Birth registration and child undernutrition in sub-Saharan Africa

The database comprises data on malnutrition and birth registration rates in 33 sub-Saharan African Countries as retrieved by DHS (http://www.dhsprogram.com) and MICS (http://www.childinfo.org/mics.html) reports. The study protocol includes detailed information on data selection and statistical analyses

Birth registration and child undernutrition in sub-saharan Africa

Objective: In many countries of the world millions of people are not registered at birth. However, in order to assess children’s nutritional status it is necessary to have an exact knowledge of their age. In the present paper we discuss the effects of insufficient or imprecise age data on estimates of undernutrition prevalence. Design: Birth registration rates and levels of stunting, underweight and wasting were retrieved from Multiple Indicator Cluster Surveys and Demographic and Health Surveys of thirty-seven sub-Saharan African countries, considering the subdivision in wealth quintiles. The composition of the cross-sectional sample used for nutritional evaluation was analysed using a permutation test. Logistic regression was applied to analyse the relationship between birth registration and undernutrition. The 95 % probability intervals and Student’s t test were used to evaluate the effect of age bias and error. Results: Heterogeneous sampling designs were detected among countries, with different percentages of children selected for anthropometry. Further, registered children were slightly more represented within samples used for nutritional analysis than in the total sample. A negative relationship between birth registration and undernutrition was recognized, with registered children showing a better nutritional status than unregistered ones, even within each wealth quintile. The over- or underestimation of undernutrition in the case of systematic over- or underestimation of age, respectively, the latter being more probable, was quantified up to 28 %. Age imprecision was shown to slightly overestimate undernutrition. Conclusions: Selection bias towards registered children and underestimation of children’s age can lead to an underestimation of the prevalence of undernutrition

Specific bioelectrical vectors pattern in individuals with sarcopenic obesity

Background: Sarcopenic obesity is a common condition in the elderly associated with excessive adiposity and low muscle mass and strength. Aims: This study aims to establish a method for detecting bioelectrical characteristics in individuals with sarcopenic obesity through specific Bioelectrical Impedance Vector Analysis (specific BIVA), while considering the characteristics of individuals with healthy, sarcopenic, and obese conditions. Methods: The sample was composed by 915 Italian adults over 50 years of age (men: 74.6 ± 8.8 y; women:76.3 ± 8.8 y) living in Sardinia (Italy). A dataset of 1590 US adults aged 21 - 49 years retrieved from the 2003 - 2004 National Health and Nutrition Examination Survey was also considered in a final step of the study. Anthropometric (stature, weight, waist, arm, and calf circumferences) and whole-body bioelectrical variables were taken. In the Italian sample, bioelectrical impedance was applied to estimate the relative content of fat mass and skeletal muscle mass. Groups with healthy body composition (NS-NO), or consistent with sarcopenia (S), sarcopenic obesity (S-O), and obesity (O) were defined based on the cut-offs suggested by European expert guidelines (EWGSOP2 and ESPEN-EASO). Specific BIVA was applied to compare groups and to identify the area for sarcopenic obesity within young-adults tolerance ellipses. The position of the specific vector of US individuals with S-O, selected on the basis of DXA measurements, was also considered. Results: In both sexes of the Italian sample, the bioelectrical characteristics of the four groups were different (p < 0.001). The differences were mainly related to vector length, indicative of higher fat mass, which was longer in the O and S-O groups, and phase angle, a proxy of intracellular/extracellular water and muscle mass, lower in the sarcopenic groups. Bioelectrical vectors of the S-O group fell in the right quadrant, outside of the 95 % tolerance ellipses of young adults. The mean vector of the US sample with S-O fell in the same area. Within the S-O area, women had similar bioelectrical values, while men showed phase angle variability, which was related to the severity of the condition. Conclusions: Specific BIVA detects body composition peculiarities of individuals with sarcopenic obesity, thus allowing their diagnosis when associated with low handgrip strength values

Nutritional status in the healthy longeval population from Sardinia (Italy)

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