Development and standardization of a nutrition knowledge test for rural women in Uttar Pradesh, India: item analysis and socioeconomic associations

Introduction Context-specific, standardized tools for assessing nutrition knowledge among rural women in Uttar Pradesh are limited. This study aimed to develop and standardize a nutrition knowledge test and examine associations between knowledge scores and selected independent varaibles. Methods An ex post facto research design was employed among 180 rural women from 12 villages in Prayagraj and Saharanpur districts, Uttar Pradesh, India. An initial pool of 32 items was developed through literature review, expert consultation, and content validation and pre-tested among 40 women from a non-sampling area. Item analysis using difficulty index, discrimination index, and point-biserial correlation retained 24 items. Reliability was satisfactory (Cronbach’s alpha = 0.850; Spearman–Brown coefficient = 0.862; Guttman split-half coefficient = 0.822). Pearson’s correlation and multiple regression analyses examined associations with eight variables: age, education, family size, landholding, annual income, mass media exposure, social participation, and capacity building. Results Most respondents had medium knowledge (62.78%), followed by low (21.67%) and high knowledge (15.56%). The mean knowledge score was 61.50 (SD = 17.83). Knowledge was positively correlated with education ( r = 0.893), annual income ( r = 0.878), mass media exposure ( r = 0.535), age ( r = 0.528), landholding ( r = 0.476), capacity building ( r = 0.430), and social participation ( r = 0.396; all p < 0.01). Family size showed a negative, non-significant correlation ( r = −0.127, p = 0.089). In regression analysis, age, education, annual income, social participation, and capacity building had significant positive coefficients, whereas landholding had a significant negative coefficient. Family size and mass media exposure were non-significant. The model explained 87.1% of the variance ( R 2 = 0.871; adjusted R 2 = 0.865). Conclusion The reliable 24-item test identified knowledge gaps concerning micronutrients, protein sources, and specific nutrition concepts. It may support targeted nutrition education and extension interventions. Further validation across diverse geographic and sociocultural settings is recommended.

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Journal
Frontiers in Sustainable Food Systems
Published
2026-11-04
DOI
https://doi.org/10.3389/fsufs.2026.1880768
Primary Topic
Health Education and Validation
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article
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article

Development and standardization of a nutrition knowledge test for rural women in Uttar Pradesh, India: item analysis and socioeconomic associations

Sayak Saha, Sweta Kumari, Sudhanand Prasad Lal, Vicky Yadav et al.
Frontiers in Sustainable Food Systems
Health Education and Validation
article

Development and standardization of a nutrition knowledge test for rural women in Uttar Pradesh, India: item analysis and socioeconomic associations

Sayak Saha, Sweta Kumari, Sudhanand Prasad Lal, Vicky Yadav, Prashish Singh, Alok Kumar, Indrajit Mandal, Nirjharini Sahoo, Priyanka Roy, Swati Kumari, Puspanjali Dalei, Rashika Mahajan, Nitin Meena, Rohit Maurya, Vivek Kumar, Raushan Kumar, Kshitij Kashyap, Saloni Kumari
article en

Abstract

Introduction Context-specific, standardized tools for assessing nutrition knowledge among rural women in Uttar Pradesh are limited. This study aimed to develop and standardize a nutrition knowledge test and examine associations between knowledge scores and selected independent varaibles. Methods An ex post facto research design was employed among 180 rural women from 12 villages in Prayagraj and Saharanpur districts, Uttar Pradesh, India. An initial pool of 32 items was developed through literature review, expert consultation, and content validation and pre-tested among 40 women from a non-sampling area. Item analysis using difficulty index, discrimination index, and point-biserial correlation retained 24 items. Reliability was satisfactory (Cronbach’s alpha = 0.850; Spearman–Brown coefficient = 0.862; Guttman split-half coefficient = 0.822). Pearson’s correlation and multiple regression analyses examined associations with eight variables: age, education, family size, landholding, annual income, mass media exposure, social participation, and capacity building. Results Most respondents had medium knowledge (62.78%), followed by low (21.67%) and high knowledge (15.56%). The mean knowledge score was 61.50 (SD = 17.83). Knowledge was positively correlated with education ( r = 0.893), annual income ( r = 0.878), mass media exposure ( r = 0.535), age ( r = 0.528), landholding ( r = 0.476), capacity building ( r = 0.430), and social participation ( r = 0.396; all p < 0.01). Family size showed a negative, non-significant correlation ( r = −0.127, p = 0.089). In regression analysis, age, education, annual income, social participation, and capacity building had significant positive coefficients, whereas landholding had a significant negative coefficient. Family size and mass media exposure were non-significant. The model explained 87.1% of the variance ( R 2 = 0.871; adjusted R 2 = 0.865). Conclusion The reliable 24-item test identified knowledge gaps concerning micronutrients, protein sources, and specific nutrition concepts. It may support targeted nutrition education and extension interventions. Further validation across diverse geographic and sociocultural settings is recommended.

Frontiers in Sustainable Food SystemsVol. 10
DAV University (IN), National Dairy Research Institute (IN), Dr. Rajendra Prasad Central Agriculture University (IN), Bihar Agricultural University (IN), Sardar Vallabhbhai Patel University of Agriculture & Technology (IN), Central Agricultural University (IN), Banaras Hindu University (IN)
Openalex Percentile: Top 8%
Health Education and Validation
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