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Mapping Xerophthalmia in Mali: Results of a NationalSurvey on Regional Distribution and Related RiskFactorsJean-Francois Schémann MD, PhDa, Denis Malvy MD, PhDb, Germain Zefack MDc, LamineTraoré MDc, Doulaye Sacko MDd, Bamani Sanoussi MDd, Albert A. Banou MDd, Omar BoréMDd, Sidi Coulibaly MDd & Mohamed el Moutchaidine MDd

a IRD (Institute Research for Development), Dakar, SENEGAL (J.-F.S.), EA 3677b René-Labusquière Institute (Tropical Medicine and Hygiene Branch), University Victor-Segalen Bordeaux, Bordeaux, FRANCE (D.M.)c IOTA (African Institute of Tropical Ophthalmology) (G.Z., L.T.)d National Blindness Control Programme (D.S., B.S., A.A.B., O.B., S.C., M.e.M.),Bamako, MALIPublished online: 14 Jun 2013.

To cite this article: Jean-Francois Schémann MD, PhD, Denis Malvy MD, PhD, Germain Zefack MD, Lamine TraoréMD, Doulaye Sacko MD, Bamani Sanoussi MD, Albert A. Banou MD, Omar Boré MD, Sidi Coulibaly MD & Mohamed elMoutchaidine MD (2007) Mapping Xerophthalmia in Mali: Results of a National Survey on Regional Distribution and RelatedRisk Factors, Journal of the American College of Nutrition, 26:6, 630-638, DOI: 10.1080/07315724.2007.10719640

To link to this article: http://dx.doi.org/10.1080/07315724.2007.10719640

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Original Research

Mapping Xerophthalmia in Mali: Results of a NationalSurvey on Regional Distribution and Related RiskFactors

Jean-Francois Schemann MD, PhD, Denis Malvy MD, PhD, Germain Zefack MD; Lamine Traore MD,Doulaye Sacko MD, Bamani Sanoussi MD, Albert A. Banou MD, Omar Bore MD, Sidi Coulibaly, MD,Mohamed el Moutchaidine MD

IRD (Institute Research for Development), Dakar, SENEGAL (J.-F.S.), EA 3677 and Rene-Labusquiere Institute (TropicalMedicine and Hygiene Branch), University Victor-Segalen Bordeaux, Bordeaux, FRANCE (D.M.), IOTA (African Institute ofTropical Ophthalmology) (G.Z., L.T.), National Blindness Control Programme (D.S., B.S., A.A.B., O.B., S.C., M.e.M.),Bamako, MALI

Key words: xerophthalmia, night blindness, Mali

Background: Vitamin A deficiency is recognized to be a severe public health problem in most of thesahelian countries. In Mali, several surveys had been performed at the district or regional level. Unfortunately,they did not cover the entire territory. In the aim of getting a general picture, we collected information on thefrequency and presentation of xerophthalmia among the children under 10 years old population recruited in thesetting of a national survey planned in 1996 and 1997 to evaluate the prevalence and determinants of trachomain Mali.

Methods: In each of the seven regions (with the exception of Bamako district), a random sample of thirtyvillages was taken from the general population. In a subsample of those villages, children under 10 years of agewere examined by an ophthalmologist and their related mothers interviewed. Diagnosis of night blindness andBitot spot occurrence was used for data gathering. Information was collected on village’s infrastructures andfamilial socioeconomic condition. Multiple logistic regression analyses were performed to purpose the bestmodel to describe the relationship between each outcome variable and the various risk factors assessed.

Results: The prevalence of night blindness was estimated to be 1.95% (95% Confidence Interval [CI]: 1.58–2.39)and Bitot spots frequency to be 1.10% (95% CI: 0.83–1.45) among children between 2 and 6 years of age.Xerophthalmia prevalence was 2.51% (95% CI: 2.09–3.00) and nearly similar according to gender (2.68% amongboys and 2.32% among girls). By region of the country and for the same age group, the prevalence ranged from 0.26%in the Kayes region to 7.02% in the Timbuktu region. In Mali, in four regions out of seven, the WHO thresholdsdefining a serious public health problem have been exceeded. The higher prevalence rates were found in Timbuktu,Mopti and Segou. After adjustment to season, the main risk factors were latitude, village size and poor sanitarycoverage. The main protective determinants were education and rice culture.

Conclusions: This presentation illustrates a public health problem concerning vitamin A deficiency among youngchildren in the general population and allows considering the effectiveness of substitutive intervention with vitaminA capsule distribution along with the improvement of vitamin A rich food production and consumption.

INTRODUCTION

The term xerophthalmia covers all eye signs caused byvitamin A deficiency. Vitamin A acts in producing photosen-sitive pigments in the cells of the retina and in the differenti-ation of mucous-secreting epithelial cells. The lack of this

essential nutrient leads to a decrease in night vision or nightblindness, xerosis, keratinisation of the conjunctiva and of thecornea. The ultimate consequence is corneal necrosis and per-foration of the eyeball. Vitamin A deficiency occurs widelyamong children in the developing countries. Many cases ofchildren blindness are due to the irreversible corneal lesions

Address reprint requests to: Dr. JF. Schemann, 9 rue de Calais, 75009 Paris, France. E-mail jfschemann@wanadoo.fr

Journal of the American College of Nutrition, Vol. 26, No. 6, 630–638 (2007)Published by the American College of Nutrition

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caused by fragility of the corneal epithelium: every year, be-tween 5 and 10 million new cases of xerophthalmia are notedamong children, of whom between 250 000 and 500 000 willexperience blindness [1]. Furthermore, numerous studies haveshown a very clear increase in mortality rates among childrenwith vitamin A deficiency [2,3].

In 1995, the World Health Organization (WHO) identified39 countries in which vitamin A deficiency constituted a realpublic health problem [4]. In sub-Saharan African countries, anumber of surveys on vitamin A deficiency have been carriedout. In Mali, the African Institute of Tropical Ophthalmology(IOTA) conducted surveys in various regions through epide-miological evaluation of blindness or more specific studiesduring the 1980s [5–8]. Unfortunately, these surveys did notcover the entire territory and were often conducted using dif-ferent designs. It was therefore not possible to map preciselyxerophthalmia feature in Mali on the basis of these previousreports.

During a national survey planned in 1996 an 1997 to eval-uate the prevalence and determinants of trachoma in Mali, wecollected information on the frequency and presentation ofxerophthalmia among the infant population [9].

POPULATIONS AND METHODS

Outline of the Survey

This survey was conduced in 1996 and 1997. The surveywas based on a two level, cross-sectional random cluster sam-ple design, using procedures suggested by WHO prevention ofblindness programme [10]. Mali was divided into seven admin-istrative regions plus the district of Bamako, the capital. Strat-ification was carried out in these seven regions, excluding theBamako district (Fig. 1). The sampling frame was the list ofvillages drawn up for the 1987 national census [11]. No urbanand rural stratification was effected in these regions. Only theadministrative districts of the capitals of the regions wereexcluded from the sampling frame. For each of the sevenadministrative regions, 30 villages, namely 30 clusters, weredrawn at random in accordance with the principle of probabilityproportional to the population, using the cumulative totalmethod. The design allowed covering 210 villages. In each ofthe selected villages, a sub-sample of households was drawn atrandom in order to provide the necessary number of childrenand women. Starting from an initial household chosen at ran-dom, the neighbouring houses were visited one by one. For therequirement of trachoma survey, 1890 children under 10 yearsold were examined in each regional stratum, i.e. 63 per cluster.In each village, sufficient locations were visited to recruit therequired quota of individuals. All children under 10 years oldfrom the sample were recorded on a register. The survey wasconducted from May to June 1996 for the Mopti and Timbucturegions, from January to February 1997 for Kayes and Gao

regions and from May to July 1997 for the Sikasso, Segou andKoulikoro regions.

The protocol was submitted to and approved by the IOTAethical committee.

Clinical Examination

All children between 0 and 10 years were examined by anophthalmologist with a � 2.5 magnifying glass and a flashlamp. The xerophthalmia outcome was diagnosed when a Bi-tot’s spot, specific corneal lesions or night blindness occurred.Night blindness was documented for children aged over 24months. The mothers were questioned for each of their childrenabout the occurrence of night blindness. Three questions wereasked in this purpose: does the child see well in the daytime?Does the child see well at night? Does the child suffer fromnight blindness (the vernacular term for night blindness wasused)? A child was recognized experiencing night-blindness ifa positive answer was occurring for the two last questions.Children recognized not seeing well during daytime were notincluded. Individuals owing reliable signs of xerophthalmiareceived a pill containing 200 000 units of vitamin A [12].

At the village level, demographic (population size, ethnicgroups), structural (distance to the closest medical centre, theexistence of a school in the village) and economic (primaryagricultural products) information’s were collected.

At the household level (defined as persons sharing a com-mon doorway), the head of household was questioned abouthis/her educational attainment, profession and any history ofhaving lived in a city or abroad. We asked questions oncommon ownership of goods or animals in the household(radios, bikes, motorbikes, carts, ploughs, traction bulls, mon-keys, cattle and small ruminants). By adding the monetaryvalues of all these goods and family possessions a proxyindicator of household wealth was derived and expressed inFCFA (1 FCFA is equivalent to 0.0018 US$). Each mother wasalso asked about her education level.

Data Processing and Analysis

Data were recorded on standardized forms, reviewed dailyfor accuracy and completeness. The administrative, environ-mental and economic data concerning the village were col-lected on a special form. There was also a form for collectingdemographic and environmental information from the head ofeach household. A detailed protocol was drawn up for stafftaking part in the survey. Several training sessions were orga-nized so as to standardize data collection and examinationprocedures. Two teams worked in tandem in each region tocollect the information and have achieved the process throughtwo weeks. Two supervisors paid regular visits to the teammembers.

The night blindness prevalence rate in children was calcu-lated for children aged from 2 to 10 for each region. Bitot spotrate was concurrently calculated in children aged from 0 to 10

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years. A “xerophthalmia” variable, corresponding to a diagno-sis of night blindness and/or Bitot’s spot, was established.Results are presented for the three age groups 0–2 years, 2–6years and 6–10 years.

The seven regions were combined in a single file for anoverall analysis of the situation at the country level. Since thesample size of each stratum was not proportional to the popu-lation of the region under examination, allowing presentingdata able to be directly extrapolated to the country as a whole,it was necessary to weight data for regions according to theirpopulation size. In the concern of adjustment for the clusterrandom sampling design, a sampling design effect of 1.5 wasincorporated in the calculation of confidence limits.

Categorical outcomes, such as prevalence rates were initiallycompared by the chi square test or Fisher’s exact test. Continuous

data across groups were compared by analysis of variance(ANOVA) if normally distributed. The Wilcoxon rank-sum testwas used for non-normal data. Odds ratio (OR), 95% confidentinterval (CI) limits, and p-values were calculated to comparestatus between groups.

Risk factors analysis was conducted among the 2 to 10 yearsindividuals. A univariate analysis was performed and the asso-ciation between the xerophthalmia and each potentially explan-atory determinant was estimated separately.

A series of logistic regression analysis was initially performedand associations between each outcome variable and each expli-cative individual risk factor were examined separately. Then, todetermine whether or not there was evidence of interaction in thedata, the role of the various risk factors on each outcome variablewas investigated. Finally, multiple logistic regression analyses

Fig. 1. Mali Administrative Regions

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were performed to find the best fitting and the best parsimoniousmodel to describe the relationship between each outcome variableand the various risk factors assessed. Each determinant was testedand kept in the multivariate model if it was significantly contrib-utive, considered as a confounding variable when it was associatedwith both the outcome variable and a different risk factor, or as aneffect modifier variable when it interacted with another risk factor.In each model and for each contributive factor, results wereexpressed as odds ratios (or adjusted odds ratios) associated withtheir 95% confidence interval estimate.

The multivariate analysis was conducted with consider-ation of two different survey seasons (May-July and January-February) and three different latitude levels (10.39° to 13°, 13°to 15° and 15° to 20.12°).

The statistical analyses were performed using EPI-INFO6.03 (Center of Disease Control and Prevention, Atlanta, GA,USA) and STATA (Stata Corporation 702 University DriveEast College Station, TX 77840 USA).

RESULTS

Sample Description

In all, 13 490 children aged under 10 were enrolled in theseven regions of Mali as a whole, Due to recruitment con-straints and sampling limits, Koulikoro and Segou contributedto less than the expected number of participants, 1568 and 1366respectively (Table 1). The distribution of children by ageshowed that children aged between two and four were slightlyover represented as compared with the age distribution among

the 1996 Malian general population. Contrarily, children be-tween the ages of eight and ten appeared to be under-repre-sented. Comparing the sample distribution by gender with thatof the general population, we noted a slight over-representationof girls.

Xerophthalmia Prevalence per Region

The prevalence rate of night blindness among childrenbetween 2 and 6 ranged from 0.17% in Kayes to 6.13% inTimbuktu (Fig. 1 and Table 2). This sign affected 1.91% (95%confidence interval [95% CI]: 1.58–2.39) of Malian children ofthis class age. The prevalence of Bitot’s spots ranged from0.26% in Kayes to 1.81% in Segou and was estimated at 1.10%(95% CI: 0.83–1.45) for the whole Mali.

Xerophthalmia, defined as the presence of one and/or theother of these signs affected 2.51% (95% CI: 2.09–3.00) of allchildren aged from 2 to 6 in Mali. Its prevalence ranged from0.26% in the Kayes region to 7.02% in Timbuktu.

Central corneal lesions were rarely encountered and re-ported in only seven cases among a sample of more than 13 000children.

Age and Gender

The distribution of signs of xerophthalmia was studiedaccording to the age of the children enrolled. The highestprevalence rates of night blindness were observed in the two tosix-years age group, where 1.95% of children were affected.The highest Bitot’s spot prevalence rates up to 1.26% werefound in children aged between six and ten.

Distribution of these clinical signs according to gender

Table 1. Regional Distribution of Children Aged under 10 among the Studied Sample and among the General Population

Sample General population*

Number Percentage (%) Number Percentage (%)

RegionKayes 2085 15.5 440689 14.6Koulikoro 1568 11.6 526389 17.5Sikasso 2271 16.8 597426 19.8Segou 1366 10.1 574102 19.0Mopti 2146 15.9 523624 17.4Timbuktu 1962 14.5 189277 6.3Gao-Kidal 2096 15.4 162640 5.4

GenderMale 6280 46. 1532140 49.1Female 7210 53.5 1482007 50.9

Age group (years)0–2 2729 0.20 667337 0.222–4 3797 0.28 641630 0.214–6 3386 0.25 615529 0.206–8 2259 0.17 572215 0.198–10 1319 0.10 517436 0.17Total 13490 100 3014147 100

* 1987 Mali population census.

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showed that xerophthalmia was more frequent in boys than ingirls. Between the ages of 2 and 6, 2.26% of boys experimentednight blindness and only 1.75% of females. Bitot’s spots wereidentified among 1.11% of male children and among 0.98% offemales.

Season and Latitude

Compared with May-June periods, prevalence of xeroph-thalmia was lower in January-February (Table 3). Consideringlatitude, children living in the northern dry areas of Mali weremore likely to present xerophthalmia (Table 3). These twomodifying factors need to be considered simultaneously and tobe entered in the model studying xerophthalmia risk factors.

Wealth

Children living in proper houses or ones with a corrugatediron roof had a lower risk of xerophthalmia (Table 3). Someconsumer goods such mopeds or TV were associated with alower prevalence. Ownership of at least one cow per familywas also linked with a lower prevalence, whereas that of sheepor goats did not appear to have any impact.

The proxy indicator of household’s wealth was inferior forchildren with xerophtahlmia signs (732,022 FCFA as opposedto 810 000 FCFA if no xerophthalmia sign), although notsignificantly (p � 0.17).

Multivariate Analysis of Risk Factors

The size of the village seemed to be an important explan-atory factor. Children from villages with 1000 to 5000 inhab-itants or more than 5000 inhabitants were at higher risk ofxerophthalmia than those living in a village of fewer than 1000inhabitants (OR � 2.36 [95% CI:1.66–3.35] and 4.07 [95%CI:2.58–6.40], respectively) (Table 4).

Distance to the nearest medical centre was also a contrib-uting factor with an increased prevalence of xerophthalmia asthe distance between the village and the medical centerincreased.

Schooling appeared to be a protective factor, as suggestedthe low prevalence level of xerophthalmia when there is aschool in the village (OR � 0.59 [95% CI: 0.43–0.88]) or whenthe child’s mother received previous schooling (OR � 0.57[95% CI: 0.31–1.07]). As far as the children were concerned,attendance at a nondenominational school appeared to be pro-tective in the univariate analysis. Nevertheless, this result wasnot contributive in the multivariate analysis.

The production of millet was associated with high prev-alence rates of xerophthalmia (OR � 1.75 [95% CI: 1.13–2.72]). On the other hand, children living in villages withrice production were less likely to have xerophthalmia signs(OR � 0.69 [95% CI: 0.50 – 0.94]). The availability ofmarket gardens was not significantly associated with a re-duced risk of xerophthalmia.

Table 2. Prevalence Rate (95% CI) of Xerophthalmia Signs by Age Groups and Regions

Region

Night blindness Bitot spots Xerophthalmia

AgePrevalence (%)

[95% CI]Age

Prevalence (%)[95% CI]

AgePrevalence (%)

[95% CI]

Kayes 0–2 0–2 0.50 [0.05–2.59] 0–2 0.50 [0.05–2.59]2–6 0.17 [0.02–0.90] 2–6 0.26 [0.04–1.03] 2–6 0.26 [0.04–1.03]6–10 0.39 [0.04–2.06] 6–10 0.20 [0.002–1.74] 6–10 0.39 [0.04–2.05]

Koulikoro 0–2 0–2 0.47 [0.005–4.11] 0–2 0.47 [0.005–4.11]2–6 2.37 [1.35–4.04] 2–6 1.46 [0.70–2.90] 2–6 2.37 [1.35–4.04]6–10 2.14 [0.92–4.63] 6–10 2.35 [1.06–4.91] 6–10 2.35 [1.06–4.91]

Sikasso 0–2 0–2 0.17 [0.002–1.48] 0–2 0.17 [0.002–1.48]2–6 0.66 [0.21–1.80] 2–6 0.50 [0.16–1.38] 2–6 0.91 [0.41–1.93]6–10 0.68 [0.12–2.70] 6–10 0.22 [0.002–1.90] 6–10 0.86 [0.20–2.89]

Segou 0–2 0–2 1.93 [0.34–7.50] 0–2 1.93 [0.34–7.50]2–6 2.04 [1.11–3.64] 2–6 1.81 [1.07–2.99] 2–6 3.60 [2.31–5.544]6–10 2.21 [0.78–5.53] 6–10 2.18 [0.77–5.46] 6–10 4.33 [2.16–8.24]

Mopti 0–2 0–2 0.72 [0.17–2.43] 0–2 0.72 [0.17–2.43]2–6 3.60 [2.40–5.39] 2–6 1.08 [0.48–2.27] 2–6 3.96 [2.68–5.77]6–10 2.41 [1.16–4.75] 6–10 1.48 [0.57–3.53] 6–10 3.10 [1.65–5.59]

Timbuktu 0–2 0–2 0.23 [0.002–2.00] 0–2 0.23 [0.002–2.00]2–6 6.13 [4.44–8.37] 2–6 2.33 [1.35–3.92] 2–6 7.02 [5.22–9.37]6–10 3.76 [2.15–6.37] 6–10 1.07 [0.34–2.92] 6–10 3.90 [2.26–6.53]

Gao-Kidal 0–2 0–2 0.29 [0.003–2.58] 0–2 0.29 [0.003–2.58]2–6 0.58 [0.19–1.58] 2–6 0.58 [0.19–1.58] 2–6 1.05 [0.47–2.22]6–10 1.15 [0.44–2.75] 6–10 0.43 [0.07–1.72] 6–10 1.42 [0.61–3.10]

Total 0–2 0–2 0.71 [039–1.25] 0–2 0.71 [039–1.25]2–6 1.95 [1.58–2.39] 2–6 1.10 [0.83–1.45] 2–6 2.51 [2.09–3.00]6–10 1.70 [1.24–2.33] 6–10 1.26 [0.87–1.81] 6–10 2.35 [1.79–3.06]

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The largest ethnic group was the Bambara people, predom-inant in 20.3% of villages, followed by the Peuhl, the Sarakoleand the Dogon. Using the Bambara as reference, there were nostatistical differences for villages belonging to Peulh, Moor or

Malinke groups. However, the risk was significantly loweramong the Sarakole (OR � 0.46 [95% CI: 0.27–0.82]), theBozo (OR � 0.08 [95% CI: 0.01–0.58]), the Senoufo (OR �

0.58 [95% CI: 0.25–1.36]) or the Songhaı ethnic groups (OR �

0.40 [95% CI: 0.21–0.75]) (Table 4).

DISCUSSION

Vitamin A Deficiency as a Public Health Problemin Mali

The survey was conducted on a long period of time betweenMay 1996 and July 1997 at different seasons and with twodifferent harvests. This has to be considered when comparingregions. Subsequently the aggregation of regional results in anational one should only be considered as a proxy indicator ofthe severity of the problem in the whole country.

WHO considers that there is a serious public health problemif, in a population of preschool age children, the prevalenceof night blindness or of Bitot’s spots exceed 1% and 0.5%respectively [13].

Night blindness is not specific of xerophthalmia and otherfactors can create night blindness. Because of budget con-straints, it was not possible during this survey to confirm

Table 3. Univariate Analysis of Xerophthalmia Risk Factors

FactorProportion

exposed(%)

OR (95% CI) P

Sex: women/men 46.7 0.77 (0.60–1.00) 0.038Age: 6–10/2–6 33.2 0.86 (0.65–1.13) 0.27

Inhabitants� 1000 40.5 11000–5000 42.2 1.83 (1.36–2.47) �0.001�5000 17.3 1.86 (1.31–2.65) �0.001

Medical centre�5km 36.1 15–15 km 28.3 1.63 (1.14–2.33) 0.004�15 km 35.6 2.03 (1.47–2.81) �0.001

School in the village 43.8 0.66 (0.50–0.86) 0.001Women Association 77.8 0.67 (0.52–0.87) 0.003Agric. production

Market gardening 66.3 0.70 (0.54–0.91) 0.005Millet 70.0 2.47 (1.73–3.53) �0.0001Rice 52.3 1.13 (0.88–1.46) 0.33

SchoolingHead of household 22.7 0.52 (0.36–0.76) 0.0002Mother 15.0 0.61 (0.39–0.93) 0.015Children 24.9 0.57 (0.40–0.79) 0.0006

Exile of the father 54.7 0.74 (0.57–0.96) 0.017Property

Radio 73.4 0.91 (0.68–1.22) 0.52TV 4,9 0.15 (0.03–0.62) 0.002Moped 28.1 0.68 (0.50–0.94) 0.014Bicycle 44.8 0.77 (0.59–1.00) 0.04Draught ox 53.6 0.98 (0.76–1.25) 0.49Cow 54.8 0.63 (0.49–0.81) 0.0002Cement house 7.0 0.30 (0.09–0.85) 0.01Metal sheet roof 17.2 0.41 (0.25–0.65) �0.0001Household with inside

well 15.8 0.62 (0.41–0.94) 0.016Season

May–June 68.0 1Jan–Feb 32.0 0.22 (0.15–0.34) �0.001

Latitude� 13° 26.7 113–15° 37.2 2.96 (1.98–4.45) �0.001� 15° 34.1 2.85 (1.89–4.29) �0.001

Ethnie/BambaraBambara 20.3Peulh 11.4 0.98 (0.64–1.50) 0.02Moor 5.0 1.88 (1.18–2.99) 0.004Sarakole 10.5 0.60 (0.35–1.00) 0.039Malinke 7.0 0.08 (0.01–0.35) �0.001Tuaregh 4.4 0.40 (0.16–0.97) 0.029Bobo 1.8 0.83 (0.29–2.17) 0.68Bozo 2.2 0.13 (0.01–0.90) 0.02Dogon 7.6 1.71 (1.13–2.58) 0.007Senoufo 8.7 0.27 (0.12–0.59) �0.001Songhai 9.2 0.72 (0.43–1.20) 0.18Else 12.0 0.63 (0.38–1.02) 0.046

Table 4. Multivariate Analysis of Xeropthtalmia RiskFactors

Explanatory variable OR 95% CI P

Gender women/men 0.80 0.61–1.03 0.088Age 6–10/2–5y 0.87 0.65–1.15 0.33N° inhabitants/� 10001000–5000 2.36 1.66–3.35 �0.001� 5000 4.07 2.58–6.40 �0.001Medical centre/� 5 km5–15 km 1.89 1.23–2.92 0.004� 15 km 1.88 1.26–2.84 0.002School in village 0.59 0.43–0.88 0.001Mother attending

school 0.57 0.31–1.07 0.08Millet 1.75 1.13–2.72 0.012Rice 0.69 0.50–0.94 0.02Season 2/1 0.11 0.06–0.22 �0.001Latitude/ �13°13–15° 2.60 1.54–4.42 �0.001�15° 5.13 2.81–9.38 �0.001Ethnic group/BambaraPeuhl 0.97 0.62–1.52 0.91Moor 1.02 0.56–1.87 0.94Sarakole 0.46 0.27–0.82 0.008Malinke 0.62 0.14–2.71 0.53Tuaregh 0.55 0.22–1.41 0.21Bobo 0.60 0.21–1.72 0.34Bozo 0.08 0.01–0.58 0.013Dogon 1.01 0.64–1.59 0.97Senoufo 0.58 0.25–1.36 0.21Songhai 0.40 0.21–0.75 0.005Else 1.71 0.96–3.06 0.07

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vitamin A deficiency by serum testing. Nevertheless we haveproven in other studies conducted in several regions of Malithat night blindness was strongly associated with very highprevalences of vitamin A deficiency. In the Bandiagara region[14], night blindness was discovered in 4.3% of children aged6 months to six years and serum retinol was lower than 0.35�g/L in 43.8% of the sampled children. The biochemical de-ficiency attested by the Modified Relative Dose Response testwas still more frequent (77%).

In Mali, these thresholds have been exceeded in four regionsout of seven. In the region of Gao-Kidal, the prevalence ofBitot’s spots was close to the threshold value. The problem wasvery important in Timbuktu, Mopti and Segou. The least af-fected regions were Kayes and Sikasso, in the south-westernpart of Mali.

The survey was carried out before National ImmunizationDays (NIDs) were implemented in 1998. Mass distribution ofvitamin A supplements unlikely interfered with the study re-sults. However, some non-governmental organizational pro-grams could have potentially distributed doses of vitamin A aspart of the primary health care system. Nonetheless this situa-tion was surely very limited as attested by the 1996 Demo-graphic and Health Study that reported a 9.7% percent ofchildren less than 3 years of age having received vitamin Adose during the preceding year [15].

Age

Young children are particularly prone to xerophthalmia.Their needs are greatest and the basic intake often inadequate.Concurrent vitamin loss as a result of infection and malabsorp-tion from diarrhoea episodes are quite common. Indeed xeroph-thalmia was more frequent in children under the age of 6.

Gender

Boys more frequently presented signs of xerophthalmia,either night blindness or Bitot’s spots. This finding recursfrequently in vitamin A surveys and may be explained invarious ways: boys are more susceptible to diarrhoea, have lessresistance to the stress of malnutrition and are therefore morelikely to present vitamin deficiency than girls [4]. Girls alsoremain closer to their mothers during the work of preparingmeals and have access to more diversified intakes includingdark green leaves vegetables and fruits.

Risk Factors

Seasonal Variations. Bias linked to seasonal variationsneed to be discussed in the search of social and environmentaldeterminants. The prevalence estimates of xerophthalmia werenot similar in the regions of Gao and Timbuktu, with Gao beingthe least affected region. Climatic conditions are broadly sim-ilar, although the population and way of life are different (theTamachek predominate in Timbuktu and the Songhaı in Gao).

The two surveys did not take place at the same time: Timbuktuwas surveyed in June 1996, at the end of the dry season, whennutritional conditions are at their worst; Gao was visited inFebruary 1997, a season with still full granaries.

The factors contributing to vitamin A deficiency are commonto all the members of a family or a village community as a whole,which explains the distribution differences between areas, as wellas a clustering effect that has to be taken into account in analysisproceeding [16]. One isolated clinical case is usually evidence ofa biochemical vitamin A deficiency in the other members of thecommunity. It is considered that children suffering from biochem-ical vitamin A deficiency are 10 times as numerous as those withxerophthalmia [14]. For these children, supplementation with highdose vitamin A capsules (100,000 IU/200,000 IU) can reducemortality by 23–30%[2–3].

Vitamin A balance essentially depends on the micronutrientcontent in food. This content is constituted by the consumptionof retinol present in animal products and by that of a precursorin the form of provitamin A carotenoids, predominantly foundin fruits and vegetables. In most of the populations exposed toxerophthalmia, vegetables are the main source of vitamin A,and even without seasonality, it is very difficult to meet allneeds for vitamin A with vegetables and fruits. It is unfortu-nately linked to seasonal variations in the produce availability.This explains why the content has to exceed daily needs so asto constitute sufficient hepatic reserves of vitamin A in order tolive through periods of shortage. The effectiveness of carotenerich foods in improving vitamin A status is still not fullyunderstood and warrants further investigations [17–19].

A certain number of factors, such as diarrhoea events orintestinal parasitic diseases, are recognized to hinder the ab-sorption of vitamin A. Other events, such as measles or respi-ratory infections, increase metabolic requirements. Mild mal-nutrition is also an obstacle to the absorption, hepatic storageand transportation of the vitamin. All these factors are commonamong children in Mali [20].

Socio-Economic Level of Families. It is generally agreedthat vitamin A deficiency affects the children of poor families.We postulated that the level of wealth in the families of theaffected children could be low. When we constructed an indi-cator of wealth by adding up the commercial value of thefamilies’ various possessions, no significant correlation withthe frequency of occurrence of xerophthalmia was found; there-fore this estimator was not kept in the model. Interestingly, thesame indicator was used in the trachoma survey and a verystrong association was then found between trachoma status andpoverty [21]. Relation between poverty and xerophthalmiaappears not so strong than with trachoma.

Village Environment. It is also paradoxical that the diseasefrequency was inversely related with the size of the village. Itmay be postulated that children are fed in a more systematic,more consistent way in a traditional, remote, closed villagesociety. The degree of health cover, as defined by the presenceof a medical centre within 5 or 15 km seems to have an impact,

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and to be associated with a lower prevalence of vitamin defi-ciency. However, it is difficult to interpret this finding. Forexample, the proximity of medical centre might make it easierto distribute vitamin A capsules for childbirth or during child-hood diseases.

Level of Education. Schooling appears to have a markedimpact on the frequency of vitamin deficiency. The presence ofa school, or the fact that the mother has attended school, wasvery significantly associated with a lower prevalence of xe-rophthalmia. On the other hand, the role played by the school-ing received by the children of the family did not stand out ina multivariate analysis. The educational system is poorly de-veloped in Mali (less than 30% of children in rural areas attendschool), but it might be hoped that it would promote a changein children feeding habits. The fact that the head of the familyhas spent a period of time abroad might increase the diversityof the family’s diet and food habit.

Agricultural Production. In the Sahelan countries, thebasic food is a cereal (millet, sorghum or rice) and a saucemade from cooking leaves, fresh or dried fish or meat depend-ing on socio-economic level [21].

It is surprising and unexpected that villages producing mil-let have a higher prevalence. Rice, which is taking on increas-ing importance in the Malian diet, seems to have a protectiveeffect even when this variable is standardized on latitude. It hasbeen introduced more recently than the traditional cereals suchas millet and may point to a search for increased diversity offood which encourages beta-carotene rich vegetables in thediet. The sauces accompanying this cereal are often different,for example peanut sauce or bean-leaf sauce.

Ethnic Group. Despite a different way of living we did notdetect any difference between Bambara villages and Peuhl orMoor ones. Indeed, if Bambara are traditional farmers, Peuhlsare more specialized in cattle breeding and then subsequentlymore likely to get more milk products for their children, andMoors live on the Mauritanian border, in dry regions which donot lend themselves to cultivation. Possible explanations to thelower risk of Sarakole, Bozo, Songhai or Senoufo people needto be very careful. Some cultural factors could interfere con-currently to richness, mobility or education.

A National Policy

In 1990, the heads of state and government made a com-mitment to allocate resources for controlling vitamin A defi-ciency before the end of the decade. Activities were conductedin many countries but very little in Africa as yet. Real progresshas been made in certain zones, particularly South America andAsia. The problem is still very acute in Sub-Saharan Africa andwill remain so while dietary intake remains limited. The ur-gency of the situation makes it legitimate to use palliativestrategies by distributing high doses of vitamin A, for exampleduring national vaccination campaigns. These findings togetherwith the results of more specific surveys in limited areas have

been strong arguments for advocating vitamin A supplementa-tion during Malian NID’s. The measure is successfully appliedevery year to the entire country since December 1998. Thisintervention must firmly be completed by the promotion of anactive and effective food policy to control this clearly identifiedmicronutrient deficiency [22].

ACKNOWLEDGMENTS

The survey conducted by IOTA and the Malian blindnessprevention program was funded by a grant of the EuropeanCommunity. We will thank the Malian Ministry of Health forits strong implication through all regional health structures.

REFERENCES

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13. WHO/UNICEF: “Indicators for Assessing Vitamin A Deficiencyand their Application in Monitoring and Evaluating Intervention

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20. Schemann JF, Sacko D, Malvy D, Banou A, Traore L, Momo G:Risk factors for trachoma. Int J Epidemiol 31:194–201, 2002.

21. Ag Bendech M, Chauliac M, Carlier C, Diarra M: Carence envitamine A et consommation alimentaire chez les enfants de 6 a 84mois en milieu rural malien. Sante 5:77–83, 1995.

22. Traore L, Banou AA, Sacko D, Malvy D, Schemann JF: Strategiesto control vitamin A deficiency. Sante 8:158–162, 1998.

Received July 19, 2005; revision accepted June 3, 2006.

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