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Keywords:

  • access to health care;
  • concentration index;
  • Côte d'Ivoire;
  • health inequities;
  • household assets ownership;
  • parasitic infections

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

Differences in the state of health between rural and urban populations living in Africa have been described, yet only few studies analysed inequities within poor rural communities. We investigated disparities in parasitic infections, perceived ill health and access to formal health services among more than 4000 schoolchildren from 57 primary schools in a rural area of western Côte d'Ivoire, as measured by their socioeconomic status. In a first step, we carried out a cross-sectional parasitological survey. Stool specimens and finger prick blood samples were collected and processed with standardized, quality-controlled methods, for diagnosis of Schistosoma mansoni, soil-transmitted helminths, intestinal protozoa and Plasmodium. Then, a questionnaire survey was carried out for the appraisal of self-reported morbidity indicators, as well as housing characteristics and household assets ownership. Mean travel distance from each village to the nearest health care delivery structure was provided by the regional health authorities. Poorer schoolchildren showed a significantly higher infection prevalence of hookworm than better-off children. However, higher infection prevalences of intestinal protozoa (i.e. Blastocystis hominis, Endolimax nana and Iodamoeba bütschlii) were found with increasing socioeconomic status. Significant negative associations were observed between socioeconomic status and light infection intensities with hookworm and S. mansoni, as well as with several self-reported morbidity indicators. The poorest school-attending children lived significantly further away from formal health services than their richer counterparts. Our study provides evidence for inequities among schoolchildren's parasitic infection status, perceived ill health and access to health care in a large rural part of Côte d'Ivoire. These findings call for more equity-balanced parasitic disease control interventions, which in turn might be an important strategy for poverty alleviation.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

It is estimated that the current global burden of malaria is 46.5 million disability-adjusted life years (DALYs) (WHO 2004). Strikingly, more than half of this burden is concentrated among the poorest 20% of people, whereas only 0.2% of the total DALYs caused by malaria are lost by the richest 20% (Gwatkin & Jones 2000). Soil-transmitted helminthiasis might be responsible for up to 39.0 million DALYs lost, and schistosomiasis for 4.5 (WHO 2002; Utzinger & Keiser 2004). For sub-Saharan Africa, it is estimated that infections with Plasmodium, schistosomes, soil-transmitted helminths and other parasites are responsible for 42.5% of the total DALYs lost in this region (Murray & Lopez 1996). The poorest of the poor are at particular high risks for infections, and hence associated morbidity and mortality, through a multiplicity of factors, including polluted water, lack of improved sanitation, crowding, poor housing conditions, high exposure to pathogens and disease vectors, and poor coverage to other essential services, e.g. education (Victora et al. 2003; World Bank 2004). Consequently, in areas where such conditions are common, they delay the social and economic development (WHO 2001; Jha et al. 2002; World Bank 2004).

In a study in Madagascar, Kightlinger et al. (1998) could show that children from poorer families had higher Ascaris lumbricoides worm burdens. Other studies investigated the relationship between infections with Schistosoma mansoni, soil-transmitted helminths or Plasmodium and socioeconomic variables and found significant associations (Tshikuka et al. 1996; Kightlinger et al. 1998; Biritwum et al. 2000; Carneiro et al. 2002). However, these studies employed slightly different methodologies rendering comparisons between epidemiological settings difficult. In recent studies estimations of wealth have been made without expenditure or consumption data. Instead, data on household assets ownership (e.g. possession of a radio or a television) and housing characteristics (e.g. type of walls and roofing material) are used to construct an asset index, which is used as proxy for wealth (Gwatkin et al. 2000; Filmer & Pritchett 2001; Armstrong Schellenberg et al. 2003; Brooker et al. 2004). Using this methodology, Filmer (2002) investigated the relationship of fever incidence, as proxy for malaria, with household poverty and found a weak but significant positive association across different African countries.

Unfortunately, in many parts of the world, the poorest people are the least likely to benefit from health interventions and adequate service delivery (World Bank 2004). For example, studies have demonstrated that children from the poorest households are less likely to be reached by preventive interventions such as the supplementation of vitamin A or insecticide-treated nets (ITNs) (Hanson & Jones 2000; Victora et al. 2003). A recent study conducted in a rural area of the United Republic of Tanzania found that care-seeking behaviour is worse among poorer families and children from poorer families made significantly longer journeys to attend the nearest health facility. Interestingly, although, reported morbidity indicators were not significantly associated to the socioeconomic status of study participants (Armstrong Schellenberg et al. 2003). For this rural setting it was thus concluded that the main difference in the poorest and the better-off is the unequal access to adequate treatment.

During the school year 2001/2002 more than 4000 schoolchildren in a rural area of Côte d'Ivoire were screened for Plasmodium, S. mansoni, soil-transmitted helminths and intestinal protozoa. Children were also interviewed about perceived morbidity indicators, housing characteristics and a set of assets in their homes. Our aim was to investigate disparities in parasitic infections, schoolchildren's self-reported ill health (i.e. symptoms and diseases) and access to health care in relation to children's socioeconomic status. We also examined associations between parasitic infections and individual household assets, habits of hand washing and location of residency. Our findings may facilitate a more equity-balanced planning of parasitic disease control interventions in western Côte d'Ivoire, and elsewhere in sub-Saharan Africa, with the objective to reach those at highest need.

Study area and population

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

The study was carried out in the region of Man, western Côte d'Ivoire, between October 2001 and July 2002. This mountainous region has distinct climate conditions within Côte d'Ivoire. The majority of the population is engaged in subsistence agriculture. Coffee and cocoa are the predominant cash crops providing an important income source for the people (Utzinger et al. 2000). Our own preceding epidemiological studies in this region have shown that multiple species parasitic infections are very common (Keiser et al. 2002a,b; Raso et al. 2004). The study presented here consists of two surveys: first, a comprehensive parasitological survey in all primary schools of two education inspections in the region of Man that fulfilled our inclusion criteria; secondly, a questionnaire survey to collect data on self-reported morbidity, housing characteristics and household assets ownership to estimate schoolchildren's socioeconomic status.

Parasitology: field and laboratory procedures

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

After the two education officers were contacted and the aim and procedures of the study were explained, they provided our research team with maps and lists of all primary schools. Schools situated in the town of Man and schools in rural areas with <100 pupils registered were excluded from this survey. The remaining 57 schools were enrolled. Next, school directors were informed by the education officers about our study and invited to prepare class lists with name, age and sex of each child. Subsequently, only schoolchildren attending grades 3–5 were considered.

During several weeks the research team visited one school after the other in the morning and distributed plastic containers to all study participants. The children were asked to return the containers with a small portion of their own stool, and unique identification numbers were attached to the filled containers. Then a finger prick blood sample was taken from each child. Thin and thick blood smears were prepared on microscope slides and immediately marked with the child's identification number. Finally, geographical coordinates of each school were determined using a hand-held Magellan 320 global positioning system (GPS; Thales Navigation, Santa Clara, CA, USA).

Stool specimens and blood smears were transferred to the central laboratory in the town of Man. Small portions of stool (1–2 g) were placed into small plastic tubes containing a 10 ml solution of sodium–acetic acid–formalin (SAF), and shaken rigorously for 20–30 s. Then, a single 42 mg Kato-Katz thick smear was prepared from each stool specimen on microscope slides (Katz et al. 1972). After a clearing time of 30–45 min they were examined by one of four experienced laboratory technologists under a light microscope at low magnification. The numbers of ova of S. mansoni, A. lumbricoides, hookworm, and Trichuris trichiura were counted and recorded separately. The blood smears were stained with Giemsa (Hira & Behbehani 1984).

The SAF-conserved stool specimen and Giemsa-stained blood smears were forwarded to a reference laboratory in Abidjan. They were processed with standardized, quality-controlled methods and analysed by four experienced laboratory technicians under a light microscope at high magnification. Presence or absence of the following intestinal protozoa was recorded separately: Blastocystis hominis, Chilomastix mesnili, Entamoeba coli, Ent. hartmanni, Ent. histolytica/Ent. dispar, Endolimax nana, Iodamoeba bütschlii and Giardia duodenalis. Blood smears were examined for species-specific density of Plasmodium, assuming for a standard white blood cell count of 8000/μl blood, according to standard procedures (see for example N'Goran et al. 2003).

Questionnaire: self-reported morbidity and socioeconomic status

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

The questionnaire employed in this study was a further developed version of an existing one, which had been used previously in the region of Man for the rapid assessment of individuals and communities at highest risk of S. mansoni infections (Utzinger et al. 2000). It included questions on symptoms and diseases that are common in this epidemiological setting. The recall period was 1 month. We added, for the first time, a section on socioeconomic indicators. After pre-testing in a nearby school that was not enrolled in the present study, the questionnaire was readily adapted and then distributed to all 57 schools. The final questionnaire consisted of three main sections, namely (i) a list of 10 symptoms (headache, hot body, abdominal pain, dysentery, blood in urine, blood in stool, breathing problems, vomiting, lethargy and diarrhoea), (ii) a list of seven diseases (skin disease, eye disease, schistosomiasis, worms, malaria, malnutrition and cold) and (iii) a list of 12 socioeconomic indicators (wearing shoes, sleeping under a bednet, living in a cement house, living in a house with electricity, and the household assets soap, radio, television, refrigerator, fan, bicycle, motorbike and car). Two additional questions were asked, namely (i) ‘Do you live inside or outside the main village?’ and (ii) ‘Do you wash your hands after defecation?’

A separate sheet of detailed instructions and copies of printed class lists accompanied the questionnaire. Teachers were instructed to interview children individually in an empty class room, and to record their answers as ‘yes’, ‘no’ and ‘don't know’, whereas ‘don't know’ was treated as a ‘no’ answer.

Treatment

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

At the end of the parasitological survey all schoolchildren were treated against an overall fee of FCFA 200 (approximately US$0.35) according to the existing treatment schedule recently developed by the regional health authorities. In brief, this fee covers the transport costs of the designated health worker to the schools and the costs of the drugs, namely praziquantel for treatment of S. mansoni, and albendazole for treatment of soil-transmitted helminth infections. Standard doses are administered according to the World Health Organization (WHO 2002). Children who complained of malaria-related symptoms and had an axillary temperature ≥37.5 °C were administered Nivaquine® and paracetamol.

Analyses

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

Data were double entered and validated with EpiInfo v. 6.04 (Centers for Disease Control and Prevention, Atlanta, GA, USA). All statistical analyses were performed with stata v. 8.0 (Stata Corporation, College Station, TX, USA). Only participants who had complete parasitological data records (one Kato-Katz thick smear, one SAF-conserved faecal sample, and one blood smear), or complete results from the questionnaire survey, or both, were included in the final analyses. The information on mean travel distances from the study villages to the nearest formal health service was employed for the spatial analysis of access to health care.

Schoolchildren were subdivided into two age groups, namely (i) 6–10 years and (ii) 11–16 years. Infections with hookworm and S. mansoni were further stratified into light, moderate or heavy infection intensities, according to thresholds set forth by WHO (2002). Infections with P. falciparum were stratified into three intensity categories, namely (i) 1–500, (ii) 501–5000 and (iii) >5000 parasites/μl of blood.

For the calculation of schoolchildren's socioeconomic status, an household asset-based approach was adopted, which proved valid for rapidly estimating household wealth and income during health surveys carried out in rural African settings (Morris et al. 2000). Principal component analysis was used to define household asset weights, whereby missing values were replaced by the mean of the respective asset. Household assets used in this survey had only dichotomous character. The procedure of this analysis was carried out according to technical notes put forward by the HNP/Poverty Thematic Group of the World Bank (Gwatkin et al. 2000). The first principal component explained 24.1% of the variability and gave greatest weight to living in households possessing a television (0.45), followed by the presence of a fan (0.42) and a refrigerator (0.39). After standardization of these weighed asset variables, living in households possessing a car had the highest scores (1.62), followed by the presence of a refrigerator (1.57), fan (1.38), motorbike (1.01) and television (0.88). Lowest scores were attached to households without a radio (−0.31) and without electricity (−0.31). The asset scores were summed to a total score for each schoolchild and the children ranked according to their total score. Thereafter, individuals’ total scores were divided into wealth quintiles, as follows: (i) poorest, (ii) very poor, (iii) poor, (iv) less poor and (v) least poor.

Chi-square statistics were used to test for associations between a particular parasitic infection, polyparasitism and single and multiple self-reported morbidity indicators with sex and age group. The concentration index (CI), as proposed by Wagstaff et al. (1991), was used to measure inequities in parasitic infection prevalence and intensities, and self-reported morbidity indicators (http://www.worldbank.org/poverty/health/wbact/health_eq.htm) related to schoolchildren's socioeconomic status. One of the strengths of the CI is that it facilitates examination of the direction of the association. The association between socioeconomic status with the presence or absence of a formal health service in the village, and the nearest distance to such services was also measured by the CI. Statistical significance was shown by the standard error (SE) of the measured inequality. Kruskal–Wallis tests were used to compare the number of multiple species parasitic infections or multiple self-reported morbidity indicators between the five socioeconomic strata.

To investigate the relationship of any single parasite with household assets, location of residency and habits of hand washing after defecation, we fitted logistic regressions for each parasite species. The covariates used were the set of household assets, location of residency and habits of hand washing after defecation. The models were adjusted for sex and age group whenever necessary. Covariates were included at a significance level of 0.2. Covariates which were not significantly related to the parasite under investigation, were removed in a stepwise backward elimination procedure. Odds ratios (OR), adjusted for sex and age group, were computed for associations with P-values <0.05, including 95% confidence intervals.

Study compliance and operational results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

From 5448 schoolchildren who were registered on the class lists in grades 3–5 in the 57 schools, 5019 were present during the cross-sectional parasitological survey. Figure 1 shows that among these children, 264 lacked a Kato-Katz thick smear and another 419 had no SAF-conserved faecal sample, primarily because of insufficient amounts of stool being collected. Another 294 children missed finger prick blood collection. Consequently, 4042 schoolchildren had complete parasitological data records, owing to an overall compliance of 74.2%. There were 2444 boys and 1598 girls with 2192 children aged 6–10 years and 1850 with an age of 11–16 years. One school failed to return the questionnaires. Overall, 1072 schoolchildren were either absent or were not interviewed by the teachers, resulting in 4376 (80.3%) schoolchildren being interviewed (for sex and age see Figure 1).

image

Figure 1. Study cohort with an emphasis on those schoolchildren who had either complete parasitological data, or complete questionnaire data, or both.

Download figure to PowerPoint

Parasitic infections

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

Table 1 summarizes the results from the cross-sectional parasitological survey. Examination of a single Kato-Katz thick smear revealed infection prevalences with S. mansoni, hookworm, A. lumbricoides and T. trichiura of 38.7%, 30.5%, 2.2% and 1.3% respectively. The most frequent intestinal protozoa, as examined by a formol-ether concentration method, were End. nana (82.6%) and Ent. coli (74.9%). Pathogenic intestinal protozoa, namely G. duodenalis and Ent. histolytica/Ent. dispar, were found in 17.4% and 11.0% of the children respectively. Infection with P. falciparum was common; microscopic analysis of a single blood smear revealed a point prevalence of 64.0%. Infections with P. malariae and P. ovale were rare; observed prevalences were 3.0% and 0.2% respectively.

Table 1.  Parasitic infections, stratified by sex and two age groups, among 4042 schoolchildren in the region of Man, western Côte d'Ivoire
ParasiteTotal (%)SexAge group
FemalesMalesχ2P-value6–10 years11–16 yearsχ2P-value
S. mansoni38.736.040.58.190.00436.441.410.570.001
Soil-transmitted helminths
 Hookworm30.522.235.986.49<0.00128.932.35.480.019
 A. lumbricoides2.22.61.82.840.0922.41.81.600.206
 T. trichiura1.31.11.41.030.3101.31.30.010.955
Intestinal protozoa
 End. nana82.681.782.90.910.33982.682.60.010.998
 Ent. coli74.976.274.12.090.14875.074.90.010.921
 G. duodenalis17.416.717.90.920.33718.516.14.060.044
 I. bütschlii17.217.517.00.200.65617.217.20.010.940
 C. mesnili15.115.215.10.030.85414.815.60.480.487
 B. hominis10.511.010.20.770.37910.710.30.180.676
 Ent. histolytica/Ent. dispar11.010.611.20.280.5979.912.36.000.014
 Ent. hartmanni7.17.07.20.130.7216.97.40.260.608
Plasmodium
 P. falciparum64.063.164.50.760.38567.459.825.07<0.001
 P. malariae3.02.63.21.060.3023.52.44.130.042

Boys were significantly more likely to be infected with S. mansoni than girls (40.5%vs. 36.0%; χ2 = 8.19, degree of freedom (d.f.) = 1, P = 0.004). Hookworm infections were much more prominent among boys than girls (35.9%vs. 22.2; χ2 = 86.49, d.f. = 1, P < 0.001). None of the other parasites showed a significant association with sex.

With regard to age, older children had significantly higher infection prevalences with S. mansoni (χ2 = 10.57, d.f. = 1, P = 0.001), hookworm (χ2 = 5.48, d.f. = 1, P = 0.019) and Ent. histolytica/Ent. dispar (χ2 = 6.00, d.f. = 1, P = 0.014). However, younger children were significantly more likely to be infected with P. falciparum (χ2 = 25.07, d.f. = 1, P < 0.001), P. malaria (χ2 = 4.13, d.f. = 1, P = 0.042) and G. duodenalis (χ2 = 4.06, d.f. = 1, P = 0.044).

Polyparasitism was very common, as four children of five harboured ≥3 parasites concurrently. Overall, 308 (7.6%) children had six, 88 (2.2%) children had seven, seven children had eight and two children had nine parasites. Only eight children were free of parasitic infections. Polyparasitism was significantly associated with sex (χ2 = 24.19, d.f. = 9, P = 0.004), but not with age (χ2 = 6.93, d.f. = 9, P = 0.644).

Self-reported morbidity

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

Table 2 shows the frequencies of self-reported morbidity indicators among schoolchildren, stratified by sex and age groups. The most frequently reported symptom was headache (66.5%), followed by hot body (57.9%) and abdominal pain (56.2%). Girls reported significantly more often to have had a headache, abdominal pain or diarrhoea in the 1 month preceding the interview. Older children reported significantly more often to have suffered from headache and abdominal pain. The most frequently reported diseases were worms (45.2%) and malaria (45.1%). While sex was significantly associated with self-reported worms, skin disease and eye disease, no significant associations were found with age.

Table 2.  Self-reported morbidity indicators among 4376 schoolchildren, stratified by sex and two age groups, in the region of Man, western Côte d'Ivoire
Morbidity indicatorTotal (%)SexAge group
FemalesMalesχ2P-value6–10 years11–16 yearsχ2P-value
Symptoms
 Headache66.571.363.429.77<0.00163.869.917.56<0.001
 Hot body57.959.756.73.790.05257.658.30.200.656
 Abdominal pain56.258.954.58.340.00454.758.25.450.020
 Lethargy46.545.846.90.480.48845.447.82.570.109
 Vomiting40.641.639.21.180.27641.539.51.770.183
 Diarrhoea33.836.332.27.750.00534.333.30.470.491
 Blood in stool30.932.030.21.450.22830.930.90.010.995
 Dysentery29.629.030.00.500.48029.929.30.210.647
 Breathing problems14.114.613.70.820.36513.614.71.130.289
 Blood in urine8.27.58.71.840.1758.97.42.990.084
Diseases
 Worms45.248.642.814.32<0.00145.644.70.340.559
 Malaria45.145.644.80.240.62644.346.21.540.214
 Cold32.632.932.40.140.70433.731.32.830.092
 Malnutrition25.724.826.31.350.24624.727.02.910.088
 Skin disease20.218.721.34.340.03720.719.70.620.431
 Eye disease15.917.315.04.340.03716.115.70.130.719
 Schistosomiasis14.613.715.21.810.17815.513.63.160.075

Only 325 (7.4%) schoolchildren reported not suffering from any of the morbidity indicators investigated. In contrast, more than two-thirds of the schoolchildren reported at least four different symptoms or diseases concurrently. There were 28 children reporting 16, and five children reporting 17 symptoms and diseases. Age was positively associated with the total number of reported morbidity indicators (χ2 = 33.59, d.f. = 17, P = 0.009).

Housing characteristics, household assets ownership and wealth quintiles

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

Table 3 displays the wealth quintiles for each household asset. Most of the schoolchildren had shoes (92.4%) and soap (87.5%). About four of 10 of the school-attending children lived in households with electricity, but only 0.2% of these children belonged to the poorest households, while 91.8% of the least poor had electricity at home. While more than half of the schoolchildren reported to have a radio at home, only one in five children had a television. None of the children of the poorest households slept under bednets, while 22.4% of the least poor gave a positive answer. Finally, none of the children of the poorest and very poor quintiles lived in households that owned a television, fan, refrigerator, motorbike or a car.

Table 3.  Wealth quintiles of 12 different household assets among 4376 schoolchildren in the region of Man, western Côte d'Ivoire
Household asset variableTotal (%)Wealth quintiles (%)
Poorest (n = 864)Very poor (n = 887)Poor (n = 867)Less poor (n = 878)Least poor (n = 880)
Wears shoes92.486.790.893.094.896.7
Has soap87.582.280.687.394.093.3
Has radio57.50.774.149.373.988.3
Has electricity42.20.27.133.877.691.8
Lives in a cement house35.51.36.844.745.778.8
Has television20.80.00.00.721.980.7
Has bicycle16.40.25.417.719.538.9
Sleeps under a bednet10.40.04.49.216.122.4
Has fan8.40.00.00.00.541.4
Has refrigerator6.00.00.00.00.029.7
Has motorbike6.00.00.00.56.722.7
Has car1.10.00.00.00.25.5

With regard to age, strong positive associations were found for wearing shoes (χ2 = 13.37, d.f. = 1, P < 0.001) and having soap at home (χ2 = 12.62, d.f. = 1, P < 0.001). However, negative associations were found for living in a house with electricity (χ2 = 5.04, d.f. = 1, P = 0.025), built with cement (χ2 = 7.01, d.f. = 1, P = 0.008), and the possession of a refrigerator (χ2 = 6.26, d.f. = 1, P = 0.012) and a television (χ2 = 6.79, d.f. = 1, P = 0.009). Girls were significantly more often associated with the assets bicycle, shoes, soap and fan, as well as having electricity at home and living in a cement house.

Associations between parasitic infections and household assets, location of residency and hygiene behaviour

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

Table 4 summarizes all significant associations between a particular parasitic infection and single household assets, location of residency and hygiene behaviour. Those children who reported washing hands after defecation were less likely to have an infection with S. mansoni (OR = 0.82, P = 0.005), C. mesnili (OR = 0.66, P < 0.001) and P. malariae (OR = 0.46, P = 0.001), but more likely to have an infection with G. duodenalis (OR = 1.21, P = 0.014). Sleeping under a bednet was a protective factor against infections with P. falciparum (OR = 0.78, P = 0.041), and showed a borderline significance for P. malariae (OR = 0.36, P = 0.050). Schoolchildren living in houses constructed with cement were less likely to have infections with soil-transmitted helminths.

Table 4.  Significant associations between parasitic infections and household assets, habits of hand washing, and location of residency, as assessed by a stepwise logistic regression analysis. Models were adjusted for sex and two age groups, whenever necessary, among 3374 schoolchildren in the region of Man, western Côte d'Ivoire (values in brackets indicate 95% confidence interval)
ParasiteSignificant associationAdjusted odds ratioP-value
S. mansoniHas bicycle1.42 (1.17–1.72)<0.001
Has soap1.38 (1.10–1.73)0.005
Age group1.22 (1.06–1.41)0.006
Sex0.84 (0.72–0.97)0.017
Washes hands after defecation0.82 (0.72–0.94)0.005
Lives in village0.75 (0.60–0.94)0.012
Has fan0.70 (0.53–0.93)0.013
Soil-transmitted helminths
 HookwormAge group1.17 (1.00–1.36)0.044
Lives in a cement house0.76 (0.64–0.90)0.001
Has soap0.73 (0.59–0.91)0.005
Has fan0.65 (0.47–0.89)0.007
Has motorbike0.64 (0.44–0.91)0.014
Sex0.52 (0.44–0.61)<0.001
 A. lumbricoidesHas soap4.06 (1.27–13.05)0.018
Lives in a cement house0.43 (0.24–0.77)0.005
Intestinal protozoa
 Ent. histolytica/Ent. disparHas soap1.58 (1.09–2.30)0.016
Age group1.28 (1.03–1.59)0.024
 End. nanaHas motorbike1.75 (1.13–2.72)0.013
 I. bütschliiHas fan0.69 (0.48–0.99)0.044
Wears shoes0.56 (0.41–0.76)<0.001
 G. duodenalisHas soap1.49 (1.11–2.02)0.009
Washes hands after defecation1.21 (1.04–1.41)0.014
Age group0.81 (0.67–0.97)0.022
Has motorbike0.66 (0.43–0.99)0.047
 C. mesniliHas soap1.47 (1.08–2.00)0.015
Washes hands after defecation0.66 (0.54–0.80)<0.001
 B. hominisHas bicycle1.49 (1.13–1.95)0.005
Plasmodium
 P. falciparumSleeps under a bednet0.78 (0.62–0.99)0.041
Has bicycle0.75 (0.62–0.92)0.006
Age group0.71 (0.61–0.81)<0.001
Has motorbike0.69 (0.52–0.92)0.013
 P. malariaeHas television1.68 (1.06–2.69)0.029
Sex0.65 (0.41–0.99)0.050
Washes hands after defecation0.46 (0.29–0.73)0.001
Sleeps under a bednet0.36 (0.13–1.00)0.050

Washing hands after defecation was significantly associated to children's socioeconomic status (χ2 = 21.78, d.f. = 4, P < 0.001), but was not associated to the number of parasites harboured. In general, schoolchildren living in the main village belonged significantly more often to the least poor group than those living in settlements outside (χ2 = 13.01, d.f. = 4, P = 0.011). The number of parasites harboured by an individual was not associated to the location of residency.

Association between socioeconomic status and parasitic infections

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

Overall, 3374 schoolchildren had complete parasitological and socioeconomic data, as shown in Figure 1. Table 5 gives an account of the relationships and directions between individual parasites and schoolchildren's socioeconomic status. The prevalence of hookworm infection was significantly higher among poorer schoolchildren when compared with their richer counterparts (CI = −0.0701, SE = 0.0170). However, prevalences of three intestinal protozoa, namely B. hominis (CI = 0.0970, SE = 0.0216), End. nana (CI = 0.0056, SE = 0.0024) and I. bütschlii (CI = 0.0336, SE = 0.0162), were significantly higher in better-off groups.

Table 5.  Frequencies of parasitic infections among 3374 schoolchildren according to their socioeconomic status in the region of Man, western Côte d'Ivoire
ParasiteTotal (%)Wealth quintiles (%)CISE (CI)t-test (CI)
Poorest (n = 676)Very poor (n = 663)Poor (n = 660)Less poor (n = 679)Least poor (n = 696)
  1. t-test is significant. CI, concentration index; SE, standard error.

S. mansoni38.739.241.240.838.734.1−0.02670.0170−1.58
Soil-transmitted helminths
 Hookworm30.533.934.232.429.223.2−0.07010.0268−2.61*
 A. lumbricoides2.22.12.92.03.10.9−0.08730.1101−0.79
 T. trichiura1.40.71.41.51.91.20.08820.08841.00
Intestinal protozoa
 End. nana82.382.180.582.182.883.80.00560.00242.32*
 Ent. coli75.775.676.676.276.373.9−0.00400.0038−1.05
 G. duodenalis17.716.717.819.916.617.40.00070.01460.05
 I. bütschlii17.315.118.116.118.718.40.03360.01622.08*
 C. mesnili15.315.414.217.615.214.4−0.00580.0156−0.37
 B. hominis10.49.37.89.212.113.40.09700.02164.49*
 Ent. histolytica/Ent. dispar11.510.815.210.910.210.6−0.03710.0321−1.16
 Ent. hartmanni7.57.36.29.16.38.60.02910.02861.02
Plasmodium
 P. falciparum64.364.664.669.164.159.3−0.01420.0124−1.15
 P. malariae3.02.23.23.53.13.20.05000.04291.16

Table 6 shows that not only the prevalence of hookworm infection, but also its intensity was significantly associated with schoolchildren's socioeconomic status; poorer children had higher frequencies of light infection intensities than their better-off counterparts (CI = −0.0674, SE = 0.0226). Poorer children also had higher frequencies of light infection intensities of S. mansoni (CI = −0.0465, SE = 0.0117). No statistically significant associations were found for either of these two parasites with regard to moderate or heavy infection intensities.

Table 6.  Different infection intensity thresholds for S. mansoni and hookworm, stratified by socioeconomic status, among 3374 schoolchildren in the region of Man, western Côte d'Ivoire
Infection intensityTotal (%)Wealth quintiles (%)CISE (CI)t-test (CI)
Poorest (n = 676)Very poor (n = 663)Poor (n = 660)Less poor (n = 679)Least poor (n = 696)
  1. t-test is significant. epg, eggs per gram of stool; CI, concentration index; SE, standard error.

S. mansoni
 No infection61.361.058.859.261.366.00.01660.01041.60
 1–100 epg15.617.515.817.014.013.9−0.04650.0117−3.96*
 101–400 epg12.611.115.512.712.711.2−0.01670.0361−0.46
 >400 epg10.510.59.811.112.18.9−0.00800.0315−0.25
Hookworm
 No infection69.566.165.867.670.876.70.03050.00923.34*
 1–2000 epg29.132.432.630.027.822.7−0.06740.0226−2.98*
 2001–4000 epg1.00.91.41.70.80.4−0.12690.1242−1.02
 >4000 epg0.50.60.30.80.60.1−0.12270.1534−0.80

Figure 2 displays the relationship between polyparasitism and socioeconomic status (Kruskal–Wallis H = 15.26, d.f. = 4, P = 0.004). The number of parasites harboured by the least poor schoolchildren was significantly lower than in their poorer peers.

image

Figure 2. Boxplot displaying frequency of parasites among 3374 schoolchildren, stratified by wealth quintiles, in the region of Man, western Côte d'Ivoire.

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Association between socioeconomic status and self-reported morbidity

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

Table 7 shows that 10 of 17 self-reported morbidity indicators were significantly associated with schoolchildren's socioeconomic status. Most of the significant indicators, with the exception of malaria and malnutrition, were reported more often from better-off groups. Self-reported headache, diarrhoea, dysentery, worms, cold, skin diseases and schistosomiasis showed no association with socioeconomic status.

Table 7.  Frequency of self-reported morbidity indicators, stratified by socioeconomic status, among 4376 schoolchildren in the region of Man, western Côte d'Ivoire
Morbidity indicatorTotal (%)Wealth quintiles (%)CISE (CI)t-test (CI)
Poorest (n = 864)Very poor (n = 887)Poor (n = 867)Less poor (n = 878)Least poor (n = 880)
  1. t-test is significant; CI, concentration index; SE, standard error.

Symptoms
 Headache66.563.965.865.771.465.80.01120.00821.37
 Hot body57.952.455.154.862.864.30.04350.00676.48*
 Abdominal pain56.255.451.855.058.160.90.02480.00942.62*
 Lethargy46.538.447.243.147.356.10.06100.02512.43*
 Vomiting40.635.737.740.344.444.90.04940.00707.06*
 Diarrhoea33.833.933.733.534.733.40.00000.00340.00
 Blood in stool30.929.530.328.534.132.20.02380.00673.55*
 Dysentery29.634.129.127.831.026.3−0.03680.0217−1.69
 Breathing problems14.110.812.512.915.518.50.10480.02244.69*
 Blood in urine8.26.67.78.28.99.70.07190.01784.04*
Diseases
 Worms45.245.143.344.647.345.50.00860.00501.72
 Malaria45.147.952.743.840.640.6−0.00010.0092−5.19*
 Cold32.628.037.333.631.033.00.00860.02860.30
 Malnutrition25.731.930.622.523.819.8−0.09650.0175−5.52*
 Skin disease20.219.424.517.021.918.3−0.01940.0261−0.74
 Eye disease15.913.712.515.818.119.40.08570.01147.53*
 Schistosomiasis14.615.114.714.216.013.2−0.01370.0176−0.78

As shown in Figure 3, significant differences were found among the five socioeconomic groups and the mean number of reported symptoms (Kruskal–Wallis H = 22.39, d.f. = 4, P < 0.001) and the number of reported diseases (Kruskal–Wallis H = 19.28, d.f. = 4, P < 0.001).

image

Figure 3. Boxplot displaying self-reported symptom (grey box) and disease (white box) indicators among 4376 schoolchildren, stratified by socioeconomic status, in the region of Man, western Côte d'Ivoire.

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Access to formal health services

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

Figure 4 shows the proportion of schoolchildren belonging to different wealth quintiles in each study village and the spatial location of the formal health services currently in place in the rural parts of the region of Man. A significant association was found between the presence of a healthcare delivery facility in a village and schoolchildren's socioeconomic status. Table 8 shows that the distance to the closest facility is negatively associated to schoolchildren's socioeconomic status; poorer schoolchildren live significantly further away than their richer counterparts.

image

Figure 4. Map displaying the proportion of schoolchildren belonging to different wealth quintiles in each study village of the region of Man, western Côte d'Ivoire. The town of Man is situated in the centre of the study area and is marked as red triangle.

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Table 8.  Travel distance to the nearest health care delivery structure according to wealth quintiles among 4376 schoolchildren in the region of Man, western Côte d'Ivoire (this table does not differentiate between schoolchildren living within a village and those in settlements outside the main village)
Distance to nearest healthcare delivery structure (km)Total (%)Wealth quintiles (%)CISE (CI)t-test (CI)
Poorest (n = 864)Very poor (n = 887)Poor (n = 867)Less poor (n = 878)Least poor (n = 880)
  1. t-test is significant; CI, concentration index; SE, standard error.

<128.021.715.926.936.938.80.15800.02516.31*
1–531.936.833.931.728.628.3−0.05590.0091−6.12*
>540.141.550.241.434.531.9−0.07040.0264−2.66*

The presence of a health care delivery structure in a village was a protective factor against infections with hookworm (OR = 0.83, P = 0.034), Ent. histolytica/Ent. dispar (OR = 0.75, P = 0.025), P. falciparum (OR = 0.84, P = 0.032) and P. malariae (OR = 0.44, P = 0.004). There was also a significant negative association between the presence of a health care facility and infection intensities of P. falciparum (χ2 = 8.81, d.f. = 3, P = 0.032), as well as hookworms (χ2 = 8.34, d.f. = 3, P = 0.040).

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

Our study shows that there are significant disparities in parasitic infections and perceived ill health among schoolchildren living in a vast geographical area of rural Côte d'Ivoire. For example, school-attending children from poorer households had significantly higher prevalences and intensities of infections with hookworms, and harboured more parasite species concurrently than their better-off counterparts. Moreover, schoolchildren living in richer households had better access to formal health services, as measured by travel distance. We employed the CI for measuring inequalities in health, which has been identified as one of only two viable techniques to carry forward such analyses (Wagstaff et al. 1991). Hence, our results are likely to give an accurate picture of current inequalities in health in western Côte d'Ivoire.

Our findings that schoolchildren from the richest quintile harboured significantly fewer parasites than their poorer peers is consistent with results from a study carried out in the city of Lubumbashi, Democratic Republic of the Congo, where polyparasitism with P. falciparum and different helminths was investigated (Tshikuka et al. 1996). There, a significant difference was also apparent between communities of different socioeconomic status, as the poorest people harboured more parasite species than richer ones. Epidemiological surveys conducted in Brazil, Honduras, Madagascar and Panama also revealed significant associations between people's socioeconomic status and infection intensities of hookworm, as well as with A. lumbricoides (Holland et al. 1988; Kightlinger et al. 1998; Smith et al. 2001; Carneiro et al. 2002). Two possible explanations of these findings are offered for discussion. First, the construction material of houses and latrines, particularly the use of cement on floors and slabs, acts as a protective factor for the transmission of soil-transmitted helminths. Previous studies from Panama and Democratic Republic of the Congo already reported significant associations between housing characteristics and infections with soil-transmitted helminths (Holland et al. 1988; Tshikuka et al. 1995). In many parts of the developing world, cement houses are an indicator of wealth, so it is conceivable that these households have pit latrines and, if resources allow, are probably constructed with cement slabs. This in turn prevents environmental contamination with the larval stages of soil-transmitted helminths, hence reduces the risk of infection (Winblad & Kilama 1985; Asaolu & Ofoezie 2003). Consequently, improving housing conditions and sanitation facilities by cementing soils is an important and relatively inexpensive control measure to reduce or prevent transmission of soil-transmitted helminths. Secondly, it is likely that richer population segments have easier access to inexpensive and highly efficacious single dose oral anti-helmintic drugs, e.g. albendazole (Utzinger & Keiser 2004).

Previous work revealed that P. falciparum infections were significantly associated to socioeconomic status, as shown in studies carried out in The Gambia and Democratic Republic of the Congo (Tshikuka et al. 1996; Clarke et al. 2001). However, in the current epidemiological setting of western Côte d'Ivoire the CI revealed no inequity in the prevalence of P. falciparum. This finding might be explained by the high overall infection prevalence of this parasite and the small proportion of schoolchildren who reported to sleep under a bednet (10.4%). Nonetheless, it is noteworthy that there was a clear gradient from 0% bednet coverage among the poorest quintile to 22.4% among the richest quintile. This observation underscores that preventive expenditure is related to socioeconomic status, as repeatedly shown for bednet use (de Savigny et al. 2002; Mushi et al. 2003; Wardlaw 2003). Recent findings from southern United Republic of Tanzania, where coverage rates of ITNs are relatively high, showed that only 8% of the people in the poorest quintile owned bednets, compared with 51% in the best-off quintile (de Savigny et al. 2002). Another study compared bednet use in relation to wealth among children under five and found that in eight of 10 countries of sub-Saharan Africa the richest quintile had a significantly higher proportion of children sleeping under a bednet (Wardlaw 2003). Interviews with a random sample of household chiefs in 25 villages in our study area revealed that the high price of ITNs is a key factor that inhibits their use at a larger scale among these rural populations. Our findings imply that strategies such as social marketing, as it has been successfully implemented in the United Republic of Tanzania, or providing ITNs free to the most vulnerable groups (i.e. pregnant women and young children), could have a highly beneficial effect in increasing access to ITNs in this region, and hence reduce malaria-related morbidity and mortality (Curtis et al. 2003; Guyatt & Ochola 2003; Hanson et al. 2003; Mushi et al. 2003).

We found three intestinal protozoa, namely B. hominis, End. nana and I. bütschlii, to be positively associated to socioeconomic status. To our knowledge, these associations are described for the first time for sub-Saharan Africa. These findings might be a consequence of rich–poor differentials in hygiene behaviour or nutritional habits. However, these intestinal protozoa are not pathogenic (End. nana and I. bütschlii) or rarely pathogenic (B. hominis) to humans, hence from a public health point of view, these results are of no significance.

In the current setting, the infection prevalence of S. mansoni was not associated to socioeconomic status. However, after stratification by infection intensities, the CI showed a clear significance contra-poor for light infections. This finding confirms studies from Brazil, where it has been shown that monthly income and several socioeconomic factors were significantly related to S. mansoni infections (Kloos et al. 1998; Bethony et al. 2001). However, other underlying factors that are of a behavioural, environmental, genetic and immunological nature may also play important roles.

The large majority of children interviewed reported suffering from several diseases and/or symptoms in the preceding month, which means that they do not perceive themselves as being healthy. On average, children reported 5–6 morbidity indicators of the 17 included in the questionnaire. Similar results have been reported recently by Moestue et al. (2003) after administration of morbidity questionnaires to several thousand schoolchildren from Ghana, Mozambique and United Republic of Tanzania. An important aspect of our study is that among schoolchildren from a given geographical area, there are significant variations of self-reported morbidity indicators in accordance to children's socioeconomic status. Initially, we were surprised that schoolchildren from better-off households perceive themselves less healthy than poorer children, as the former reported significantly more symptoms concurrently. However, consulting the literature, we noticed that this observation had been made before in many different epidemiological settings; richer people are more likely to complain (for two recent examples see van Doorslaer & Gerdtham 2003; Zere & McIntyre 2003). This might also suggest that schoolchildren from better-off households have higher expectations for their own health that make them more sensitive to distress resulting from the same level of pathology, which they identify as symptoms. Illness experience of children with lower expectations are ignored, and hence not reported as symptoms. Consequently, our findings may suggest that perceived needs are an inadequate guide for preventive and curative interventions. Relying only on symptom self-report may ignore health care needs of poorer segments of the population, despite greater needs based on objective assessment of infection rates. Consequently poorer children could be at an elevated risk of severe disease, because they recognize disease signals less clearly, hence might fail to seek care in time. In turn, advocacy on behalf of this segment of the population is required for a health system to function equitably.

Barriers to access to health care delivery structures can be physical, cost related in terms of travel and treatment expenditures, and capacity related in terms of health facilities being able to meet current and projected demands (Ensor & Cooper 2004; Rosero-Bixby 2004). In the present study area there is only one hospital, situated in the town of Man, and 13 rural healthcare facilities, mainly located in the highest populated villages. Employing demographic data from the 1998 census to estimate the proportion of the population residing in villages with or without formal health services, we found that approximately 40% of the rural population lived more than 5 km away from such services. Interestingly, health care delivery structures were primarily located in villages where the mean socioeconomic status, as measured among school-attending children, was high. It follows that poorer families had longer journeys to the nearest health facilities when seeking care and, consequently, may incur higher travelling costs. The long journeys might further increase the risk of severe morbidity and mortality, i.e. due to malaria or acute respiratory infections, as villagers living far away from health care delivery structures are likely to seek treatment significantly less often than those living nearby (Müller et al. 1998; Becher et al. 2004; World Bank 2004). The poorer may therefore experience a greater vulnerability to the consequences of severe parasitic infections as a result of different health-seeking behaviour. Our findings therefore imply that there is a great need to improve access to early diagnosis and effective treatment for this rural population. The establishment and use of a geographical information system could provide a tool to readily guide interventions, so that access to health care can be improved (Noor et al. 2003, 2004; Rosero-Bixby 2004).

One shortcoming of our study is that the sample of children attending school may not be representative for the whole society in this area. Clearly, there is a sampling bias related to non-enrolled school-age children. In India, for example, it has been shown that on average a rich child was 31% more likely to be enrolled in school than a poor child (Filmer & Pritchett 2001). For the whole of Côte d'Ivoire a similar pattern has been found, and hence similar results can be expected for our study area, although the difference might be smaller in only rural parts of a single region. To address this issue, household surveys are needed. We speculate that the gap currently observed between poor and rich school-attending children in this study area might be even higher following the proposed approach.

In conclusion, some of the parasitic infections investigated here showed clear associations to schoolchildren's socioeconomic status, as assessed by a simple asset-based approach (Morris et al. 2000). However, disease outcomes in this epidemiological setting are also driven by a myriad of other factors, notably behavioural and ecological, which may play equal or even more important roles for transmission. Importantly, better-off children were more likely to live in villages with health care delivery structures in place, and seemed to have better access to preventive measures such as ITNs. Our results call for concerted efforts to reach the most disadvantaged segments of populations in this part of rural Côte d'Ivoire, as well as elsewhere in the developing world. The task ahead is immense, but improving access to preventive and curative medicine, clean water and improved sanitation, coupled with sound hygiene behaviour education, will have significant effects in decreasing the intolerable burden of parasitic diseases, and thereby contribute to poverty alleviation in an equitable and sustainable manner.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References

We thank the education officers of the two school inspections in the region of Man for their excellent collaboration. We are especially grateful to all school directors, teachers and pupils of the 57 schools for their commitment during the parasitological and questionnaire surveys, and to the designated regional health officers for their sustained interest and exemplary collaboration to move this joint research and integrated parasitic disease control programme forward. We are grateful to the laboratory technicians A. Allangba, A. Fondio, K.L. Lohourignon, F. Sangaré, B. Sosthène and M. Traoré for their experience and high-quality work both in the field and behind the bench. This investigation received financial support from the Claire Sturzenegger-Jean Favre Foundation, the Roche Research Foundation through a fellowship to G. Raso, the Swiss National Science Foundation (SNF) through a ‘SNF Förderungsprofessur’ to J. Utzinger (Project No. PP00B-102883) and the Individual Project 4 (IP4) ‘Health and Well-being’ of the NCCR North-South: ‘Research Partnerships for Mitigating Syndromes of Global Change’, which is also funded by the SNF. Finally, we thank M.G. Weiss, D. de Savigny and three anonymous referees for a series of excellent suggestions.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Study area and population
  6. Parasitology: field and laboratory procedures
  7. Questionnaire: self-reported morbidity and socioeconomic status
  8. Treatment
  9. Analyses
  10. Results
  11. Study compliance and operational results
  12. Parasitic infections
  13. Self-reported morbidity
  14. Housing characteristics, household assets ownership and wealth quintiles
  15. Associations between parasitic infections and household assets, location of residency and hygiene behaviour
  16. Association between socioeconomic status and parasitic infections
  17. Association between socioeconomic status and self-reported morbidity
  18. Access to formal health services
  19. Discussion
  20. Acknowledgements
  21. References
  • Armstrong Schellenberg J, Victora CG, Mushi A et al. (2003) Inequities among the very poor: health care for children in rural southern Tanzania. Lancet 361, 561566.
  • Asaolu SO & Ofoezie IE (2003) The role of health education and sanitation in the control of helminth infections. Acta Tropica 86, 283294.
  • Becher H, Müller O, Jahn A, Gbangou A, Kynast-Wolf G & Kouyaté B (2004) Risk factors of infant and child mortality in rural Burkina Faso. Bulletin of the World Health Organization 82, 265273.
  • Bethony J, Williams JT, Kloos H et al. (2001) Exposure to Schistosoma mansoni infection in a rural area in Brazil. II: household risk factors. Tropical Medicine and International Health 6, 136145.
  • Biritwum RB, Welbeck J & Barnish G (2000) Incidence and management of malaria in two communities of different socio-economic level, in Accra, Ghana. Annals of Tropical Medicine and Parasitology 94, 771778.
  • Brooker S, Clarke S, Njagi JK et al. (2004) Spatial clustering of malaria and associated risk factors during an epidemic in a highland area of western Kenya. Tropical Medicine and International Health 9, 757766.
  • Carneiro FF, Cifuentes E, Tellez-Rojo MM & Romieu I (2002) The risk of Ascaris lumbricoides infection in children as an environmental health indicator to guide preventive activities in Caparaó and Alto Caparaó, Brazil. Bulletin of the World Health Organization 80, 4046.
  • Clarke SE, Bøgh C, Brown RC, Pinder M, Walraven GEL & Lindsay SW (2001) Do untreated bednets protect against malaria? Transactions of the Royal Society of Tropical Medicine and Hygiene 95, 457462.
  • Curtis C, Maxwell C, Lemnge M et al. (2003) Scaling-up coverage with insecticide-treated nets against malaria in Africa: who should pay? Lancet Infectious Diseases 3, 304307.
  • van Doorslaer E & Gerdtham U-G (2003) Does inequality in self-assessed health predict inequality in survival by income? Evidence from Swedish data. Social Science and Medicine 57, 16211629.
  • Ensor T & Cooper S (2004) Overcoming barriers to health service access: influencing the demand side. Health Policy and Planning 19, 6979.
  • Filmer D (2002) Fever and its Treatment among the More and Less Poor in Sub-Saharan Africa. World Bank, Washington, DC.
  • Filmer D & Pritchett LH (2001) Estimating wealth effects without expenditure data – or tears: an application to educational enrollments in states of India. Demography 38, 115132.
  • Guyatt H & Ochola S (2003) Use of bednets given free to pregnant women in Kenya. Lancet 362, 15491550.
  • Gwatkin DR & Jones C (2000) The Burden of Disease among the Global Poor: Current Situation, Future Trends, and Implications for Strategy. World Bank, Washington, DC.
  • Gwatkin DR, Rustein S, Johnson K, Pande R & Wagstaff A (2000) Socio-Economic Differences in Health, Nutrition, and Population in the Côte d'Ivoire. HNP/Poverty Thematic Group of The World Bank. World Bank, Washington, DC.
  • Hanson K & Jones C (2000) Social Marketing of Insecticide Treated Mosquito Nets, Tanzania: End of Phase 1 Social and Economic Analysis. Malaria Consortium, London.
  • Hanson K, Kikumbih N, Armstrong Schellenberg J et al. (2003) Cost-effectiveness of social marketing of insecticide-treated nets for malaria control in the United Republic of Tanzania. Bulletin of the World Health Organization 81, 269276.
  • Hira P & Behbehani K (1984) Acetone-fixed, Giemsa-stained thick blood films for the diagnosis of malaria. Annals of Tropical Medicine and Parasitology 78, 7779.
  • Holland CV, Taren DL, Crompton DWT et al. (1988) Intestinal helminthiases in relation to the socioeconomic environment of Panamanian children. Social Science and Medicine 26, 209213.
  • Jha P, Mills A, Hanson K et al. (2002) Improving the health of the global poor. Science 295, 20362039.
  • Katz N, Chaves A & Pellegrino J (1972) A simple device for quantitative stool thick-smear technique in schistosomiasis mansoni. Revista do Instituto de Medicina Tropical de São Paulo 14, 397400.
  • Keiser J, N'Goran EK, Singer BH, Lengeler C, Tanner M & Utzinger J (2002a) Association between Schistosoma mansoni and hookworm infections among schoolchildren in Côte d'Ivoire. Acta Tropica 84, 3141.
  • Keiser J, N'Goran EK, Traoré M et al. (2002b) Polyparasitism with Schistosoma mansoni, geohelminths, and intestinal protozoa in rural Côte d'Ivoire. Journal of Parasitology 88, 461466.
  • Kightlinger L, Seed J & Kightlinger M (1998) Ascaris lumbricoides intensity in relation to environmental, socioeconomic, and behavioral determinants of exposure to infection in children from southeast Madagascar. Journal of Parasitology 84, 480484.
  • Kloos H, Gazzinelli A & Van Zuyle P (1998) Microgeographical patterns of schistosomiasis and water contact behavior; examples from Africa and Brazil. Memórias do Instituto Oswaldo Cruz 93 (Suppl. 1), 3750.
  • Moestue H, Mahumane B, Zacher A et al. (2003) Ill-health reported by schoolchildren during questionnaire surveys in Ghana, Mozambique and Tanzania. Tropical Medicine and International Health 8, 967974.
  • Morris SS, Carletto C, Hoddinott J & Christiaensen LJM (2000) Validity of rapid estimates of household wealth and income for health surveys in rural Africa. Journal of Epidemiology and Community Health 54, 381387.
  • Müller I, Smith T, Mellor S, Rare L & Genton B (1998) The effect of distance from home on attendance at a small rural health centre in Papua New Guinea. International Journal of Epidemiology 27, 878884.
  • Murray CJL & Lopez AD (1996) The Global Burden of Disease: a Comprehensive Assessment of Mortality and Disability from Diseases, Injuries, and Risk Factors in 1990 and Projected to 2020. Harvard University Press, Harvard.
  • Mushi AK, Armstrong Schellenberg JRM, Mponda H & Lengeler C (2003) Targeted subsidy for malaria control with treated nets using a discount voucher system in Tanzania. Health Policy and Planning 18, 163171.
  • N'Goran EK, Utzinger J, Gnaka HN et al. (2003) Randomized, double-blind, placebo-controlled trial of oral artemether for the prevention of patent Schistosoma haematobium infections. American Journal of Tropical Medicine and Hygiene 68, 2432.
  • Noor AM, Zurovac D, Hay SI, Ochola SA & Snow RW (2003) Defining equity in physical access to clinical services using geographical information systems as part of malaria planning and monitoring in Kenya. Tropical Medicine and International Health 8, 917926.
  • Noor AM, Gikandi PW, Hay SI, Muga RO & Snow RW (2004) Creating spatially defined databases for equitable health service planning in low-income countries: the example of Kenya. Acta Tropica 91, 239251.
  • Raso G, Luginbühl A, Adjoua CA et al. (2004) Multiple parasite infections and their relationship to self-reported morbidity in a community of rural Côte d'Ivoire. International Journal of Epidemiology 33, 10921102.
  • Rosero-Bixby L (2004) Spatial access to health care in Costa Rica and its equity: a GIS-based study. Social Science and Medicine 58, 12711284.
  • de Savigny D, Mwageni E, Masanja H et al. (2002) Household wealth ranking and risks of malaria mortality in rural Tanzania. Third MIM Pan-African Malaria Conference, Arusha.
  • Smith HM, DeKaminsky R, Niwas S, Soto RJ & Jolly PE (2001) Prevalence and intensity of infections of Ascaris lumbricoides and Trichuris trichiura and associated socio-demographic variables in four rural Honduran communities. Memórias do Instituto Oswaldo Cruz 96, 303314.
  • Tshikuka JG, Scott ME & Gray-Donald K (1995) Ascaris lumbricoides infection and environmental risk factors in an urban African setting. Annals of Tropical Medicine and Parasitology 89, 505514.
  • Tshikuka JG, Scott ME, Gray-Donald K & Kalumba ON (1996) Multiple infection with Plasmodium and helminths in communities of low and relatively high socio-economic status. Annals of Tropical Medicine and Parasitology 90, 277293.
  • Utzinger J & Keiser J (2004) Schistosomiasis and soil-transmitted helminthiasis: common drugs for treatment and control. Expert Opinion on Pharmacotherapy 5, 263285.
  • Utzinger J, N'Goran EK, Ossey YA et al. (2000) Rapid screening for Schistosoma mansoni in western Côte d'Ivoire using a simple school questionnaire. Bulletin of the World Health Organization 78, 389398.
  • Victora CG, Wagstaff A, Armstrong Schellenberg J, Gwatkin D, Claeson M & Habicht J-P (2003) Applying an equity lens to child health and mortality: more of the same is not enough. Lancet 362, 233241.
  • Wagstaff A, Paci P & van Doorslaer E (1991) On the measurement of inequalities in health. Social Science and Medicine 33, 545557.
  • Wardlaw T (2003) UNICEF MICS malaria data. Meeting of the RBM Monitoring and Evaluation Reference Group.
  • WHO (2001) Macroeconomics and Health: Investing in Health for Economic Development. World Health Organization, Geneva.
  • WHO (2002) Prevention and Control of Schistosomiasis and Soil-Transmitted Helminthiasis: Report of a WHO Expert Committee. World Health Organization, Geneva. WHO Technical Report Series No. 912.
  • WHO (2004) The World Health Report 2004 – Changing History. World Health Organization, Geneva.
  • Winblad U & Kilama W (1985) Sanitation Without Water. MacMillan, London.
  • World Bank (2004) World Development Report 2004: Making Services Work for Poor People. World Bank, Washington, DC.
  • Zere E & McIntyre D (2003) Equity in self-reported adult illness and use of health service in South Africa: inter-temporal comparison. Journal of Health, Population, and Nutrition 21, 205215.