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Observational bias during nutrition surveillance: results of a mixed longitudinal and cross-sectional data collection system in Northern Nigeria.

Grellety E, Luquero FJ, Mambula C, Adamu HH, Elder G, Porten K - PLoS ONE (2013)

Bottom Line: The effect of repeated visits to the same cluster was examined using general linear mixed effects models adjusted for the seasonal change.With each repeat survey of a cluster, the prevalence of GAM decreased by 1.6% (95% CI: 0.4 to 2.7; p = 0.012) relative to the prevalence observed during the previous visit after adjusting for seasonal change.Repeated surveys in the same cluster-village, even if different children are selected, lead to a progressive improvement of the nutritional status of that village.

View Article: PubMed Central - PubMed

Affiliation: Epicentre, Paris, France. Emmanuel.GRELLETY@epicentre.msf.org

ABSTRACT

Background: The Sahel is subject to seasonal hungry periods with increasing rates of malnutrition. In Northern Nigeria, there is no surveillance system and surveys are rare. The objectives were to analyse possible observational bias in a sentinel surveillance system using repeated mixed longitudinal/cross-sectional data and estimate the extent of seasonal variation.

Methods: Thirty clusters were randomly selected using probability proportional to size (PPS) sampling from Kazaure Local Government Area, Jigawa State. In each cluster, all the children aged 6-59 months within 20 randomly selected households had their mid-upper arm circumference measured and were tested for oedema. The surveys were repeated every 2 or 4 weeks. At each survey round, three of the clusters were randomly selected to be replaced by three new clusters chosen at random by PPS. The seasonal variation of acute malnutrition was assessed using cyclical regression. The effect of repeated visits to the same cluster was examined using general linear mixed effects models adjusted for the seasonal change.

Results: There was a significant seasonal fluctuation of Global Acute Malnutrition (GAM) with a peak in October. With each repeat survey of a cluster, the prevalence of GAM decreased by 1.6% (95% CI: 0.4 to 2.7; p = 0.012) relative to the prevalence observed during the previous visit after adjusting for seasonal change.

Conclusions: Northern Nigeria has a seasonal variation in the prevalence of acute malnutrition. Repeated surveys in the same cluster-village, even if different children are selected, lead to a progressive improvement of the nutritional status of that village. Sentinel site surveillance of nutritional status is prone to observational bias, with the sentinel site progressively deviating from that of the community it is presumed to represent.

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Prediction of seasonal variation of the GAM using a Binomial GLMM, Kazaure LGA, Jigawa State, Nigeria.
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pone-0062767-g004: Prediction of seasonal variation of the GAM using a Binomial GLMM, Kazaure LGA, Jigawa State, Nigeria.

Mentions: Table 2 shows the results of the univariate and multivariate linear analysis of the absolute MUAC. In the univariate analysis MUAC varied significantly with the number of times the cluster was surveyed, and also with age, sex, ethnic group and seasonal pattern. These factors remained significant in the multivariate analysis showing that they each made an independent contribution to the variance. The number of times a cluster had been visited was significantly associated with an increase in the average MUAC between 0.006 mm and 0.124 mm per visit (95% CI). Table 3 shows the variations in GAM and SAM expressed as the relative change in prevalence. The GAM varies significantly with the number of times the cluster has been surveyed, age, sex, ethnic group and season both with the univariate and multivariate analysis. The prevalence of SAM varied with the number of times the cluster has been surveyed, age, sex, ethnic group and season in the univariate analysis, but only with sex, age, and seasonality in the multivariate analysis. Thus, as a particular cluster village is repeatedly visited, the prevalence of acute malnutrition decreases linearly. The PR per surveillance visit was 0.98 (95% CI: 0.973 to 0.996; p = 0.012) for GAM and 0.99 (95% CI: 0.962 to 1.017; p = 0.475) for SAM compared with the previous visit (Table 4). This means that the observed prevalence decreases by 1.6% (95% CI: 0.4 to 2.7, GAM) and 1.1% (95% CI: 0.0 to 3.8, SAM) relative to the prevalence observed during the previous visit after adjusting for seasonal change. The seasonal changes in GAM and SAM prevalence were significant; figures 4 and 5 show the predicted variation over one year. GAM prevalence reaches a maximum between July and December with a peak in October and SAM between June and November with a peak in September (Table 3 and 4). The relative intensity of the peaks is 1.5 and 2.4 respectively.


Observational bias during nutrition surveillance: results of a mixed longitudinal and cross-sectional data collection system in Northern Nigeria.

Grellety E, Luquero FJ, Mambula C, Adamu HH, Elder G, Porten K - PLoS ONE (2013)

Prediction of seasonal variation of the GAM using a Binomial GLMM, Kazaure LGA, Jigawa State, Nigeria.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3643959&req=5

pone-0062767-g004: Prediction of seasonal variation of the GAM using a Binomial GLMM, Kazaure LGA, Jigawa State, Nigeria.
Mentions: Table 2 shows the results of the univariate and multivariate linear analysis of the absolute MUAC. In the univariate analysis MUAC varied significantly with the number of times the cluster was surveyed, and also with age, sex, ethnic group and seasonal pattern. These factors remained significant in the multivariate analysis showing that they each made an independent contribution to the variance. The number of times a cluster had been visited was significantly associated with an increase in the average MUAC between 0.006 mm and 0.124 mm per visit (95% CI). Table 3 shows the variations in GAM and SAM expressed as the relative change in prevalence. The GAM varies significantly with the number of times the cluster has been surveyed, age, sex, ethnic group and season both with the univariate and multivariate analysis. The prevalence of SAM varied with the number of times the cluster has been surveyed, age, sex, ethnic group and season in the univariate analysis, but only with sex, age, and seasonality in the multivariate analysis. Thus, as a particular cluster village is repeatedly visited, the prevalence of acute malnutrition decreases linearly. The PR per surveillance visit was 0.98 (95% CI: 0.973 to 0.996; p = 0.012) for GAM and 0.99 (95% CI: 0.962 to 1.017; p = 0.475) for SAM compared with the previous visit (Table 4). This means that the observed prevalence decreases by 1.6% (95% CI: 0.4 to 2.7, GAM) and 1.1% (95% CI: 0.0 to 3.8, SAM) relative to the prevalence observed during the previous visit after adjusting for seasonal change. The seasonal changes in GAM and SAM prevalence were significant; figures 4 and 5 show the predicted variation over one year. GAM prevalence reaches a maximum between July and December with a peak in October and SAM between June and November with a peak in September (Table 3 and 4). The relative intensity of the peaks is 1.5 and 2.4 respectively.

Bottom Line: The effect of repeated visits to the same cluster was examined using general linear mixed effects models adjusted for the seasonal change.With each repeat survey of a cluster, the prevalence of GAM decreased by 1.6% (95% CI: 0.4 to 2.7; p = 0.012) relative to the prevalence observed during the previous visit after adjusting for seasonal change.Repeated surveys in the same cluster-village, even if different children are selected, lead to a progressive improvement of the nutritional status of that village.

View Article: PubMed Central - PubMed

Affiliation: Epicentre, Paris, France. Emmanuel.GRELLETY@epicentre.msf.org

ABSTRACT

Background: The Sahel is subject to seasonal hungry periods with increasing rates of malnutrition. In Northern Nigeria, there is no surveillance system and surveys are rare. The objectives were to analyse possible observational bias in a sentinel surveillance system using repeated mixed longitudinal/cross-sectional data and estimate the extent of seasonal variation.

Methods: Thirty clusters were randomly selected using probability proportional to size (PPS) sampling from Kazaure Local Government Area, Jigawa State. In each cluster, all the children aged 6-59 months within 20 randomly selected households had their mid-upper arm circumference measured and were tested for oedema. The surveys were repeated every 2 or 4 weeks. At each survey round, three of the clusters were randomly selected to be replaced by three new clusters chosen at random by PPS. The seasonal variation of acute malnutrition was assessed using cyclical regression. The effect of repeated visits to the same cluster was examined using general linear mixed effects models adjusted for the seasonal change.

Results: There was a significant seasonal fluctuation of Global Acute Malnutrition (GAM) with a peak in October. With each repeat survey of a cluster, the prevalence of GAM decreased by 1.6% (95% CI: 0.4 to 2.7; p = 0.012) relative to the prevalence observed during the previous visit after adjusting for seasonal change.

Conclusions: Northern Nigeria has a seasonal variation in the prevalence of acute malnutrition. Repeated surveys in the same cluster-village, even if different children are selected, lead to a progressive improvement of the nutritional status of that village. Sentinel site surveillance of nutritional status is prone to observational bias, with the sentinel site progressively deviating from that of the community it is presumed to represent.

Show MeSH
Related in: MedlinePlus