Identifying Targets for the Prevention of Childhood Undernutrition in a Resource-Limited Peri-Urban Ecuadorian Community.

BACKGROUND: In middle-income countries, malnutrition concentrates in marginalized populations with a lack of effective preventive strategies. OBJECTIVE: Identify risk factors for undernutrition in a peri-urban Ecuadorian community of children aged 12 to 59 months. METHODS: Data from a cross-sectional survey in 2011 of children 1 to 5 years were analyzed including demographic data, medical history and examination, food frequency questionnaire (FFQ), anthropometric measurements, and blood for complete blood count, C-reactive protein, vitamin A, iron, and zinc levels. Dietary Diversity Score (DDS) was calculated from FFQ. Bivariate and multivariate analysis assessed effects on primary outcome of undernutrition by DDS, vitamin deficiencies, and demographic and nutritional data. RESULTS: N = 67, 52.2% undernourished: 49.3% stunted, 25.4% underweight, and 3% wasted; 74.6% (n = 50) were anemic and 95.1% (n = 39) had low serum zinc. Dietary Diversity Score was universally low (mean 4.91 ± 1.36, max 12). Undernutrition was associated with lower vitamin A levels (20 306, IQR: 16605.25-23973.75 vs 23665, IQR: 19292-26474 ng/mL, P = .04); underweight was associated with less parental report of illness (43.8%, n = 7 vs 80% n = 40, P = .005) and higher white blood count (13.7, IQR: 11.95-15.8 vs 10.9, IQR: 7.8-14.23 × 109/L, P = .02). In multiple regression, risk of undernutrition decreased by 4% for every $10 monthly income increase (95 CI%: 0.5%-7.4%, P = .02, n = 23); risk of underweight decreased by 0.06 for every increased DDS point (adjusted odds ratio: 0.06; 95 CI%: 0.004-0.91, P = .04, n = 23). CONCLUSIONS: In this peri-urban limited-resource, mostly Indigenous Ecuadorian community, stunting exceeds national prevalence, lower monthly income is the strongest predictor of undernutrition, lower DDS can predict some forms of undernutrition, and vitamin deficiencies are associated with but not predictive of undernutrition.

Weight-for-age z-score as a proxy marker for diarrhoea in epidemiological studies.

BACKGROUND: The validity of unblinded randomised trials testing interventions against diarrhoea is severely compromised by the potential for bias. Objective proxy markers for diarrhoea not relying on self-report are needed to assess the effect of interventions that cannot be blinded. Short-term changes in weight-for-age z-score (WAZ) may (due to catch-up growth) not be a clinically important marker for nutritional status. However, even a transient decrease in WAZ could indicate recent diarrhoea, and be interpreted as the effect of an intervention. METHODS: Using data from two large vitamin A trials from Ghana and Brazil, the immediate effect of the cumulative diarrhoea occurrence over 14 and 28 day time windows on WAZ was explored. RESULTS: A very strong linear association was found between the number of days with diarrhoea over the last 14-28 days and WAZ. In both trials, differences in diarrhoea between the trial arms were associated with corresponding differences in WAZ. CONCLUSION: Repeated WAZ measures appear to be a suitable proxy marker for diarrhoea in children, but have disadvantages in terms of specificity and study power.

Recent diarrhoeal illness and risk of lower respiratory infections in children under the age of 5 years.

BACKGROUND: Children in low-income settings suffering from frequent diarrhoea episodes are also at a high risk of acute lower respiratory infections (ALRI). We explored whether this is due to common risk factors for both conditions or whether diarrhoea can increase the risk of ALRI directly. METHODS: We used a dynamic time-to-event analysis of data from two large child studies in low-income settings in Ghana and Brazil, with the cumulative diarrhoea prevalence over 2 weeks as the exposure and severe ALRI as outcome. The analysis was adjusted for baseline risk of ALRI and diarrhoea, seasonality and age. RESULTS: The child population from Ghana had a much higher risk of diarrhoea, malnutrition and death than the children in Brazil. In the data from Ghana, every additional day of diarrhoea within 2 weeks increased the risk of ALRI by a factor of 1.08 (95% CI 1.00-1.15). In addition, we found a roughly linear relationship between the number of diarrhoea days over the last 28 days and the risk of ALRI. In the Ghana data, 26% of ALRI episodes may be due to recent exposure to diarrhoea. The Brazilian data gave no evidence for an association between diarrhoea and ALRI. CONCLUSION: Diarrhoea may contribute substantially to the burden of ALRI in malnourished child populations.

Estimating the longitudinal prevalence of diarrhea and other episodic diseases: continuous versus intermittent surveillance.

BACKGROUND: Longitudinal prevalence (ie, the proportion of time with the disease) is used to describe morbidity from diarrhea and other episodic conditions. The aim of this analysis was to compare estimates of longitudinal prevalence based on intermittent sampling at regular intervals with 24- or 48-hour recall, with estimates based on continuous surveillance. METHODS: Based on 2 real datasets from Brazil and Guatemala, we developed a simulated dataset representing the diarrhea morbidity of 10,000 individuals followed over 365 days. RESULTS: Both the model and the real datasets showed that the standard deviation of the longitudinal prevalence increases with decreasing numbers of days sampled, so that a study sampling only a fraction of days would require a larger sample size. However, due to the correlation of diarrhea between consecutive days, sampling at 7- to 14-day intervals results in relatively small loss of precision and power compared with daily morbidity records, especially when the average diarrheal episode is long. A study based on morbidity data for every seventh day may require only a 5%-24% larger sample size than a study with daily records, depending on the average duration of episodes. Using a recall period of 48 hours instead of 24 hours increases power if the average episode is short. CONCLUSIONS: The results question the necessity of continuous surveillance to estimate longitudinal prevalence. In addition to savings in cost and staff time, intermittent sampling of morbidity may improve validity by minimizing recall error and reducing the influence of surveillance on participants' behavior.