Global Dietary Surveillance: Data Gaps and Challenges

Micha, Renata; Coates, Jennifer; Leclercq, Catherine; Charrondière, U. Ruth; Mozaffarian, Dariush

doi:10.1177/0379572117752986

Cited by 74 publications

(81 citation statements)

References 124 publications

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“…These findings will facilitate future use of household consumption estimates by scientists and policy makers to more accurately estimate dietary intakes, when household questionnaires are the only source of dietary data. Leveraging national household surveys already in place to routinely collect individual-level dietary data, even in a reasonably powered subset of the population, would be of great value to LMIC settings [ 83 ]. Relative to its importance as a global risk factor for health, disparities, and sustainability, national investment in the routine collection of individual-level dietary data should be prioritized for accurate diet assessment, burden analyses and policy implementation.…”

Section: Discussionmentioning

confidence: 99%

Assessing dietary intakes from household budget surveys: A national analysis in Bangladesh

et al. 2018

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BackgroundAccurate national information on dietary intakes, including heterogeneity among individuals, is critical to inform health implications and policy priorities. In low- and middle-income countries, household expenditure surveys constitute the major source of food data, but with uncertain validity for individual-level intakes.ObjectiveTo investigate how individualized dietary consumption estimated from household survey data compared with individual-level 24-hr dietary recalls (24hR); and to assess potential heterogeneity by method for individualizing household intakes, dietary indicator, and individual characteristics (age, sex, education, religion, household income).MethodsWe evaluated data from the 2011–2012 Bangladesh Household Integrated Survey (BIHS), which included household-level consumption data (5,503 households) and individual-level dietary data based on 24hR from these households (22,173 participants). Household and 24hR estimates were standardized and harmonized for 33 dietary indicators, including 9 food groups, total energy, 8 macronutrients, and 15 micronutrients. Individual consumption was estimated from household data using two approaches, the Adult Male Equivalent (AME) and per capita (PC) approach. For each dietary indicator, differences in household vs. individual mean estimates were evaluated overall and by strata of individual characteristics, using Spearman’s correlations and univariate and multivariate linear regression models.ResultsIndividualized household estimates overestimated individual intakes from 24hR for all dietary factors using either estimation method (P<0.001 for each), except for starchy vegetables (AME: P = 0.15; PC: P = 0.85). For foods, overestimation ranged from 4% for seafood to about 240% for fruits, and for nutrients from 11% for carbohydrates and poly-unsaturated fats to 55% for vitamin C, with similar overestimation for the AME and the PC method. By strata, overestimation was modestly higher in men vs. women, in children (0-10y) vs. adolescents (11-19y) and adults (20-44y, ≥45y), among adults of higher (≥6y) vs. lower (<6y) education, in Muslims vs. other religions (Christians, Hindus), and for the lowest vs. all other income groups. This overestimation was notably higher in young children (0-5y) vs. all other age groups and in the lowest vs. all other income groups. Underestimation was rarely observed, for example for milk intake (-56%) in young children (0-5y). The PC approach did not capture heterogeneity in validity of estimation of different dietary factors by age, mainly in children (0-5y, 6-10y). Spearman's correlations between individualized household estimates and 24hR data were higher for the AME (0.30–0.70) than PC (0.20–0.50) approach. Findings were similar with and without multivariate regression, with proportions of variance (R2) in 24hR intakes explained by the AME being generally greater than PC estimates, yet still low to modest.ConclusionsIn this national survey, established methods for estimating individual level intakes from household surve...

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Section: Discussionmentioning

confidence: 99%

Assessing dietary intakes from household budget surveys: A national analysis in Bangladesh

et al. 2018

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“…The portfolio approach makes use of location-specific data to not only capture the socio-ecological dynamics of smallholder food production diversity but uniquely includes individual food consumption data to inform knowledge on local dietary gaps. Such individual-level consumption data are imperative for informed decision making at country, regional and global levels, but the information available is generally limited and dispersed (IFPRI 2014;Micha et al 2018). For example, the data available are often based on national food supplies rather than individual-level information disaggregated by location, gender, age and intra-household food allocation.…”

Section: Discussionmentioning

confidence: 99%

Developing fruit tree portfolios that link agriculture more effectively with nutrition and health: a new approach for providing year-round micronutrients to smallholder farmers

et al. 2019

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A sufficient intake of fruits can alleviate micronutrient deficiencies and reduces the risks of a number of associated diseases. In many parts of sub-Saharan Africa, however, the production and consumption of fruits are inadequate on average and in particular so in specific seasons. To better incorporate fruits into local food systems while addressing the challenge of seasonal availability, World Agroforestry (ICRAF) has developed a methodology based on “fruit tree portfolios” that selects socio-ecologically suitable and nutritionally important fruit tree species for farm production, to meet local consumption needs. We here present this approach and illustrate it with data from a case study involving Western and Eastern Kenya. The approach uses mixed methods to capture on-farm fruit tree diversity and seasonality at a household level (n = 600 in our case study), the months of household’s food security and insecurity (n = 600) and food consumption patterns at an individual level, to identify dietary gaps (n = 294 women and child pairs in our example). In our case study, 31 fruit tree species were reported on farms in our Western Kenya sample (9 of which were indigenous) and 51 (27 indigenous) in Eastern Kenya. In addition, the median number of food-insecure months per household was four (ranging from 0 to 9 months) in Eastern Kenya and three (0 to 12 months) in Western Kenya. Finally, using 24-h recalls the proportion of women that had consumed a fruit the day before the interview was around 55% in Western Kenya and 80% in Eastern Kenya, with consumption averaging 93 and 131 g, respectively. Using these parameters for each site and fruit tree phenology and food composition data sets, we derived context-specific recommendations that involve promoting 11 fruit tree species to address micronutrient gaps.

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“…However, these data are often collected through small-scale surveys. In addition, they are largely underutilised due to poor dissemination and lack of harmonisation that does not allow comparisons across time periods, seasons and geographical locations (33,34) .The world needs harmonised IQFC data to address the growing challenges of malnutrition and food safety efficiently and to deal with the environmental impact of diets. It is necessary to ensure that IQFC data fulfil the following conditions, so they can be used to their full potential in informing actions to improve nutrition, food safety and environmental protection for all:…”

Section: Individual Quantitative Food Consumption Datamentioning

confidence: 99%

FAO/WHO GIFT (Global Individual Food consumption data Tool): a global repository for harmonised individual quantitative food consumption studies

et al. 2019

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Knowing who eats what, understanding the various eating habits of different population groups, according to the geographical area, is critical to develop evidence-based policies for nutrition and food safety. The FAO/WHO Global Individual Food consumption data Tool (FAO/WHO GIFT) is a novel open-access online platform, hosted by FAO and supported by WHO, providing access to harmonised individual quantitative food consumption (IQFC) data, especially in low- and middle-income countries (LMIC). FAO/WHO GIFT is a growing repository, which will serve as the global FAO/WHO hub to disseminate IQFC microdata. Currently five datasets from LMIC are available for dissemination, and an additional fifty datasets will be made available by 2022. To facilitate the use of these data by policy makers, ready-to-use food-based indicators are provided for an overview of key data according to population segments and food groups. FAO/WHO GIFT also provides an inventory of existing IQFC data worldwide, which currently contains detailed information on 188 surveys conducted in seventy-two countries. In order for end-users to be able to aggregate the available data, all datasets are harmonised with the European Food Safety Authority's food classification and description system FoodEx2 (modified for global use). This harmonisation is aimed at enhancing the consistency and reliability of nutrient intake and dietary exposure assessments. FAO/WHO GIFT is developed in synergy with other global initiatives aimed at increasing the quality, availability and use of IQFC data in LMIC to enable evidence-based decision-making and policy development for better nutrition and food safety.

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Global Dietary Surveillance: Data Gaps and Challenges

Cited by 74 publications

References 124 publications

Assessing dietary intakes from household budget surveys: A national analysis in Bangladesh

Assessing dietary intakes from household budget surveys: A national analysis in Bangladesh

Developing fruit tree portfolios that link agriculture more effectively with nutrition and health: a new approach for providing year-round micronutrients to smallholder farmers

FAO/WHO GIFT (Global Individual Food consumption data Tool): a global repository for harmonised individual quantitative food consumption studies

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