Spanish adaptation and validation of the Child Food Security Survey Module (CFSSM-S)

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© The Authors 2018Â. Objective The present study aimed to assess the: (i) internal structure of the Spanish Child Food Security Survey Module (CFSSM-S) with exploratory and confirmatory factor analysis (EFA and CFA); (ii) measurement invariance by gender, grade, weight status, socio-economic status (SES) and family affluence; and (iii) relationships with these external variables.Design A cross-sectional study was conducted. The CFSSM-S and other tools were employed to assess food insecurity, weight status, SES and family affluence, respectively.Setting A secondary school (grades 7-10) in the city of Terrassa in Catalonia, Spain.Subjects Participants included adolescent boys and girls (n 426) aged 12-17 years.Results The cross-validation design with EFA and CFA captured a single factor, 'food insecurity'. The goodness-of-fit for the one-factor model with CFA (root-mean-square error of approximation=0·038, comparative fit index=0·984, Tucker-Lewis index=0·979) and internal consistency (ω=0·95) were excellent. The measurement invariance indicated that CFSSM-S could be used across genders, grades, weight status, SES and family affluence. Only mean differences for SES and family affluence were found which showed a linear trend, indicating higher CFSSM-S scores for participants with lower SES and family affluence. Of participants, 1·9 % experienced very low food security, 16·4 % low food security and 81·7 % were food secure.Conclusions The CFSSM-S is the first validated instrument to assess food insecurity with psychometric guarantees in Spanish adolescents. Researchers and health practitioners in Spain could use this self-reported questionnaire to gain more information about adolescent health in relation to food insecurity.
Original languageEnglish
Pages (from-to)2753-2761
Number of pages9
JournalPublic Health Nutrition
Issue number15
Early online date12 Jul 2018
Publication statusPublished - 1 Oct 2018


  • Adolescents
  • Confirmatory factor analysis
  • Cross-validation
  • Food insecurity
  • Measurement invariance


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