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Risk Factors for Xerophthalmia Among Mothers and Their Children and for Mother-Child Pairs With Xerophthalmia in Cambodia
Richard D. Semba, MD, MPH;
Saskia de Pee, PhD;
Dora Panagides, MHS;
Ouk Poly, MD;
Martin W. Bloem, MD, PhD
Arch Ophthalmol. 2004;122:517-523.
ABSTRACT
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Objective To characterize the risk of xerophthalmia among nonpregnant women and their children and the risk factors for households in which both mother and child have xerophthalmia.
Methods In case-control analyses of more than 15 000 households in the National Micronutrient Survey of Cambodia, univariate and multivariate logistic regression were used to estimate odds ratios (ORs) for nonpregnant mothers, children, and mother-child pairs with xerophthalmia.
Main Outcome Measures Risk factors for xerophthalmia.
Results Of 10 942 children aged 18 to 60 months and 9587 nonpregnant women, the adjusted prevalence of xerophthalmia was 0.7% and 1.9%, respectively. In multivariate analyses, a child was at higher risk of xerophthalmia when the mother had xerophthalmia (OR = 4.36; 95% confidence interval [CI], 2.25-8.46), and a mother was at higher risk of xerophthalmia when a child had the disease (OR = 9.21; 95% CI, 3.56-23.82). Households were at higher risk for having both mother and child with xerophthalmia if there was a history of diarrhea in the mother (OR = 6.48; 95% CI, 1.49-28.23) or in a child younger than 60 months (OR = 10.16; 95% CI, 1.55-66.62) in the last 2 weeks.
Conclusions Xerophthalmia clusters among mothers and children in Cambodia and is associated with diarrheal disease. Interventions are needed to address vitamin A deficiency and diarrheal disease at the household level.
INTRODUCTION
Vitamin A deficiency is a leading cause of infectious disease morbidity and mortality in developing countries worldwide. Xerophthalmia, which includes night blindness, Bitot spots, corneal xerophthalmia, and keratomalacia, remains the leading cause of blindness among children in developing countries.1 Of an estimated 453 000 children with blindness or severe visual impairment in low-income countries worldwide, 200 000 children have corneal scarring attributed mostly to vitamin A deficiency and measles.2 Vitamin A deficiency may occur because of an inadequate intake of vitamin A, an increased demand for vitamin A during periods of rapid growth in children, and abnormal urinary losses of vitamin A during infection. Vitamin A deficiency can result in impaired immunity, increased infectious disease morbidity, and a higher risk of corneal blindness, especially in children with measles.3-4 Xerophthalmia has been associated with diarrheal disease5-6 and tuberculosis7 in preschool children and with gastrointestinal and genitourinary infections among pregnant women.8-10
Recently, xerophthalmia was found to be relatively common among nonpregnant women in Bangladesh,11 Nepal,12 and Cambodia,13 suggesting that in some parts of the world, women of childbearing age also constitute a group at high risk for vitamin A deficiency. The risk of xerophthalmia among mothers and children in the same households has not been well characterized, and the risk factors for household clusters of mothers and children with xerophthalmia need further elucidation. We hypothesized that a mother is at higher risk for xerophthalmia when she has a child with xerophthalmia and that a child is at higher risk of xerophthalmia if his or her mother has this disease. We also hypothesized that a household cluster of xerophthalmia among mother and child was associated with risk factors such as low socioeconomic status and diarrheal disease. To address these hypotheses, we conducted both a cross-sectional study and case-control analysis among nonpregnant women and their children younger than 60 months in the National Micronutrient Survey of Cambodia13 in 2000, a population-based survey of more than 15 000 households in 10 provinces of Cambodia.
METHODS
The National Micronutrient Survey of Cambodia, a collaborative effort of the Cambodian government and Helen Keller International, Phnom Penh, Cambodia, was conducted from February 2000 to September 2000. The specific aims of the survey were to determine the national prevalence of micronutrient deficiencies such as vitamin A deficiency among mothers and their children younger than 60 months, to assess potential risk factors for micronutrient deficiencies, and to measure current coverage of vitamin A capsule distribution programs. Data were collected from 15 120 households, which were selected by multistage cluster sampling. Cambodia's 20 rural provinces were divided into 6 groups based on ecological, geographical, socioeconomic, and health characteristics. From each of these 6 groups, 84 communes were chosen by randomly selecting half of the provinces in the group and then selecting the communes using probability proportional to size-sampling techniques. From each selected commune, 30 households with at least 1 child younger than 60 months were selected by interval sampling. Thus, the total number of households selected was 15 120 (6 groups x 84 clusters x 30 households). A household was defined as a group of individuals who eat from the same pot of food and, for adults in the group, who are present in the household for at least 6 months out of the year.
A standardized questionnaire in Khmer was used to obtain information on different nutritional outcomes such as vitamin A deficiency and stunting, food consumption and vitamin A intake, demographics and socioeconomic status, and health program performance. Interviews were conducted by 40 2-person teams hired from the Cambodian government. As part of the interview, the field workers noted the main materials of the walls of the house (bamboo, thatch, grass, hay, leaves, or other temporary materials vs wood/plywood, concrete, brick, stone, galvanized iron/aluminum, other metal sheets, asbestos cement sheets, or other permanent materials) and inquired about the amount of land that each household owned, which was then converted to hectares. The heights and weights of women were measured using a microtoise and scale (A&D Precision Health Scale, UC-300; A&D, Tokyo, Japan), and body mass index (Quetelet) was calculated as weight in kilograms divided by height in meters squared. Mid upper arm circumference was measured with a measuring tape, and a value of 230 mm was chosen as a cutoff point for undernutrition in adult women.14 Pregnancy status was determined by asking a woman whether she was pregnant; if she was unsure, the result was coded as not pregnant.
Women were asked whether they currently had night blindness, or kwak moin ("chicken blindness"), and a parent or guardian was asked whether each child in the household had night blindness. A history of night blindness was shown to be a reliable indicator of vitamin A deficiency in a study by Sommer et al,15 and throughout our article, xerophthalmia refers to night blindness. Other questions pertained to a history of diarrhea in the last 2 weeks and consumption of vitamin A–rich foods. Vitamin A intake was assessed with the 24-VASQ16 method, in which a 24-hour recall questionnaire was administered that included all foods and drinks consumed during the previous day. All vitamin A–containing ingredients were then assigned a food code and vitamin A content code. The food codes defined whether the ingredient was a vegetable, fruit, animal food, or fortified food. Vitamin A content codes were assigned for the amount of vitamin A in the individual ingredient consumed, which was classified as less than 20, 20 to 75, 76 to 150, 151 to 300, 301 to 750, and more than 750 retinol equivalents. Vitamin A intake was calculated per food code using the midpoints of the vitamin A content categories. Vitamin A content of food items was obtained from food composition tables available in the region (Thailand and Indonesia) that used high-performance liquid chromatography analysis for assessing carotene content. Vitamin A intake from fruits, including pumpkin and sweet potato, was corrected by 50% and from vegetables, including carrots, by 23% according to the most recent information on the bioavailability of provitamin A carotenoids.17 Thus, using the 24-VASQ method, we obtained a semiquantitative estimate of the amount of vitamin A consumed by an individual from vegetables, fruits, or animal foods (no vitamin A–fortified foods were available in the provinces surveyed).
For this analysis, mothers were included if they were not pregnant, had at least 1 child aged 18 to 60 months, and had a valid data entry for night blindness for both mother and child. Children were included if they were aged 18 to 60 months and had a valid data entry for night blindness for child as well as mother. A case-control design was used to estimate the odds ratios (ORs) for xerophthalmia among mothers and children and then for household clusters of xerophthalmia. All cases were selected for the analysis. Controls were selected by calculating the number of cases for each province and using a random sample of controls to cases in a 5:1 ratio for each province. The ratio of 5:1 was chosen to balance the number of cases and controls and to have a large number of subjects for the analysis. Random selection was conducted using the specific function in SPSS version 7.5 for Windows (SPSS Inc, Chicago, Ill). All analyses were conducted for the total group of cases and controls. Using a case-control design with similar methods as described previously, household clusters with xerophthalmia (cases) were also compared with household clusters that did not have xerophthalmia (controls). Household clusters with xerophthalmia were defined as households in which both the mother and at least 1 child had xerophthalmia. Household clusters without xerophthalmia were defined as households in which neither the mother nor any children in the same household had xerophthalmia.
Cases and controls were first compared using the  2 test for categorical variables. The multivariate logistic regression model included risk factors for which P <.10 in univariate analyses. Regression coefficients were converted to ORs and confidence intervals (CIs) for the ORs that were derived from the standard error estimates of the regression coefficients. The overall prevalence estimates were weighted to account for differences in population size of the various provinces, and the 95% CIs of the prevalence estimates were corrected for design effect using Epi Info version 6.01 statistical software (Centers for Disease Control and Prevention, Atlanta, Ga).
RESULTS
There were 10 942 children and 9587 mothers in the analysis. Of the 10 942 children aged 18 to 60 months, 94 children had xerophthalmia, of whom 17 had a mother with xerophthalmia. Of the 9587 mothers who had at least 1 child aged 18 to 60 months in the same household, 238 mothers had xerophthalmia, of whom 17 had a child with xerophthalmia. There were only 2 households in the entire survey in which 2 siblings aged 18 to 60 months had xerophthalmia. The prevalence of xerophthalmia among children aged 18 to 60 months with a mother living in the same household is shown by province in Table 1. The prevalence of xerophthalmia was different between provinces (Pearson 2 test; P <.001). The population-weighted prevalence of xerophthalmia was 0.7% among children aged 18 to 60 months with a mother in the same household. The crude OR for a child to have xerophthalmia if his or her mother had xerophthalmia was 7.2 (95% CI, 3.4-15.2).
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Table 1. Prevalence of Xerophthalmia Among Children, Mothers, and Mother-Child Pairs by Province in Cambodia*
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Risk factors that appeared to be associated with xerophthalmia in children in the univariate analyses included a mother who had xerophthalmia during her last pregnancy, a mother with diarrhea in the last 2 weeks, a history of xerophthalmia in the mother, a mother with a mid upper arm circumference less than 230 mm, mother's parity greater than 3, a history of diarrhea in the child in the last 2 weeks, the child not currently breastfeeding, age of the child older than 24 months, the child not receiving a vitamin A capsule within the last 6 months, the child not consuming vitamin A from animal foods during the previous day, more than 5 family members in the household, and a roof made of thatch material (Table 2). These variables were entered into a final multivariate model, presented in Table 3. When adjusted for other risk factors, the OR for a child to have xerophthalmia if his or her mother currently had xerophthalmia and/or had xerophthalmia during the previous pregnancy was 4.36 (95% CI, 2.25-8.46).
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Table 2. Variables Associated With Xerophthalmia Among Children, Mothers, and Mother-Child Pairs*
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Table 3. Multivariate Model of Risk Factors for Xerophthalmia in Children*
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Variables that were not associated with xerophthalmia among children, mothers, or mother-child pairs (P >.10) and not included in Table 2 were the mother receiving vitamin A capsules after her last delivery, mother's body mass index less than 18.5, child wasted (weight-for-height z score <–2), child underweight (weight-for-age z score <–2), child's vitamin A intake from plant foods, ownership of poultry by the household, household members using a latrine, participation of any household member in a nongovernmental organization project, land owned by the household less than 0.5 hectares, village accessible by road, and village accessible by water.
The prevalence of xerophthalmia among 9587 mothers who had at least 1 child aged 18 to 60 months in the same household is shown by province in Table 1. The population-weighted prevalence of xerophthalmia among these mothers was 1.9%. The crude OR for a mother to have xerophthalmia if her child had xerophthalmia was 9.08 (95% CI, 4.10-20.0). In univariate analyses, risk factors that appeared to be associated with xerophthalmia in the mother were maternal history of xerophthalmia in the previous pregnancy, maternal history of diarrhea in the last 2 weeks, the mother not having received a formal education, mother's lower intake of vitamin A from plant or animal foods, a child with diarrhea in the last 2 weeks, a child who currently had xerophthalmia, a roof made of thatch, a wall made of bamboo, and the presence of a home garden (Table 2). These variables were entered into a final multivariate model, presented in Table 4. When adjusted for other risk factors, the OR for a mother to have xerophthalmia if her child had xerophthalmia was 9.21 (95% CI, 3.56-23.82).
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Table 4. Multivariate Model of Risk Factors for Xerophthalmia in Mothers*
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There were 17 household clusters in which both a mother and child had xerophthalmia. The population-adjusted prevalence of households that contained a mother-child pair with xerophthalmia was 0.1% (Table 1). Risk factors that appeared to be associated with households in which a mother-child pair had xerophthalmia included a mother with a history of xerophthalmia in the previous pregnancy, a maternal history of diarrheal disease in the last 2 weeks, mother's parity greater than 3, a child with diarrhea in the last 2 weeks, a child without stunting, the presence of a home garden, and the road to the village being passable throughout the year (Table 2). These variables were fit into the multivariate model indicated in Table 5. In the final multivariate model, the risk of both mother and child having xerophthalmia was increased if the child or mother had had diarrhea within the last 2 weeks.
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Table 5. Multivariate Model of Risk Factors for Households With Mother-Child Pair With Xerophthalmia as Compared With No Case in the Household*
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COMMENT
This study from Cambodia shows that the risk of xerophthalmia is much higher for a child if the mother has xerophthalmia and for a mother if a child has the disease. To our knowledge, this is the first study to examine the risk of xerophthalmia in mothers and children from the same households. Previous studies have shown that the risk of xerophthalmia is higher for a child in a household where another child has xerophthalmia.18 In the survey in Cambodia, there were only 2 households in which siblings were reported to have xerophthalmia. Of the children who were reported to have xerophthalmia, 18% came from a household in which the mother also reported a history of xerophthalmia. A case-control design was used within this larger survey, as has been used in previous epidemiologic studies of risk factors for xerophthalmia.19-20 The prevalence of xerophthalmia was significantly different between provinces, and we controlled for the contributions of controls from different provinces by using this case-control design.
Currently the World Health Organization, UNICEF [United Nations Children's Fund], and the International Vitamin A Consultative Group have established criteria for the identification of vitamin A deficiency as a public health problem based on the prevalence of xerophthalmia of higher than 1% among preschool children21 and 5% or higher among pregnant women.10, 22 A prevalence cutoff has not yet been established to define vitamin A deficiency as a public health problem for nonpregnant women of childbearing age, as found among 1.9% of these mothers in Cambodia. Xerophthalmia has also been reported among 1% to 2% of nonpregnant women in Bangladesh11 and 6.2% of nonpregnant, lactating women in lowland Nepal.12 These studies suggest that guidelines need to be developed to define vitamin A deficiency as a public health problem among nonpregnant women in developing countries.
In our study, diarrheal disease appeared to be strongly associated with xerophthalmia in both mothers and children. This observation is consistent with previous studies showing an association between vitamin A deficiency and diarrheal disease.5-6,20 Longitudinal studies in Indonesia have shown that preschool children with xerophthalmia are at higher risk of a subsequent episode of diarrheal disease23 and that preschool children with diarrheal disease are at higher risk of developing xerophthalmia.24 Although the relationships between diarrheal disease and xerophthalmia have not been described in a longitudinal manner among nonpregnant women, it seems reasonable that the same epidemiologic relationships exist among nonpregnant women as for preschool children. The underlying mechanisms may include a compromise in both gut immunity and gut permeability associated with vitamin A deficiency.3, 25 A history of diarrhea in the mother was a significant risk factor for xerophthalmia in children, and a history of diarrhea in children was a significant risk factor for xerophthalmia in the mother. These observations suggest that the risk of xerophthalmia increases with diarrhea among mother or child in the household.
Risk factors that were associated with xerophthalmia among children aged 18 to 60 months also included a thatched roof, an indicator of low socioeconomic status. In Indonesia, xerophthalmia in preschool children was associated with low socioeconomic status and poor hygiene.19 Nonreceipt of a vitamin A capsule within the last 6 months was also associated with an increased risk of xerophthalmia in preschool children, and this finding reinforces the importance of vitamin A capsule distribution programs for children. Mothers were at higher risk for xerophthalmia if they had had the disease during a previous pregnancy. The requirement for vitamin A increases during pregnancy,26 and vitamin A deficiency has long been recognized as a problem among pregnant women.27-28 The higher risk of xerophthalmia among nonpregnant women in Cambodia suggests that many of these women have not been able to recover their vitamin A stores following pregnancy. These findings suggest that a broader life cycle approach must be used to ensure that women of childbearing age receive sufficient vitamin A, whether pregnant, lactating, or nonpregnant and not lactating.
Vitamin A capsule distribution programs are the main strategy for reducing vitamin A deficiency in many developing countries.1 These community-based vertical programs are aimed primarily at preschool children and will miss nonpregnant women of childbearing age, another major risk group for xerophthalmia. Postpartum vitamin A capsule distribution to women is 1 measure that may help to reduce the risk of xerophthalmia among women following delivery, but these programs often have limited coverage, and the World Health Organization–recommended dose of one 200 000-IU capsule21 to an adult is not likely to replenish maternal vitamin A stores beyond a few months. Complementary strategies such as homestead food production are needed to increase the consumption of vitamin A–rich foods on the household level.29 The bioavailability of provitamin A carotenoids from fruits and vegetables is much lower than has previously been assumed,17, 30 and homestead food production should therefore focus on the development of both animal and plant sources of vitamin A and on generating income to improve the dietary quality, including vitamin A content, of family members in the household.31
AUTHOR INFORMATION
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Corresponding author and reprints: Richard D. Semba, MD, MPH, 550 N Broadway, Suite 700, Baltimore, MD 21205 (e-mail: rdsemba{at}jhmi.edu).
Submitted for publication June 16, 2003; final revision received November 5, 2003; accepted January 15, 2004.
This study was supported in part by grant HRN-A-00-98-00013-00 from the US Agency for International Development, Washington, DC, and grants HD30042 and HD32247 from the National Institutes of Health, Bethesda, Md.
We thank Mum Bunheng, MD, and Eng Huot, MD, Ministry of Health, and Hou Taing Eng, PhD, Ministry of Planning, for their support in conducting the National Micronutrient Survey. The Ministry of Planning, Ministry of Health, and Ministry of Rural Development, Phnom Penh, Cambodia, kindly allowed their staffs to assist with data collection as survey team members. We thank the provincial, district, commune, and village authorities for their logistic, management, and supervisory support, the survey teams of more than 130 persons who worked diligently to collect data throughout the country, and the members of the more than 15 000 households for their participation and time spent with the survey teams. We also thank the data entry department at Helen Keller International, Jakarta, Indonesia, for their assistance with designing, training, implementing, and supervision of data entry; the data entry operators; and Mayang Sari, Msc, for design effect analyses.
From the Department of Ophthalmology, Johns Hopkins School of Medicine, Baltimore, Md (Dr Semba); Helen Keller International, Asia Pacific Regional Office, Singapore (Drs de Pee and Bloem and Ms Panagides); Ministry of Health, Government of Cambodia, Phnom Penh (Dr Poly); and Helen Keller Worldwide, New York, NY (Dr Bloem). The authors have no relevant financial interest in this article.
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