Seasonal variations in nutritional risk among children in central Mali

Adams, Aubrey Manack

doi:10.1080/03670244.1994.9991418

Cited by 13 publications

(7 citation statements)

References 26 publications

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“…A slightly more specific version of the wealth hypothesis addresses the seasonal nature of food security in the area. Anthropologists (Richards, 1939), nutritionists , and anthropological informants working or living in agricultural communities frequently call attention to the potentially devastating preharvest season, a period marked by a host of deleterious outcomes including increased infectious diseases (Tomkins, 1993), increased workloads (Panter-Brick, 1996), reductions in energy intake (Brown et al, 1982) and food availability (Wandel and Holmboe-Ottesen, 1992), deterioration of nutritional status (Adams, 1994;Ferro-Luzzi and Branca, 1993), and increased child mortality (Moore et al, 1997). Because of these patterns, "seasonality" may create and subsequently reinforce inequalities in poverty and poor health, not only within but between groups.…”

Section: Seasonal Household Food Securitymentioning

confidence: 99%

Ethnic expansions and between‐group differences in children's health: A case study from the Rukwa Valley, Tanzania

Hadley

2005

American J Phys Anthropol

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The Sukuma ethnic group appears to be expanding across Tanzania at a rate far greater than other ethnic groups in the area. In this paper, the household-level dynamics that may be fueling this expansion are explored by comparing measures of infant mortality and child health with another Tanzanian ethnic group, the Pimbwe. Consistent with expectations, the Sukuma appear to have comparable levels of fertility but lower child mortality. As predicted, compared to the Pimbwe, Sukuma children are also heavier and taller for their age, suggesting better nutritional status. Four hypotheses about why the Sukuma are so successful in this area are addressed. Surprisingly, the results show that household food security and wealth are not related to children's nutritional status, nor can maternal effects account for the observed health differences. Several lines of evidence suggest that different patterns of infant feeding practices may underlie the differences in children's nutritional status.

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Section: Seasonal Household Food Securitymentioning

confidence: 99%

Ethnic expansions and between‐group differences in children's health: A case study from the Rukwa Valley, Tanzania

Hadley

2005

American J Phys Anthropol

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“…Malaria affects those who have greater susceptibility to infection: i ) children under 5 years of age who have not yet developed low-level immunity; ii ) mal-nourished pregnant women; and iii ) labor migrants from non-endemic zones who, like children under 5 years of age, lack low-level immunity [17] – [22] . Furthermore, pervasive malnutrition—which precedes harvesting and partially coincides with diarrhea, ARI, and malaria transmission zeniths—aggravates (and probably underlies) the somber epidemiological scenario crafted by the aforementioned diseases in the Sahel [7] , [23] , [24] .…”

Section: Introductionmentioning

confidence: 99%

Forecasting Non-Stationary Diarrhea, Acute Respiratory Infection, and Malaria Time-Series in Niono, Mali

et al. 2007

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BackgroundMuch of the developing world, particularly sub-Saharan Africa, exhibits high levels of morbidity and mortality associated with diarrhea, acute respiratory infection, and malaria. With the increasing awareness that the aforementioned infectious diseases impose an enormous burden on developing countries, public health programs therein could benefit from parsimonious general-purpose forecasting methods to enhance infectious disease intervention. Unfortunately, these disease time-series often i) suffer from non-stationarity; ii) exhibit large inter-annual plus seasonal fluctuations; and, iii) require disease-specific tailoring of forecasting methods.Methodology/Principal FindingsIn this longitudinal retrospective (01/1996–06/2004) investigation, diarrhea, acute respiratory infection of the lower tract, and malaria consultation time-series are fitted with a general-purpose econometric method, namely the multiplicative Holt-Winters, to produce contemporaneous on-line forecasts for the district of Niono, Mali. This method accommodates seasonal, as well as inter-annual, fluctuations and produces reasonably accurate median 2- and 3-month horizon forecasts for these non-stationary time-series, i.e., 92% of the 24 time-series forecasts generated (2 forecast horizons, 3 diseases, and 4 age categories = 24 time-series forecasts) have mean absolute percentage errors circa 25%.Conclusions/SignificanceThe multiplicative Holt-Winters forecasting method: i) performs well across diseases with dramatically distinct transmission modes and hence it is a strong general-purpose forecasting method candidate for non-stationary epidemiological time-series; ii) obliquely captures prior non-linear interactions between climate and the aforementioned disease dynamics thus, obviating the need for more complex disease-specific climate-based parametric forecasting methods in the district of Niono; furthermore, iii) readily decomposes time-series into seasonal components thereby potentially assisting with programming of public health interventions, as well as monitoring of disease dynamics modification. Therefore, these forecasts could improve infectious diseases management in the district of Niono, Mali, and elsewhere in the Sahel.

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“…To test precisely how often children fall below this weight level more observations during the course of the year are needed than were collected. A recent study in Mali also failed to find seasonal change in the prevalence of children at risk despite the presence of seasonal variations in growth velocity (Adams 1994). Nevertheless, since the annual growth rates that are realized by the children in the lowest income class are not below those of the other income classes, there are no indications that the greater seasonal fluctuation results in any negative effects in the long run.…”

Section: Environmental Factorsmentioning

confidence: 86%