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| ABSTRACT |
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| INTRODUCTION |
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The World Health Organization has suggested that anemia is of "moderate" public health importance where its prevalence is between 20% and 39.9% and "severe" if it occurs in 40% or more of the population. It is recommended that an approach to iron deficiency anemia be especially targeted toward women of reproductive age who risk the attendant consequences of anemia during pregnancy.8 Integrating this strategy into a community-based program has been found to be effective.9 A recent meta-analysis has confirmed that antenatal iron supplementation improves both antenatal and post-natal hemoglobin concentration and that side effects of iron supplementation appear more common in women who receive daily iron.10 For countries in the Western Pacific Region, where anemia prevalence constitutes a public health problem, a strategy of weekly iron supplementation has been recommended, with hookworm control where prevalent.11
In Southeast Asia, almost 215 million women are estimated to be anemic. In Vietnam, the prevalence of anemia was 42.8% in 1995,12 and a recent survey found that 40% of non-pregnant women were anemic.13 The prevalence of hookworm infection in northern Vietnam has previously been reported as 52%.14 However, in many districts of Vietnam, the prevalence of anemia, iron deficiency and hookworm infection remains largely unknown. Thus, before the development and implementation of strategies in Vietnam to control iron deficiency anemia, further analysis of these parameters is necessary.
We conducted a cross-sectional survey in Yen Bai province, in northwest Vietnam, to assess the prevalence of and factors associated with iron deficiency and anemia in non-pregnant women of reproductive age. This study represents the baseline assessment before implementing a model program in this area to address anemia and hookworm infection in Vietnamese women of reproductive age.15
| MATERIALS AND METHODS |
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The province is divided into nine administrative towns and districts. Two districts, Yen Binh and Tran Yen, were chosen for the study. An estimated 51,623 women of reproductive age (16–45 years) live within the study area. Twenty-eight percent of the communes in this area are classified as having very poor economic status.16
Villages and women were selected using the population proportional to size cluster sampling method. Thirty-three villages were selected, and in each, 13 women were invited for a cross-sectional baseline evaluation. Sample size was calculated to produce a 90% power (
= 0.05) to detect a change in hemoglobin of 10% at follow-up analyses incorporating the cluster-based nature of the survey. A total of 354 women completed the survey and laboratory evaluation.
Laboratory methods. Blood and stool samples were collected from each participant. The intensity of hookworm, Ascaris lumbricoides, and Trichuris triciura infection was evaluated from the fecal specimen using standard Kato Katz methodology17 and expressed as eggs per gram of feces (epg). Intensity of hookworm infection was classified according to WHO guidelines: 0 epg classified as nil, up to 2,000 epg classified as light, 2,000–4,000 epg as moderate, and > 4,000 epg classified as severe.18 The count of eggs per gram of stool has been previously shown to rise with overall gastrointestinal hookworm burden.19 Hemoglobin was evaluated in the field from finger prick blood, using a hemoglobinometer (HemoCue AB, Angelholm, Sweden). A 3-mL sample of venous blood was collected using a closed collection system into tubes containing fast clotting agent. The tubes were spun at 4,000 rpm for 20 minutes at room temperature, after which serum was collected and stored at –4°C. The samples were transported on dry ice to Sydney, Australia, for analysis by the South Eastern Sydney Illawarra Area Health Service (SEALS). Serum ferritin was measured using a sandwich immunoenzymatic assay (IEA; Beckman Coulter Access Reagents, Fullerton, CA). Soluble transferrin receptor was evaluated using enzyme-linked immunoassay (ELISA; IT; Orion Diagnostica, Espoo, Finland). The ratio of transferrin receptor to log (to base 10) serum ferritin (TfR-F index) was calculated from these results.20 Serum C-reactive protein (CRP) levels were assessed by an ELISA method. We chose a level of > 10 mg/L to represent a state of inflammation, because this has been previously reported as an appropriate clinical cut-off.21
Anemia was defined as a hemoglobin concentration of < 12 g/dL and iron deficiency as a serum ferritin of < 15 ng/mL, except where otherwise stated, in concordance with WHO recommendations for women of reproductive age.8 Transferrin receptor levels of 2.3 µg/mL or above were considered abnormal, based on the manufacturers reference interval (0.8–2.3 mg/L). The TfR-F index has been previously shown to provide an excellent indicator of iron reserves, with depletion of iron stores implied once the ratio exceeds 1.8.22 We adopted this cut-off as an alternative indicator of iron deficiency.
Survey. Participating women were asked to complete a questionnaire covering potential demographic risk factors for iron deficiency and hookworm infection, including dietary meat consumption, ethnic group, education, number of children, domestic sanitary facilities, and frequency of wearing shoes. Current pregnancy status was also assessed. Local village health workers assisted the survey team in administering the survey.
Statistical analysis. The data were entered in the field into spreadsheets using Microsoft Excel (Microsoft Corp., Redmond, WA). The spreadsheets were imported into Stata (Intercooled Stata 9.2 for Windows; StataCorp, College Station, TX) for further analysis. The distribution of laboratory variables was assessed.
Hemoglobin values were approximately normally distributed, enabling use of the arithmetic mean. Ferritin, transferrin receptor, and the TfR-F index were right-skewed; thus, these were log-transformed for subsequent analysis. Hookworm eggs per gram data were right skewed, with a considerable number of zero values. Thus, egg count data were analyzed using the Poisson distribution, incorporating the clustered nature of the survey (by village), with comparisons between groups made by calculating the incidence rate ratio. Egg count data were logarithmically transformed after addition of 1 to facilitate regression calculations.18 Median meat consumption was determined.
The prevalence of anemia, iron deficiency, hookworm infection, and iron deficiency anemia were calculated using the cut-offs defined above. Average iron indices, hookworm burden, and meat consumption were calculated and compared between those women who were anemic and those who were non-anemic; the analysis was based on a linear regression model that incorporated the effect of clustering by village. Prevalences of iron deficiency, hookworm infestation, and meat consumption were also compared between anemic and non-anemic groups. Comparison of significance of differences between meat consumption in the anemic and non-anemic groups was performed using a two-sample Wilcoxon rank-sum (Mann-Whitney) test.
Multiple regression analysis incorporating the cluster design of the survey was performed to evaluate the effect of hookworm eggs per gram, meat consumption, and the demographic variables of age, number of children, and level of education on hemoglobin and log transformation of iron indices (ferritin, transferrin receptor, and TfR-F index). The regression equation used the log(eggs per gram) value as described above, and as such, the results for association with hookworm are reported after transformation by taking the inverse logarithm.
Ethical considerations. Before the implementation of the project, extensive consultation was undertaken between the project team and the community, as well as careful liaison with village, district, and provincial health staff. The local village health workers provided participants with information regarding the reasons for the survey, and verbal informed consent was obtained at the time of enrollment. The survey team assisted the village health workers where participants experienced concerns or uncertainty relating to any aspect of their participation.
The project was approved by the Human Research Ethics Committee of the National Institute of Malariology, Parasitology, and Entomology (Hanoi, Vietnam), the Walter and Eliza Hall Institute of Medical Research (Melbourne, Australia), and Melbourne Health (Melbourne, Australia).
| RESULTS |
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The district and total means for hemoglobin, iron studies, meat consumption, and stool parasite counts, together with prevalences of anemia, iron deficiency, and hookworm infection, are presented in Table 2
. The geometric mean eggs per gram was 145.04 (95% CI 105.63–199.01). To indicate the mean worm burden among women who were actually infected, the value was recalculated after the exclusion of the 21.85% who had a count of 0. After this adjustment, the mean was 586.19 (492.90–697.15). Using the Poisson distribution, the mean hookworm egg count was 1,184.48 (952.96–1,472.24).
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The overall prevalence of hookworm infection was 78.15% (261/334); however, most participants (61.68%, 206/334) had a light worm burden.
A comparison of indices of iron stores, hookworm infection, and meat consumption between anemic and non-anemic women is shown in Table 3
. The mean indices of iron stores among the anemic group were significantly different to those of the non-anemic group. Median meat consumption was also lower among the anemic population (P = 0.004). However, there was no evidence of significant difference in hookworm eggs per gram [incidence rate ratio, 1.31; 95% confidence interval (CI), 0.81–2.11; P = 0.270].
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3 servings/wk) was protective against anemia [odds ratio (OR), 0.52; 95% CI, 0.32, 0.85; P = 0.009] and iron deficiency (OR, 0.46; 95% CI, 0.28, 0.76; P = 0.002). Prevalence of moderate or severe hookworm infection was not significantly different between the anemic and non-anemic groups. In particular, severe hookworm infection (> 4,000 epg) was not significantly more common among anemic women (7.20%) than non-anemic women (5.74%; P = 0.595). The logarithm of hookworm eggs per gram was not associated with age (coefficient, –0.03; 95% CI, –0.10, 0.04; P = 0.392), level of education (coefficient, 0.06; 95% CI, –0.43, 0.56; P = 0.794), or number of children (coefficient, 0.32; 95% CI, –0.20, 0.84; P = 0.224), but there was weak evidence of inverse association with meat consumption (coefficient, –0.17; 95% CI, –0.35, 0.00; P = 0.048). By logistic regression, ethnicity was not associated with moderate/heavy hookworm infection (OR, 1.12; 95% CI, 0.87, 1.44; P = 0.387), anemia (OR, 1.15; 95% CI, 0.97, 1.35; P = 0.109), or ferritin level < 15 ng/mL (OR, 1.11; 95% CI, 0.96, 1.28; P = 0.168). Hookworm, hemoglobin, and iron indices were not associated with frequency wearing of shoes or type of latrine used. Consumption of meat was not associated with age or number of children but was positively associated with increased level of education on regression analysis (coefficient, 1.19; 95% CI, 0.84, 1.55; P < 0.001).
Table 4
shows the results of a multiple regression analysis performed to determine the relationship between dependent variables (hemoglobin, iron indices) and amount of meat consumption, degree of hookworm infection, and demographic factors. There was a positive association between meat consumption and both hemoglobin and iron indices. Hemoglobin was not associated with hookworm eggs per gram, but iron indices, particularly ferritin, were. Hemoglobin and iron indices were unrelated to age, number of years of education, and number of children of women of reproductive age. After education, age, and number of children were withdrawn from the model (data not shown), hemoglobin was unrelated to hookworm eggs per gram (coefficient, 0.98; 95% CI, 0.92, 1.04; P = 0.506) but was associated with meat consumption (coefficient, 0.07; 95% CI, 0.00, 0.14; P = 0.042). Hookworm (coefficient, 0.93; 95% CI, 0.89, 0.98; P = 0.007) and meat intake (coefficient, 0.07; 95% CI, 0.04, 0.11; P < 0.001) were both associated with logarithmic transformation of ferritin. Transferrin receptor was not associated with hookworm (coefficient, 1.00; 95% CI, 0.98, 1.02; P = 0.795), but there was a weak association with meat intake (–0.02; 95% CI, –0.04, 0.00; P = 0.074). The results were similar for transferrin receptor/log ferritin index and associations with hookworm (co-efficient, 1.02; 95% CI, 0.99, 1.06; P = 0.200) and meat intake (coefficient, –0.04; 95% CI, –0.07, –0.01; P = 0.006).
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| DISCUSSION |
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The main limitation of the study was that, in < 10% of cases, demographic data and test results were missing. This was because of occasional unanswered questions at the time of interview, and in some cases, low volumes of venous blood taken, such that not all laboratory analyses could be performed for all participants. Although we have no reason to believe that this biased the analysis, it remains a possibility. A proportional cluster sampling method was used to ensure that the findings were representative for the 51,623 women living in Tran Yen and Yen Binh districts. However, these districts were relatively easily accessible, and the relationship between iron deficiency, anemia, diet, and hookworm infection may differ in more remote districts in Vietnam.
Associations between hemoglobin and iron with meat consumption were not part of the a priori hypothesis. However, the association is robust (P < 0.05) and physiologically feasible, although the coefficient for association was not especially high (0.07 for both hemoglobin and ferritin). It is unlikely that our study was underpowered to detect an association between hookworm and hemoglobin because the inverse logarithm of the confidence interval for the association was narrow (0.92, 1.04) and centered around 1.
In this study, iron deficiency was more prevalent among the anemic population, but only approximately one third of women with anemia had a low serum ferritin. The true prevalence of iron deficiency anemia may be higher than this because ferritin is an acute phase protein that may be elevated in inflammation. To address this, we used alternative indices of iron deficiency—soluble transferrin receptor and the TfR-F index20—and confirmed that the prevalence of iron deficiency was similar using the TfR (> 2.3 µg/mL), the TfR-F index (> 1.8), and serum ferritin (< 15 ng/mL), both in the overall and in the anemic groups. This suggests that the newer indices are comparable to ferritin for detecting iron deficiency in this population. Combining the results of both serum ferritin and the TfR-F index provides a higher prevalence of iron deficiency, both overall and among the anemic group, implying that the cases detected by each method do not completely overlap. Iron depletion (ferritin = 15–30 ng/mL) was present in 23.58% of anemic women (and a similar proportion of the non-anemic sample), raising the possibility that iron supplementation may have a greater than expected impact in the long term because both anemic and non-anemic women would be at risk of developing or exacerbating iron deficiency anemia should their iron requirements increase, for example, during pregnancy.
Inadequate iron intake, particularly caused by reduced access to heme iron, which is chiefly found in meat and is highly bioavailable, can contribute to iron deficiency.23 Our analysis showed that meat intake was associated with iron status, and there was a strong trend toward a positive correlation with hemoglobin. This suggests that failure of adequate iron intake is an important contributor to iron deficiency in this region. Although demographic factors were not associated with outcomes of iron deficiency or anemia, there was an association between education and increasing meat intake. This suggests better educated women can afford, or make it a priority to include, meat in their diet. These findings provide a rationale to include regular iron fortification or supplementation in any strategy aimed at alleviating iron deficiency. A large survey in Vietnam has recently shown that low meat intake is associated with iron deficiency anemia,13 but unlike our findings, it found that hookworm infection was the stronger risk factor. Similar findings were found among pregnant women. Hookworm infection has been previously found to affect appetite,24 and we found a subtle inverse association between hookworm and meat intake.
This study showed that hookworm infestation is prevalent in northwest Vietnam, with 78.14% of women in the study infected. However, heavy infection (> 4,000 epg) was relatively uncommon. The mean hookworm burden remained "light," even if the uninfected population was removed from the analysis, suggesting that hookworm burden was low among those who were infected. This may be explained by recent school-based deworming activities conducted in the area. Increasing intensity of hookworm infestation was related to iron deficiency, suggesting that hookworm is a contributing factor to gastrointestinal blood loss in women in this area of Vietnam.
The lack of an association with anemia may be caused by the low prevalence of moderate and heavy hookworm infection and the large number of anemic women who were not iron deficient, suggesting other causes of anemia may be prevalent in this population. Other nutritional deficiencies, 25 and vitamin A,26 have been such as of folate, vitamin B12, shown to contribute to anemia. Inflammation can produce an anemia of chronic disease, characteristically associated with an elevated CRP and ferritin.21 However, the finding of a normal CRP in > 99% of the study group makes it unlikely that this had an impact on the results. Genetic hemoglobinopathies, such as
thalassemia and hemoglobin E may also cause anemia. These have been found to be common among certain populations in Southeast Asia27 and may have contributed to anemia in some of the study participants.
Our study confirmed that iron deficiency anemia is a major public health problem in women of reproductive age in northwest Vietnam. Lack of dietary iron and hookworm infection both contribute to iron deficiency, and therefore, a program of iron supplementation and deworming would be beneficial in this area. Further study to define the other causes of anemia will be important for planning national anemia prevention strategies.
Received August 19, 2007. Accepted for publication November 25, 2007.
Acknowledgments: The authors thank Luong Ba Phu and his staff at the Malaria Control Program office, Yen Bai, for invaluable assistance with all the provincial aspects of the survey. In addition, we thank the Yen Bai Peoples Committee for their ongoing support, the District Preventive Medicine staff, Commune and Village health workers, and the women who participated in the survey. The authors thank Keith Westbury and scientists at SEALS for their efficient processing of samples and Christalla Hajisava for assistance with formatting the manuscript.
* Address correspondence to Beverley-Ann Biggs, The Royal Melbourne Hospital, Parkville 3050, Victoria, Australia. E-mail: babiggs{at}unimelb.edu.au ![]()
Authors addresses: Sant-Rayn Pasricha, Department of Haematology, The Alfred Hospital, Commercial Road, Prahran Victoria 3181, Australia, Telephone: 61-3-9276-2000, Fax: 61-3-9076-2222, E-mail: santapasricha{at}hotmail.com. Sant-Rayn Pasricha, Sonia R. Caruana, Gerard J. Casey, and Beverley-Ann Biggs, Department of Medicine (RMH/WH), The University of Melbourne, 4th Floor, Clinical Sciences Building, The Royal Melbourne Hospital, Parkville, Victoria 3050, Australia, and Centre of Clinical Research Excellence in Infectious Diseases (CCREID), The Royal Melbourne Hospital, Parkville Victoria 3050, Australia, Telephone: 61-3-8344-6252, Fax: 61-3-9347-1863, E-mail: sonia2rose{at}yahoo.com.au, gcasey{at}unimelb.edu.au, and babiggs{at}unimelb.edu.au. Tran Q. Phuc and Nong T. Tien, National Institute of Malariology, Parasitology and Entomology (NIMPE), 245 Luong The Vinh Street, Hanoi, Vietnam, Telephone: 84-4-8543035, Fax: 84-4-8543015, E-mail: tquangphuc{at}yahoo.com and nongthitien{at}yahoo.com. Damien Jolley and Sally Kingsland, Monash Institute of Health Services Research, Monash University, Clayton Campus, Wellington Road, Clayton, Victoria 3800, Australia, Telephone: 61-3-9905-4000, Fax: 61-39905-4007, E-mail: damien{at}jolley.com.au and sally.kingsland{at}gmail.com. Lachlan MacGregor, Clinical Epidemiology and Health Service Evaluation Unit, The Royal Melbourne Hospital, Royal Park Campus, Park House, Building 22, 34-54 Poplar Road, Parkville, Victoria 3052, Australia, Telephone: 61-3-9342-3040, Fax: 61-3-9342-7060, E-mail: Lachlan.Macgregor{at}mh.org.au. Antonio Montresor, World Health Organization, 63 Tran Hung Dao, Hanoi, Vietnam, Telephone: 84-4-943-3734, Fax: 84-4-943-3740, E-mail: montresora{at}vtn.wpro.who.int.
Reprint requests: Beverley-Ann Biggs, Department of Medicine (RMH/WH), The University of Melbourne, 4th Floor, Clinical Sciences Building, The Royal Melbourne Hospital, Parkville, Victoria 3050, Australia.
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