How well global dietary intake estimates agree: a case of sodium consumption.

Global dietary data repositories are key components of nutrition surveillance. The two most comprehensive databases, the Global Dietary Database (GDD) and the Global Burden Disease (GBD), provide national dietary intake estimates but use different data sources and models to generate estimates. To explore the agreement between GDD and GBD estimates, we compared country-specific average daily sodium intakes in 169 countries over a 28-year period using descriptive statistics, the Bland-Altman method, and prevalence exceeding the intake reference level of 2.3 g/day. We detected a staggering 36% difference between GDD and GBD estimates of global mean intakes (2.68 ± 0.74 vs. 3.88 ± 1.15 g/day, respectively; p < 0.0001). As 104 (61.5%) countries reported to have over-consumed sodium by both databases, the development of standardized approaches for national dietary intake estimation is critical for monitoring global sodium intake in a systematic and comprehensive way and for implementing global strategies to reduce sodium intake.

Peak timing of slowest growth velocity among young children coincides with highest ambient temperatures in Burkina Faso: a longitudinal study.

BACKGROUND: Seasonal cycles in climatic factors affect drivers of child growth and contribute to seasonal fluctuations in undernutrition. Current growth seasonality models are limited by categorical definitions of seasons that rely on assumptions about their timing and fail to consider their magnitude. OBJECTIVE: We disentangle the relationship between climatic factors and growth indicators, using harmonic regression to determine how child growth is related to peaks in temperature, precipitation, and vegetation. METHODS: Longitudinal anthropometric data collected between August 2014 and December 2016 from 5039 Burkinabè children measured monthly from age 6 to 28 mo (108,580 observations) were linked with remotely sensed daily precipitation, vegetation, and maximum air temperature. Our models parsimoniously extract a cyclic signal with multiple potential peaks, to compare the magnitude and timing of seasonal peaks in climatic factors and morbidity with that of nadirs in growth velocity (cm/mo, kg/mo). RESULTS: Length and weight velocity were slowest twice a year, coinciding both times with the highest temperatures, and peak fever incidence. Length velocity is slowest 13 d after the first temperature peak in April, and 5 d after the second. Similarly, weight velocity is slowest 13 d before the first temperature peak, and 11 d before the second. The statistical relationship between temperature and anthropometry shows that when the current temperature is higher, weight velocity is lower (ß = -0.0048; 95% CI: -0.0059, -0.0038), and length velocity is higher (ß = 0.0088; 95% CI: 0.0070, 0.0105). CONCLUSIONS: Results suggest that child health and development are more affected by high temperatures than by other aspects of climatic seasonality such as rainfall. Emerging shifts in climatic conditions will pose challenges to optimal growth, highlighting the importance of changes that optimize the timing of nutrition interventions and address environmental growth-limiting conditions. CLINICAL TRIAL REGISTRY: Clinicaltrials.gov: NCT02071563.

Reducing the risks of nuclear war - The role of health professionals.

No abstract available.

Seasonality of Acute Malnutrition in African Drylands: Evidence From 15 Years of SMART Surveys.

Reduction of wasting, or low weight-for-height, is a critical target for the Zero Hunger Sustainable Development Goal, yet robust evidence establishing continuous seasonal patterns of wasting is presently lacking. The current consensus of greatest hunger during the preharvest period is based on survey designs and analytical methods, which discretize time frame into preharvest/postharvest, dry/wet, or lean/plenty seasons. We present a spatiotemporally nuanced study of acute malnutrition seasonality in African drylands using a 15-year data set of Standardized Monitoring and Assessment of Relief and Transition surveys (n = 412,370). Climatological similarity was ensured by selecting subnational survey regions with 1 rainy season and by spatially matching each survey to aridity and livelihood zones. Harmonic logit regression models indicate 2 peaks of wasting during the calendar year. Greatest wasting prevalence is estimated in April to May, coincident with the primary peak of temperature. A secondary peak of wasting is observed in August to October, coinciding with the primary peak of rainfall and secondary peak of temperature. This pattern is retained across aridity and livelihood zones and is sensitive to temperature, precipitation, and vegetation. Improved subnational estimation of acute malnutrition seasonality can thus assist decision makers and practitioners in data-sparse settings and facilitate global progress toward Zero Hunger.

Plain language titleFifteen Years of Rapid Assessment Surveys Indicate Seasonal Variability in Prevalence of Acute Malnutrition Among Children Younger Than 5 Years in African DrylandsPlain language summaryWasting or low weight-for-height is a key indicator of short-term or acute malnutrition. The timing of highest wasting prevalence, particularly among children younger than 5 years, is of interest for humanitarian efforts to reduce hunger. Current knowledge about this timing derives from survey designs, which discretize continuous time into preharvest/postharvest, dry/wet, or lean/plenty seasons. Instead of this categorical approach, we utilize harmonic regressions that allow for modeling of continuous time in our analysis of 15 years of Standardized Monitoring and Assessment of Relief and Transition surveys. Surveys conducted in parts of North Africa with 1 rainy season (unimodal regions) were selected for similar climate, and survey locations were further subdivided by aridity and livelihood zones. The seasonal pattern of extreme wasting prevalence in each group was modeled using survey data for a total of 412,370 children. We identified 2 periods of highest wasting prevalence in April to May and August to October. The April to May peak occurs during highest temperatures, and the August to October peak occurs during periods of highest rainfall and warmer temperatures in the study area. These findings can inform the timing of nutrition programs in unimodal dryland regions and guide future quantitative models of acute malnutrition seasonality.

The Complexity of the Seasonality of Nutritional Status: Two Annul Peaks in Child Wasting in Eastern Chad.

BACKGROUND: Understanding seasonal patterns in nutritional status is critical for achieving and tracking global nutrition goals. However, the majority of nutrition seasonality research design draws on 2 or 3 within-year time points based on existing assumptions of seasonality, missing a more nuanced pattern. OBJECTIVE: We aimed to identify the intra-year variability of childhood wasting, severe wasting, and weight-for-height z-scores (WHZ) in a dryland single wet-season context and illustrate an analytical approach for improving analysis of the seasonality of nutritional status. METHODS: To quantify the intra-year variability in nutritional status, we use data from a 23-month panel study (May 2018 to March 2020) following 231 children (6-59 months of age) in eastern Chad. We apply a mixed-effects harmonic regression with child- and village-level fixed effects on the odds of being wasted, severely wasted, and on WHZ, testing for multiple and nonsymmetrical seasonal peaks, adjusted for child sex and age. We triangulate our findings using climate data on temperature, vegetation, and precipitation. RESULTS: We identify 2 annual peaks of wasting and severe wasting. Wasting peaks at 14.7% (confidence interval [CI], 11.8-18.2) at the end of the dry season, while the smaller peak corresponds to the start of the harvest period at 13.4% (CI, 10.7-16.6). The odds of being wasted decline during the rainy season to 11.8% (CI, 9.4-14.7), with the lowest prevalence of 8.8% (CI, 6.9-11.1) occurring during the start of the dry season. In addition, a 1°C monthly increase in temperature is significantly associated with a 5% (CI, 1.4-8.7) and 12% (CI, 3.0-20.3) increase in the odds that a child is wasted and severely wasted, respectively. CONCLUSIONS: Intra-year variability of child wasting is far more complex and nuanced than identified by the literature, with 2 peaks, as opposed to 1, likely corresponding to different seasonal drivers, such as food insecurity, disease, water contamination, and care practices at different times of year. Better seasonality analysis can go a long way in improving the timing and content of programming with the goal of reducing child wasting.

Plain language titleTwo Seasonal Peaks of Acute Malnutrition in ChadPlain language summaryUnderstanding seasonal patterns in nutrition is crucial for achieving and monitoring global nutrition goals. However, most research on nutrition seasonality relies on only a few time points within a year, which oversimplifies the true pattern. In our study conducted in Chad, a dryland environment with a single rainy season, we examined various indicators of acute malnutrition, including severe acute malnutrition. We analyzed 23 months of data from 231 children aged 6 to 59 months, considering factors such as sex, age, monthly rainfall, temperature, and vegetation. Our findings revealed 2 peaks of acute malnutrition, challenging the prevailing notion of a single peak identified in existing literature. The first, larger peak occurred at the onset of the rainy season, followed by a decline and then a second peak just before the harvest period. This pattern aligned with temperature variations rather than rainfall. The complex and nuanced seasonal patterns we observed suggest that different factors such as food insecurity, disease, water contamination, and care practices may contribute to acute malnutrition at different times of the year. Improved analysis of seasonality can significantly enhance the timing and effectiveness of interventions aimed at reducing child wasting.