Hindi) questionnaire was developed based on World Health Organization (WHO), United Nations Children’s Fund (UNICEF), and Anemia Mukt Bharat operational guidelines. It was organized into four sections:

• Socio-demographic and maternal health profile – age, residence type, education, occupation, household income, parity, antenatal care (ANC) visits, current trimester, BMI, and MUAC category.

• Childhood malnutrition knowledge – 20 multiple-choice questions assessing understanding of definitions (stunting, wasting, underweight), key signs and symptoms, feeding practices, dietary diversity, hygiene, and prevention strategies.

• Maternal nutritional anemia knowledge – 20 multiple-choice questions covering definition, causes, prevention, supplementation, dietary sources, and common myths.

• Self-reported anthropometric data – height, weight, and MUAC.

• Each correct answer was scored “1” and each incorrect answer “0,” yielding domain-specific scores (0–20 each) and an overall score (0–40). Scores were classified as: very good (16–20), good (12–15), fair (8–11), and poor (0–7) for each domain, with overall knowledge ≥12 considered “good” for regression analysis.

Pilot Testing and Validation

The draft questionnaire was pre-tested on 30 women (excluded from the main study) to assess clarity, comprehensibility, and cultural appropriateness. Minor modifications were made to simplify technical terms and ensure contextual relevance. Internal consistency was assessed using Cronbach’s alpha, yielding reliability coefficients of 0.84 for the malnutrition section and 0.81 for the anemia section, indicating good reliability.

Data Collection Procedure

Data were collected digitally using Google Forms. The survey link was disseminated via WhatsApp, Facebook groups, and local self-help networks. In rural areas with limited internet access, ASHAs and Anganwadi workers assisted by providing smartphones or tablets and guiding participants through the questionnaire in person while ensuring privacy. The form was designed to require completion of all items before submission, minimizing missing data.

Data Management and Statistical Analysis

Responses were exported from Google Forms to Microsoft Excel and subsequently imported into IBM SPSS Statistics version 25 for analysis. Descriptive statistics (frequencies, percentages, means, and standard deviations) summarized participant characteristics and response distributions. Bivariate associations between knowledge categories and socio-demographic/maternal health variables were examined using Chi-square tests. Variables with p < 0.05 in bivariate analysis were entered into a multivariate logistic regression model to identify independent predictors of good overall knowledge. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were calculated, and statistical significance was set at p < 0.05.

Ethical Considerations

Electronic informed consent was obtained from all participants prior to data collection. Participation was voluntary, and anonymity was maintained by avoiding the collection of personal identifiers. Data were stored securely with restricted access to the principal investigator only.

Table 1 presents the socio-demographic and maternal health profile of the 400 women surveyed. The majority of participants were in the 25–29 years age group (31.0%), followed closely by those aged 30–34 years (27.5%), with a balanced distribution between rural (50.0%) and urban (50.0%) residents. Education levels varied considerably while 31.0% had completed graduation or higher, a notable 10.5% had no formal education. Most women were homemakers (58.0%), and one-third (34.5%) belonged to households earning ₹10,000–20,000 per month. Over half (51.5%) were multiparous, and nearly two-thirds (63.0%) had attended at least four ANC visits in their most recent pregnancy. Nutritional status indicators showed that 24.0% were underweight by BMI, and 21.0% had low MUAC (<23 cm), signaling a substantial proportion at nutritional risk despite the predominance of women with normal BMI (57.5%). These findings highlight both diversity and vulnerability in the study population.

Table 1: Socio-Demographic and Maternal Health Characteristics of Participants (n = 400)

Table 2 summarizes participant responses to awareness and misconception questions on childhood malnutrition. While knowledge was strong in areas such as exclusive breastfeeding (83.0%), timely initiation of breastfeeding (77.5%), and the role of hygiene in preventing undernutrition (80.0%), gaps persisted in recognizing anthropometric indicators only 63.5% correctly identified MUAC cut-offs, and just 65.5% recognized bilateral pitting edema as a danger sign. Misconceptions were also evident, with 53.5% believing malnutrition is only present when a child appears visibly thin. Dietary knowledge was variable; while 79.5% knew the correct age for starting complementary feeding, fewer (66.5%) could identify optimal iron-rich foods for children. These patterns suggest that while general awareness of infant and young child feeding practices is encouraging, technical knowledge of diagnostic signs and micronutrient-rich diets remains incomplete.

Table 2: Awareness and Misconception Questions on Childhood Malnutrition Among Women in Shimla (n = 400)

Table 3 reports awareness and misconceptions regarding maternal nutritional anemia. Although 80.5% correctly identified iron deficiency as the leading cause, only   59.5%    could    accurately     define     anemia    inpregnancy per trimester-specific hemoglobin cut-offs. Nutritional knowledge was encouraging, with high recognition of folic acid’s role in preventing neural tube defects (79.0%) and the importance of green leafy vegetables, pulses, and animal-source foods for iron (69.5%). However, misconceptions and practice-related gaps persisted only 64.0% knew vitamin C enhances iron absorption, and 68.5% recognized tea/coffee as inhibitors. Preventive behaviors were variably understood; while 73.0% were aware of daily IFA requirements during pregnancy, fewer (63.0%) knew the correct deworming schedule. Importantly, just over half (52.5%) rejected the misconception that anemia affects only poor women, reflecting the persistence of socio-cultural bias.

Table 3: Awareness and Misconception Questions on Maternal Nutritional Anemia Among Women in Shimla (n = 400)

Table 4 classifies knowledge levels for both childhood malnutrition and maternal anemia. For malnutrition, 31.5% achieved “very good” scores (16–20/20), 41.0% “good,” and 27.5% fell into fair or poor categories. Maternal anemia knowledge was slightly lower, with 29.5% achieving “very good” and 47.0% scoring fair or poor. When combined into an overall knowledge score, one-third (33.0%) reached “very good,” 39.5% “good,” and 27.5% remained in the fair/poor range. These results indicate that while a substantial proportion of women possess adequate to high knowledge, a significant knowledge deficit persists among nearly one in four respondents representing a critical target group for future educational interventions.

Table 4: Knowledge Score Classification Among Participants (n = 400)

Table 5 examines the association between overall knowledge category and key socio-demographic and maternal health variables. Educational attainment emerged as a strong differentiator over half (51.6%) of graduate-level women achieved “very good” knowledge compared to only 9.5% of those without formal education (p<0.001). Occupation and household income also showed clear gradients: service/professional women and those earning >₹30,000/month had the highest proportions with “very good” knowledge (59.1% and 81.3%, respectively), while unemployed and lowest-income women were overrepresented in the fair/poor categories (p<0.001). Antenatal care utilization was particularly important; women with ≥4 ANC visits had more than twice the proportion of “very good” knowledge compared to those with fewer visits (42.1% vs. 17.6%, p<0.001). Nutritional status also correlated with knowledge normal BMI and adequate MUAC were both associated with higher scores (p=0.004 and p=0.023, respectively). Interestingly, age, parity, and trimester did not significantly influence knowledge, suggesting that structural and behavioral factors may outweigh biological ones in shaping awareness.

Table 5: Association Between Overall Knowledge Category and Socio-Demographic/Maternal Health Variables (n = 400)

Table 6 presents the multivariate logistic regression analysis identifying independent predictors of good overall knowledge on childhood malnutrition and maternal nutritional anemia. After adjusting for confounders, higher education retained a strong positive association graduates and above were over five times more likely to have good knowledge (AOR 5.14, 95% CI 2.49–10.62, p<0.001), with secondary education also significant (AOR 3.12, p<0.001). Service/professional occupations (AOR 2.86, p=0.004) and higher household income (>₹30,000: AOR 3.94, p<0.001) independently predicted good knowledge, underscoring socio-economic advantage as a key driver. Health service utilization emerged as a major modifiable factorwomen with ≥4 ANC visits had over twice the odds of good knowledge (AOR 2.45, p<0.001). Adequate MUAC (≥23 cm) and normal BMI also remained significant predictors, reflecting the interplay between nutritional status and health awareness. Residence type, parity, and age were not significant after adjustment, suggesting that targeted educational and antenatal interventions could bridge the knowledge gap irrespective of demographic profile.

Table 6: Multivariate Logistic Regression Analysis of Factors Associated with Good Overall Knowledge on Childhood Malnutrition and Maternal Nutritional Anemia (n = 400)

This study provides a comprehensive snapshot of community-level awareness and misconceptions regarding childhood malnutrition and maternal nutritional anemia among women in Shimla district, revealing encouraging levels of basic knowledge alongside persistent technical gaps and socio-cultural myths. With over 70% of respondents achieving “good” or “very good” overall knowledge, the findings suggest that core health messages particularly those related to breastfeeding practices, complementary feeding, and hygiene are reaching much of the population. However, the substantial proportion of women with only fair or poor knowledge (27.5%) indicates that a significant minority remains at risk of inadequate health behaviors, potentially undermining maternal and child nutrition outcomes.

The strength of awareness in this sample especially on timely initiation and exclusivity of breastfeeding (77.5% and 83.0%, respectively) compares favorably with national NFHS-5 figures, where only 41.8% of Indian infants are breastfed within one hour of birth and 63.7% exclusively for six months. This likely reflects Himachal Pradesh’s relatively high literacy, established ICDS infrastructure, and proactive ASHA/Anganwadi worker engagement. Yet, critical gaps in technical understanding, such as recognition of anthropometric indicators (MUAC cut-offs known by only 63.5%) and early clinical signs (bilateral pitting edema identified by 65.5%), mirror findings from other Indian states and global settings, where anthropometric literacy is often limited to trained health workers. This limitation is particularly concerning because mothers are often the first to detect signs of nutritional compromise if they are unaware of early indicators, opportunities for timely referral and intervention may be missed.

Maternal nutritional anemia knowledge followed a similar pattern: strong awareness of causes and consequences (iron deficiency cited by 80.5%; adverse pregnancy outcomes recognized by 82.0%) coexisted with practical knowledge gaps. For example, only 64.0% knew that vitamin C enhances iron absorption, and just 63.0% correctly identified the national deworming schedule during pregnancy. The persistence of the misconception that anemia affects only poor women (47.5% believed this) is consistent with earlier qualitative research in North India, where anemia is often socially “invisible” in wealthier households, reducing perceived susceptibility and care-seeking.

Multivariate analysis underscored the central role of structural determinants. Higher educational attainment, professional occupation, and higher household income independently predicted good knowledge findings consistent with national and international literature demonstrating the socio-economic gradient in health literacy. More importantly, ≥4 ANC visits emerged as a significant and modifiable predictor, increasing the odds of good knowledge by 2.45 times. This reinforces WHO and Government of India recommendations that ANC visits are not only for clinical monitoring but also for targeted nutrition counseling. Women with adequate MUAC and normal BMI also demonstrated higher knowledge, suggesting a positive feedback loop where better nutrition and better awareness reinforce each other.

The absence of significant associations with age, parity, or residence type after adjustment is noteworthy. It suggests that geographic access alone may be less of a barrier in Shimla than in more remote districts, likely due to improved mobile and digital outreach reflected in the feasibility of Google Form–based data collection in this study. However, the fact that one in five women still had low MUAC indicates that knowledge does not always translate into practice, possibly due to entrenched food habits, economic constraints, or intra-household food distribution patterns.

From a public health perspective, these findings carry several implications. First, targeted behavior change communication (BCC) must move beyond generic breastfeeding and hygiene messages to emphasize technical skills such as recognizing anthropometric danger signs, understanding nutrient enhancers/inhibitors, and following preventive supplementation schedules. Second, ANC visits remain an underutilized opportunity for intensive counseling on both maternal and child nutrition; strengthening this counseling component, especially for women with lower education or income, could yield significant gains. Third, myths such as “anemia is only for the poor” require culturally sensitive myth-busting, ideally through trusted local channels such as Anganwadi centers, women’s self-help groups, and school-based mother’s meetings.

Comparing with other Indian studies, the dual burden of moderate knowledge levels and persistent misconceptions in Shimla parallels findings from other  states, where literacy is high but nutritional outcomes are not uniformly optimal. Internationally, similar patterns have been observed in previous studies, where women had strong general nutrition awareness but lacked specific, actionable knowledge, leading to suboptimal feeding and supplementation practices. These parallels highlight that while knowledge is a necessary condition for behavior change, it is not sufficient economic empowerment, food environment improvements, and supportive family/community norms are equally critical [13-18].

Overall, this study strengthens the evidence that bridging the last mile in maternal and child nutrition requires precision-targeted knowledge transfer, reinforced by structural support. In a setting like Shimla, where digital literacy is growing, hybrid strategies combining in-person counseling with app-based reminders, interactive videos, and WhatsApp–based myth-busting may be particularly effective. The findings also validate the utility of rapid, low-cost, Google Form–based knowledge assessments as a monitoring tool for local program planning.

Strengths and Limitations

A major strength of this study lies in its large, balanced rural–urban sample and comprehensive coverage of both maternal anemia and child malnutrition knowledge within the same population, enabling a holistic view of interlinked nutrition issues. The use of a validated, bilingual questionnaire, pre-tested for cultural appropriateness, ensured data reliability and contextual relevance. Digital data collection via Google Forms minimized missing responses and facilitated real-time quality checks. However, limitations include the purposive–snowball sampling approach, which, while necessary for targeted recruitment, may limit generalizability beyond similar socio-demographic settings. Self-reported anthropometric and socio-economic data may be subject to recall or social desirability bias. Furthermore, the cross-sectional design precludes causal inference between knowledge and nutritional status. Despite these constraints, the findings provide actionable insights for local program planning and nutrition education strategies.

This study demonstrates that while the majority of women in Shimla district possess good to very good knowledge regarding childhood malnutrition and maternal nutritional anemia, substantial gaps persist in the recognition of technical indicators, preventive supplementation schedules, and the role of dietary enhancers and inhibitors. Socio-economic advantage, higher education, professional employment, and optimal antenatal care utilization emerged as key determinants of better knowledge, highlighting both structural and behavioral levers for intervention. Importantly, persistent misconceptions such as anemia being a disease of the poor indicate that awareness campaigns must go beyond information provision to actively dismantle harmful myths. Strengthening nutrition counseling during antenatal visits, promoting community-level anthropometric literacy, and leveraging hybrid outreach methods can bridge the last-mile gap in maternal and child nutrition awareness. Addressing these knowledge deficits is critical to breaking the intergenerational cycle of “hidden hunger” and accelerating progress toward SDG targets in Himachal Pradesh and similar contexts.

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