Providing an enabling nurturing care environment for early childhood development (ECD) that cuts across the five domains of the Nurturing Care Framework (i.e., good health, adequate nutrition, opportunities for early learning, security and safety and responsive caregiving) has become a global priority. Brazil is home to approximately 18.5 million children under 5 years of age, of which 13% are at risk of poor development due to socio‐economic inequalities. We explored whether the Early Childhood Friendly Municipal Index (IMAPI) can detect inequities in nurturing care ECD environments across the 5570 Brazilian municipalities. We examined the validity of the IMAPI scores and conducted descriptive analyses for assessing sociodemographic inequities by nurturing care domains and between and within regions. The strong correlations between school achievement (positive) and socially vulnerable children (negative) confirmed the IMAPI as a multidimensional nurturing care indicator. Low IMAPI scores were more frequent in the North (72.7%) and Northeast (63.3%) regions and in small (47.7%) and medium (43.3%) size municipalities. Conversely, high IMAPI scores were more frequent in the more prosperous South (52.9%) and Southeast (41.2%) regions and in metropolitan areas (41.2%). The security and safety domain had the lowest mean differences (MDs) among Brazilian regions (MD = 5) and population size (MD = 3). Between‐region analyses confirmed inequities between the North/Northeast and South/Southeast. The biggest within‐region inequity gaps were found in the Northeast (from −22 to 15) and the North (−21 to 19). The IMAPI distinguished the nurturing care ECD environments across Brazilian municipalities and can inform equitable and intersectoral multilevel decision making.

Objective:To analyse usual intakes of energy, macronutrients and micronutrients, and their percentage of inadequacy, in a Brazilian population at severe food insecurity (SFI) risk, determined from a predictive model using two national databases.Design:Cross-sectional study. Our study used a statistical model to predict SFI using the 2009 National Sample Household Survey, where the Brazilian Food Insecurity Scale measured SFI.Setting:Brazil.Participants:The model was applied in a probabilistic sample of 34 003 Brazilians aged 10 years or older that participated in a national dietary survey during 2008–2009. The application of the model generated the probability of each individual being in SFI. The probability of SFI was grouped into quartiles (first quartile with the lowest SFI risk, fourth quartile with highest probability of SFI risk).Results:The intakes of macro- and micronutrients were associated with SFI. The amount of energy and nutrients in the diet tended to be lower among individuals in the fourth quartile, with highest probability of SFI. The average intake of all studied minerals (Ca, Fe, Na, Mg) was less in individuals in the fourth quartile. Only Na presented a higher percentage of inadequacy in the first quartile, the one with a lower chance of SFI.Conclusions:The food intake of the Brazilian population at higher SFI risk is characterized by energy reduction, reduced consumption of macronutrients and high prevalence of inadequate micronutrient intakes, as well as a lower mean intakes, when compared with the first quartile with the lowest SFI risk.

Selecting indicators to monitor nurturing care (NC) environments that support decision‐making and guide the implementation of integrated early childhood development (ECD) programmes has become a priority globally. Several population‐based approaches have been attempted to create a set of indicators or a composite index methodology to measure the NC environment using existing secondary data. However, they have not been systematized. Our scoping review aimed to analyse the population‐based approaches for monitoring the domains of the NC (e.g. good health, adequate nutrition, responsive caregiving, security and safety, and opportunities for early learning). ECD experts, peer‐reviewed, and grey literature were systematically searched with no year or language restrictions. Data extraction used a standard predefined protocol. Thirty‐two population‐based approaches were identified. Most approaches were composed of a set of indicators (53.1%, n = 17) versus composite indexes (46.9%, n = 15) and had the country as their unit of analysis (68.8%, n = 22). Twenty‐seven approaches were applied in middle‐income countries (84.4%) and thirteen in low‐income countries (40.6%). Four approaches were guided by the NC framework (12.5%), and 56.3% (n = 18) did not include any indicator representing responsive caregiving. NC indicators (n = 867) were sorted into 100 groups of indicators. Twenty of the 32 approaches had some kind of methodological validation (62.5%). We identified six methodological challenges to build a population‐based approach. Standardized methods for selecting and validating indicators, and coordinated efforts to share findings/data with stakeholders should be prioritized. Given the great variability in methods and indicators used to measure NC environments, valid approaches should be flexible to work well across different contexts.

Diferenças no consumo alimentar de adolescentes na Região Centro-Oeste e outras regiões brasileiras Differences in dietary intake of adolescents in the Midwest and other Brazilian regions Resumo Os objetivos foram analisar a frequência de consumo de alimentos saudáveis e não saudáveis e diferenças no conhecimento e consumo de alimentos típicos brasileiros dos adolescentes da Região Centro-Oeste, comparando-a às demais regiões. Estudo transversal, desenvolvido com 10.514 adolescentes, com 13 e 14 anos de idade e que responderam ao questionário online. Os dados foram analisados por meio do programa estatístico SPSS, utilizando análise univariada para estimar frequência do consumo alimentar e teste de associação qui-quadrado para variáveis categóricas como conhecimento e consumo de alimentos nacionais. O nível de significância considerado foi de 5%. Verificou-se alta frequência de consumo de alimentos marcadores de uma alimentação não saudável e baixa frequência de consumo de alimentos marcadores de uma alimentação saudável. Os adolescentes da Região Centro-Oeste apresentaram maior frequência de consumo de feijões e hortaliças e menor frequência de consumo de salgados fritos e biscoitos, com diferença significativa (p<0,001) para as outras regiões. Os alimentos nacionais foram amplamente conhecidos, com exceção para o cará, que apenas 32,1% dos adolescentes da Região Centro-Oeste relataram conhecer. O consumo desses alimentos típicos foi bem variado e diferiu significativamente das outras regiões para cará, dobradinha, mandioca, arroz carreteiro, canjica e uva. Evidencia-se a necessidade de investigações mais específicas da presença dos alimentos nacionais no ambiente habitacional e de convívio e investigações no consumo que contemplem a realização da Segurança Alimentar e Nutricional.

The Brazilian Early Childhood Friendly Municipal Index (IMAPI) is a population‐based approach to monitor the nurturing care environment for early childhood development (ECD) using routine information system data. It is unknown whether IMAPI can be applied to document metropolitan urban territorial differences in nurturing care environments. We used Brasilia, Brazil's capital with a large metropolitan population of 2,881,854 inhabitants divided into 31 districts, as a case study to examine whether disaggregation of nurturing care data can inform a more equitable prioritization for ECD in metropolitan areas. IMAPI scores were estimated at the municipal level (IMAPI‐M, 31 indicators) and at the district level (IMAPI‐D, 29 indicators). We developed a quantitative prioritization process for indicators in each IMAPI analysis, and those selected were jointly mapped in the socioecological model for the role of indicators in relation to the enabling environment for nurturing care. Out of 28 common nurturing care indicators across IMAPI analysis, only four were prioritized in both analyses: one from the Adequate nutrition, two from the Opportunities for early learning, and one from the Responsive caregiving domains. These four indicators were mapped as enabling policies, supportive services, and caregivers’ capabilities (socioecological model) and Effort, Coverage, and Quality (indicator's role). In conclusion, the different levels of nurturing care data disaggregation in the IMAPI can better inform decision‐making than each one individually, especially in metropolitan areas where municipalities and districts within metropolitan areas have relative decision‐making autonomy.