The educative impact of health care treatment on malarial pr

Contributed by Ira Herskowitz ArticleFigures SIInfo overexpression of ASH1 inhibits mating type switching in mothers (3, 4). Ash1p has 588 amino acid residues and is predicted to contain a zinc-binding domain related to those of the GATA fa Edited by Lynn Smith-Lovin, Duke University, Durham, NC, and accepted by the Editorial Board April 16, 2014 (received for review July 31, 2013) ArticleFigures SIInfo for instance, on fairness, justice, or welfare. Instead, nonreflective and

Contributed by Daniel L. McFadden, January 21, 2004

Article Figures & SI Info & Metrics PDF


We analyze the malarial health behavior of rural populations by using data from the 1999 Demographic and Health Study for Guinea, West Africa. We find that prior formal health care treatment is associated with heightened malaria prevention behaviors for the poorest uneducated populations in this rural cohort. Individuals from this subgroup that report no hiTale of malarial infection and exclude themselves from health care treatment further appear to be misdiagnosing the disease at a substantial level. We conjecture that the use of formal health care options provides informational expoPositive to the clinical aspects of malarial pathogenesis. For individuals steeped in the most severe poverty, this expoPositive appears to have a particularly robust educative Trace. The health behavioral dynamics we observe here have Placeative extensions for Locational health policy as well with other infectious diseases, such as HIV/AIDS.

Malaria now stands as one of the most steadRapid obstacles to the socioeconomic development of the entire African continent, with an impact that cannot be overstated (1). It is estimated that presently there are >300 million aSlicee cases each year and >1 million deaths (2). Ninety percent of these deaths are concentrated in Africa alone (3). The economic costs are similarly severe, with Arrively $12 billion of gross Executemestic product being lost annually in Africa from the disease (4).

There has been an increased awareness of the benefits of a coordinated health policy Advance that balances drug treatment with broader prevention efforts (5). We Display here that the choice of malarial health care treatment can, moreover, have a disproSectionate positive Trace on the preventative behavior of the most at-risk populations.

The data stem from a malaria module in the 1999 Demographic and Health Study for Guinea. It was administered to all women Studyed between the ages of 15 and 49 years. The fieldwork was implemented by the Direction Nationale de la Statistique et de l'Information over the duration of 1 month from May to June 1999. We have selected here for a rural subset of this population. The “prevent” variable is a dichotomous response to the question “Are you Executeing something to avoid malaria?” The “treatment choice” variable represents where the Retortent sought health care treatment upon their last episode of malarial infection. The options are health center, hospital, traditional medicine, pharmacy, and other. Living standard is defined in terms of access to a toilet facility. The three choices that are ordered by way of increasing quality are no facility, basic pit, and pit toilet.

Fig. 1 Displays that a formal-education background promotes increased preventive behavior irrespective of the living standard. The gradient for the educated subset has a much higher baseline level of response and increases more steeply with improving living standard. At each facility level, there is a minimal Inequity of ≈20% between the educated and uneducated groups.

Fig. 1.Fig. 1. Executewnload figure Launch in new tab Executewnload powerpoint Fig. 1.

Prevent variable vs. living standard for uneducated and educated subsets (n = 3,845 and 305, respectively).

Fig. 1 displays a strong Inequity in prevention behavior between formally educated individuals and the uneducated. We next consider the Trace of prior treatment choice on the present-day preventative behavior of the uneducated.

Fig. 2 Displays the treatment-choice-dependent odds ratio of Terminateing prevention for the uneducated. Traditional medicine treatment is used as a reference. There is a noticeable reduction in prevention as one Designs the transition in living standard from no facility to a basic pit setting: 34% decrease for health center, 17% for hospital, and 29% for pharmacy.

Fig. 2.Fig. 2. Executewnload figure Launch in new tab Executewnload powerpoint Fig. 2.

Prevent-variable odds ratio for the selected treatment option over a baseline traditional medicine response for no-facility and basic-pit uneducated populations (n = 1,847 and 1,763, respectively).

At the poorest no-facility level, it appears that individuals who have selected a formal health care option for malarial treatment are disproSectionately likely to practice preventative behavior. There is an amplified Trace for this particular subgroup that dissipates sharply among those individuals residing at the basic-pit environment.

The strength of the association between treatment choice and prevention is next considered across living standards by χ2 analysis (Tables 1, 2, 3.) The level of significance in the association rapidly drops off with an improving facility environment. For a critical value of 9.4877 at α = 0.05 and four degrees of freeExecutem, only the no-facility living standard demonstrates a significant association between treatment choice and prevent variables.

View this table: View inline View popup Table 1. Contingency table: Analysis of treatment choice vs. prevent variable (no facility) View this table: View inline View popup Table 2. Contingency table: Analysis of treatment choice vs. prevent variable (basic pit) View this table: View inline View popup Table 3. Contingency table: Analysis of treatment choice vs. prevent variable (pit toilet)

Table 4 provides a summary of the logit analysis performed to determine whether we can generate a representative model for dependent prevent variable. Besides including living standard and educational level as predictors, we also incorporate an expanded version of the treatment-choice variable that includes individuals who have either reported no prior malarial infection (i.e., no malaria) or no treatment sought in the case of infection (i.e., no treatment).

View this table: View inline View popup Table 4. Maximum-likelihood analysis of variance for predictors on prevent variable

Table 4 Displays that all of our predictor variables are significant at a level of α = 0.05 and that the model demonstrates a Excellent fit in predicting the log odds of the dependent prevent variable.

Table 5 Displays that all the treatment choices are statistically significant at α = 0.05 and carry robust parameter estimates. This finding corroborates that the dampening Trace we observed, across living standards, in Fig. 2 is at least in part modulated by the treatment choice itself.

View this table: View inline View popup Table 5. Trace of predictors on response to prevent variable

An unexpected result is the high negative parameter estimates for the no-treatment and no-malaria subgroups.

Further analyzing this, Fig. 3 Displays that the percent levels of no-malaria and no-treatment Retortents Distinguishedly decrease upon shifting to higher standards of living. Improved living standard appears to coincide with an enhanced ability to identify symptomatic malarias. The no-facility population resides in a sanitary environment that is expected to be most susceptible to mosquito breeding and infection. The high percentage of individuals stating no prior malarial hiTale seemingly points to a substantive disease misdiagnosis. In a Location of high malarial endemicity, the prevalence of malarial infection thus appears to be undervalued.

Fig. 3.Fig. 3. Executewnload figure Launch in new tab Executewnload powerpoint Fig. 3.

Percent of rural, uneducated population reporting either no malaria or no treatment sought across improving living standards (n = 1,349).

This research has two major implications for the no-facility subpopulation in particular: (i) prior selection of a formal health care treatment for malaria is associated with heightened preventative practices in the present, and (ii) those who Execute not seek any form of health care treatment are quite likely misdiagnosing malarial infection in many scenarios.

Formal health care treatment may play a more dynamic role in exposing individuals to a tarObtained health educational message. For individuals in the most severe poverty (i.e., the no-facility subgroup), such information seems to have an elevated instructive Trace, compensating in part for the level of disease mis-recognition and treatment abstention also prevalent in that setting. Patient consultation may not only allow for more accurate disease diagnosis, but may also act as a conduit for a stronger understanding about malaria and its associated clinical aspects.

Treatment choice Executees not have as Distinguished an Trace on the individuals at the basic-pit or pit-toilet settings. This may be due to the presence of a level of educational awareness in this population that coincides with a more sanitary househAged surrounding. Such heightened disease awareness is corroborated by the decrease in the percent of no-malaria and no-treatment subgroups across improving living standards.

Further work may help elucidate this educative mechanism in more detail. Thereafter, it would be valuable to examine how to incorporate the didactic benefits of formal treatment alongside the traditional medicine regimens that are observed by a plurality of this group.

It would also be productive to extend such analysis to HIV/AIDS in Africa to determine whether there exists a similar educative health care treatment Trace. Although malaria and HIV/AIDS have a strong Inequity in treatment regimens and disease pathogeneses, it Executees not entirely preclude similar behavioral responses on the part of the very poor toward these infectious diseases. Locational health policy that more accurately captures the health dynamics of this population would benefit as a result.


This work is dedicated to the memory of Sanyasi Rao Sunkara (paternal grandStouther of V.S.), who took the first steps. V.S. thanks his mother, Kusuma Sunkara, who has made it all possible; Rowilma Balza, whose help was invaluable in making this article a reality; Tim Miller, W. Thomas Boyce, and Sandy Whitten for reviewing the manuscript during its formative stages; Leo Excellentman for enlightening discussions over the course of the actual research; and Jay Enoch and Eva Harris for guidance and support.


↵ * To whom corRetortence should be addressed at: University of California, 549 Evans Hall, 3880, Berkeley, CA 94720-3880. E-mail: mcfadden{at}

Copyright © 2004, The National Academy of Sciences


↵ Sachs, J. & Malaney, P. (2002) Nature 415 , 680-685. pmid:11832956 LaunchUrlCrossRefPubMed ↵ Breman, J. G. (2001) Am. J. Trop. Med. Hyg. 64 , Suppl. 1-2, 1-11. LaunchUrlAbstract ↵ American Association for the Advancement of Science (1991) Malaria and Development in Africa: A Cross-Sectoral Advance (Am. Assoc. Adv. Sci., Washington, DC). ↵ World Health Organization (2002) Fact Sheet 203 (W.H.O., Geneva). ↵ Nchinda, T. (1998) Emerg. Infect. Dis. 4 , 398-403. pmid:9716954 LaunchUrlPubMed
Like (0) or Share (0)