Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-25T21:15:57.192Z Has data issue: false hasContentIssue false

Prevalence of anaemia, deficiencies of iron and vitamin A and their determinants in rural women and young children: a cross-sectional study in Kalalé district of northern Benin

Published online by Cambridge University Press:  25 January 2017

Halimatou Alaofè*
Affiliation:
Health Promotion Sciences Department, Mel and Enid Zuckerman College of Public Health, University of Arizona, 1295 N. Martin Avenue, Campus PO Box 245163, Tucson, AZ 85724, USA
Jennifer Burney
Affiliation:
School of Global Policy and Strategy (GPS), University of California, San Diego, La Jolla, CA, USA
Rosamond Naylor
Affiliation:
School of Earth, Energy & Environmental Sciences, Stanford University, Stanford, CA, USA
Douglas Taren
Affiliation:
Health Promotion Sciences Department, Mel and Enid Zuckerman College of Public Health, University of Arizona, 1295 N. Martin Avenue, Campus PO Box 245163, Tucson, AZ 85724, USA
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Objective

To identify the magnitude of anaemia and deficiencies of Fe (ID) and vitamin A (VAD) and their associated factors among rural women and children.

Design

Cross-sectional, comprising a household, health and nutrition survey and determination of Hb, biochemical (serum concentrations of ferritin, retinol, C-reactive protein and α1-acid glycoprotein) and anthropometric parameters. Multivariate logistic regression examined associations of various factors with anaemia and micronutrient deficiencies.

Setting

Kalalé district, northern Benin.

Subjects

Mother–child pairs (n 767): non-pregnant women of reproductive age (15–49 years) and children 6–59 months old.

Results

In women, the overall prevalence of anaemia, ID, Fe-deficiency anaemia (IDA) and VAD was 47·7, 18·3, 11·3 and 17·7 %, respectively. A similar pattern for anaemia (82·4 %), ID (23·6 %) and IDA (21·2 %) was observed among children, while VAD was greater at 33·6 %. Greater risk of anaemia, ID and VAD was found for low maternal education, maternal farming activity, maternal health status, low food diversity, lack of fruits and vegetables consumption, low protein foods consumption, high infection, anthropometric deficits, large family size, poor sanitary conditions and low socio-economic status. Strong differences were also observed by ethnicity, women’s group participation and source of information. Finally, age had a significant effect in children, with those aged 6–23 months having the highest risk for anaemia and those aged 12–23 months at risk for ID and IDA.

Conclusions

Anaemia, ID and VAD were high among rural women and their children in northern Benin, although ID accounted for a small proportion of anaemia. Multicentre studies in various parts of the country are needed to substantiate the present results, so that appropriate and beneficial strategies for micronutrient supplementation and interventions to improve food diversity and quality can be planned.

Type
Research Papers
Copyright
Copyright © The Authors 2017 

Recent reviews of dietary intake data from Benin showed that recommended daily intakes of key micronutrients, such as vitamin A and Fe, were not met( Reference Alaofè, Zee and Dossa 1 Reference Agueh, Tugoué and Sossa 4 ). At the sub-national level, in northern Benin, macronutrient intakes are also too low( Reference Mitchikpe, Dossa and Ategbo 5 , Reference Honfo, Hell and Akissoe 6 ). Lack of dietary diversity is a particularly severe problem in Benin where diets are based predominantly on starchy staples with little or no animal products and few fresh fruits and vegetables( Reference Alaofè, Zee and Dossa 1 , Reference Sodjinou, Agueh and Fayomi 2 , 7 ). According to the last Demographic and Health Survey (DHS) carried out in 2012, only 28 % of rural children satisfied the minimum diversity criterion of eating at least four out of seven food groups and 14 % consumed the minimum acceptable diet. In addition, the prevalence of stunting, wasting and underweight was respectively 40, 5 and 19 % among children aged 6–59 months, while 9 % of rural women had chronic energy deficiency (BMI<18·5 kg/m2)( 7 ). To improve the nutrition situation of women and children in Benin, the Ministry of Health has undertaken several interventions through its Strategic Plan for Food and Nutrition Development, comprising the supplementation of three major nutrients (vitamin A, Fe and iodine) and other promotive activities, such as exclusive breast-feeding, appropriate complementary feeding, and improved maternal and child nutrition( 8 ).

Despite the efforts of the line ministry and its stakeholders, Beninese women aged 15–49 years (41 %) and children aged 6–59 months (58 %) are significantly affected by anaemia with greater prevalence in rural areas( 7 ). Other nutritional data, such as Fe and vitamin A status, however, were not documented in the Benin 2012 DHS. In the 2006 Benin DHS, vitamin A deficiency (VAD) as measured by serum retinol <20 μg/dl was estimated to affect 66·0 % of children aged 12–71 months while the prevalence of night blindness was 11·8 % among pregnant women( 9 ). The few studies of micronutrient deficiencies among rural populations were conducted in specific localized groups and revealed greater prevalence rates of VAD among 12–71 month-old children (82 %) and pregnant women (14 %) in northern Benin( 9 ), while 33–49 % of children under 5 years of age were Fe deficient( Reference Mitchikpe, Dossa and Ategbo 10 ). Until now, to our knowledge, there have been no population-based studies permitting generalization about the epidemiology of anaemia and its principal determinants in non-pregnant women, despite the problem being among the top ten causes of morbidities in the country( Reference Bodeau-Livinec, Briand and Berger 11 , Reference Ouédraogo, Koura and Accrombessi 12 ). The only study that identified anaemia risk factors among Beninese children was carried out in 2007 and found that incomplete immunization, stunted growth, recent infection, absence of a bednet, low household living standard, low maternal education and low community development index increased the risk of anaemia( Reference Ngnie-Teta, Receveur and Kuate-Defo 13 ).

As such, identifying the magnitude of anaemia and deficiencies of Fe and vitamin A and their determinants in high-risk groups, such as women of childbearing age and children, is essential for evidence-based intervention modalities, particularly in rural areas, where women and children may suffer not only from micronutrient deficiencies but also a shortage of food( Reference Alaofè, Burney and Naylor 14 ). The present study is a very important step forward to avail of evidence-based information on the distribution of anaemia and micronutrient deficits and their predisposing diet and health factors among rural women and children in northern Benin. It will help understand the contemporary health profile of the rural populations of the study area in terms of dietary, socio-economic and environmental factors.

Methods

Location

The study was conducted during the dry season between January and March 2014 in the Kalalé district of northern Benin. The Kalalé district is home to more than 180 000 people, 95 % of whom rely on subsistence farming as their primary means of survival. For most, farming is limited to the rainy season due to a lack of water for irrigation( Reference Hamilton 15 ). Prices for basic vegetables (tomatoes, onions, peppers, etc.) almost double during the year from the rainy season to the dry season. The lack of availability and high prices combine to severely limit diets during the dry season and malnutrition is prevalent( 16 , Reference Nierenberg and Halweil 17 ).

Study design

Data for the present study were obtained from a baseline survey to evaluate the expansion and implementation of commercial-scale solar-powered drip irrigation systems (solar market gardens, or SMG) that aimed at improving food security, maternal and infant nutrition status, and women’s empowerment( Reference Burney, Woltering and Burke 18 Reference Bruhn and McKenzie 20 ). The cross-sectional study was conducted among sixteen villages. In each village, all households represented in women’s groups (WG) were surveyed, along with a random sample of non-women’s group (NWG) households from the same village; the goal was to select a maximum of thirty NWG households. In each investigated household, only one mother or caregiver of childbearing age (15–49 years) and her young child (6–59 months of age) were chosen. The first NWG household with a target mother–child in a given geographical area was selected randomly by the village delegate, and the survey continued until the required number of households was covered for each village. If there were more than one woman/child in the house, only one mother–child pair was selected. In total, 774 households were selected from the sampling frame for inclusion in the survey with 770 (311 WG v. 459 NWG) successfully recruited. The main reason for non-response was the failure to find individuals at home despite repeated visits to their household. Overall, 767 households were assessed, as three households of pregnant women were excluded from the analyses.

Data collection

Information on socio-economic and demographic characteristics, health status and diet factors was collected, while anthropometric measurements and blood samples were taken from the selected mother–child pairs to assess anaemia, Fe and vitamin A status. Figure 1 describes the study selection process.

Fig. 1 Study selection process (vit. A, vitamin A)

Sociodemographic questionnaire

A structured questionnaire was administered to the mother of each participant child and was composed of sociodemographic information (age, education, marital status and family size), obstetric history (pregnancy), illnesses (diarrhoea, malaria and any febrile illnesses in the last 2 weeks) and qualitative dietary information, such as the frequency of consumption of plant- and animal-source foods. The socio-economic status (SES) index was constructed using principal component analysis, and included house and land ownership, housing quality (e.g. house construction materials), access to services (water, electricity and gas) and household assets (various durable goods, agricultural machinery, animals and livestock)( Reference Vyas and Kumaranayake 21 , Reference Gwatkin, Rutstein and Johnson 22 ). Factor scores derived from the first factor (which explained 27·8 % of the variance) were then used to characterize the SES of each household. Households were categorized into SES quartiles based on their individual SES index score.

Dietary assessment

A qualitative recall of all foods consumed during the previous 24 h period was performed. Based on the FAO/FANTA Household Dietary Diversity Questionnaire and Guidelines, the dietary data collected were computed into nine food groups for women (starchy staples; dark green leafy vegetables; vitamin-A-rich fruits and vegetables; other fruit and vegetables; organ meat; meat and fish; eggs; legumes, nuts and seeds; milk and milk products) and seven food groups for children (grains, roots and tubers; legumes and nuts; dairy products; flesh foods; eggs; vitamin-A-rich fruits and vegetables; other fruits and vegetables)( Reference Kennedy, Ballard and Dop 23 ). The dietary diversity score (DDS) was calculated by summing the number of unique food groups and then divided into tertiles.

Anthropometry

Selected mother–child pairs were invited to come to the village health centre or school early in the morning. Both populations were weighed without shoes or sandals and wearing light clothes using a balance with a precision of 0·1 kg (Body Composition Monitor Scale Tanita BC-543). Height was measured using a device with a precision of 0·1 cm (Shorr Board®). For children under 2 years, measurement of recumbent length was taken on an adjustable child-length measuring board with a precision of 0·1 cm (Shorr Board®). For children aged 6 months to 5 years, anthropometric Z-scores were calculated using the National Center for Health Statistics/WHO growth reference data of 2006( Reference de Onis, Onyango and Borghi 24 ). Anthropometric status was assessed by the following indicators: weight-for-age Z-score <−2 for underweight; height-for-age Z-score <−2 for stunting; and weight-for-height Z-score <−2 for wasting. For women, BMI was calculated as body weight (in kilograms) divided by the square of height (in metres). Women were classified using BMI cut-off points endorsed by WHO as underweight (BMI<18·5 kg/m2), normal (BMI=18·5–24·9 kg/m2), overweight (BMI≥25·0 kg/m2) and obese (BMI≥30·0 kg/m2)( 25 ).

Blood sampling and analysis

Just after anthropometry, venous blood (2 ml for women and 1 ml for children) was drawn by venepuncture into a sterile tube (no anticoagulant) by a licensed medical technician. Hb was measured immediately using the Hemocue 201® device according to the manufacturer’s instructions. Five free-falling drops of blood were collected on a pre-coded special chromatography filter paper (Whatman) and dried in the shade. The dried blood spots were protected from light and stored in a plastic bag with desiccant, and the packaged dried blood spots were preserved in a refrigerator (2–8°C). Then, the packaged dried blood spots were inserted into a rip-resistant envelope and sent by courier within 3 weeks to Craft Technologies, Inc. (Wilson, NC, USA), where retinol levels of the dried blood spots were estimated by the HPLC method( Reference Craft, Bulex and Valdez 26 , Reference Craft, Haitema and Brindle 27 ). The remainder of the blood sample was stored in a cool box and transported at a temperature of 4–8°C. Within 24 h of sample collection, serum was obtained by centrifugation at 3000 g for 10 min, then aliquoted into 0·2 ml pre-labelled PCR tubes (Sarstedt) and kept frozen at −20°C before being sent (within 3 weeks) on dry ice to VitMin Lab (Willstaett, Germany) for analysis of ferritin (SF), soluble transferrin receptor, body Fe stores, retinol-binding protein, C-reactive protein (CRP) and α1-acid glycoprotein (AGP) concentrations using a sensible sandwich ELISA technique.

Anaemia was defined according to WHO standards as Hb below 11 mg/dl for children aged 6 months to 5 years and below 12 mg/dl for non-pregnant women( Reference Craft, Bulex and Valdez 26 ). Subclinical inflammation was defined as CRP>5 mg/l and/or AGP>1 g/l. Four groups were defined based on CRP and AGP levels: (i) reference (normal CRP and AGP); (ii) incubation (raised CRP and normal AGP); (iii) early convalescence (raised CRP and AGP); and (iv) late convalescence (normal CRP and raised AGP). Corrected values of SF and retinol within inflammation groups were obtained by multiplying values by their respective group corrector factors: SF by 0·77 (incubation), 0·53 (early convalescence) and 0·75 (late convalescence); retinol by 1·13 (incubation), 1·24 (early convalescence) and 1·11 (late convalescence). For children 6–59 months, Fe deficiency (ID) was defined as SF<12 mg/l for the reference group, SF<15 mg/l for the incubation group and early convalescence group, and SF<22 mg/l for the late convalescence group. As for non-pregnant women, ID was defined as SF<15 mg/l for the reference group, SF<19 mg/l for the incubation group and early convalescence group, and SF<27 mg/l for the late convalescence group. Fe-deficiency anaemia (IDA) was defined as the combination of anaemia and ID( 28 , Reference Thurnham, McCabe and Haldar 29 ). Subclinical VAD was defined using WHO cut-offs as serum retinol <20 µg/dl for both populations( 28 , Reference De Pee and Dary 30 , Reference Thurnham, McCabe and Northrop-Clewes 31 ).

Statistical analysis

All statistical analyses were performed using the Stata statistical software package version 14 and statistical significance was set at P<0·05. To summarize data, categorical variables were expressed as percentages while continuous variables were expressed as arithmetic means, with the exception of SF, as the data were not normally distributed. SF concentrations were log-transformed before statistical analysis. Because of the high proportion of missing data for anaemia, ID, IDA and VAD (12–30 %), missing value analysis (using logistic regression and t test) was conducted and revealed that outcome data were missing completely at random. Multivariable logistic regression models for anaemia and micronutrient deficiencies were obtained by using a manual backward stepwise procedure. Age, sex and setting, considered biologically and statistically relevant, and all variables associated with each of the outcomes at the P<0·20 level were included. At the individual level, in addition to biological variables, factors representing supplements, DDS and infections were included. Consumption of protein (meat, egg, fish or cheese) foods per week and monthly frequency of fruits and vegetables consumption were also used as indicators of diet quality, as they were highly correlated with micronutrient intakes and were a key source of bioavailable forms of Fe and vitamin A. The underlying factors included household ethnicity, maternal education, maternal occupation, family size, access to health care, source of water and hygienic latrine use. SES, food insecurity and source of information were also considered. The major assumptions of logistic regression analysis (absence of multicollinearity and interaction among independent variables) were checked to be satisfied. The goodness of fit was assessed using the Hosmer–Lemeshow statistic. The adjusted odds ratio (AOR) and 95 % confidence interval were computed.

Results

Sociodemographic characteristics

Of the 767 mother–child pairs surveyed, food records were analysed for 765 mothers and 647 children, while anthropometric measurements were collected from 585 mothers, and weight and height were respectively collected from 682 and 609 children. Among the children, 48·9 % were male, mean age was 21·6 months and 50·9 % were under 2 years of age (Table 1). About 65·4 % of the children had received vitamin A supplements in the last 6 months and the children consumed an average 3 pieces of protein foods per week. The mean DDS was 3·1 (out of 7) food groups, while 39·8, 23·6 and 10·9 % of the children were stunted, underweight and wasted, respectively. As for women, the majority had no formal education (90·3 %) and most were aged 30–49 years. Their main occupation was farming and the mean consumption of protein foods was 6 pieces per week. The women’s mean DDS was 3·9 (out of 9) food groups and their mean BMI was 22·2 kg/m2. Among households, mean household size was 7·7 members and a majority was Muslim (92·1 %). About 21·1 % of households were food insecure and 33·0 % had no access to health care, whereas only 13·2 and 8·2 % had access to hygienic latrines and electricity connection, respectively. About 40 % of households consumed fruits and vegetables two or three times per month. The highest ethnic group was Gando (34·5 %) followed by Boo (23·9 %) and other ethnic groups (Peulh, Boko, and Bariba). The main source of information was radio (3·37 d/week).

Table 1 Characteristics of children, their mothers/caregivers and their households; Kalalé district, northern Benin, January–March 2014

sem, standard error of the mean; sep, standard of error of the prevalence; DDS, dietary diversity score.

* Protein foods included meat, egg, fish and cheese.

Agricultural/other labour=farming, livestock and hunting; services/business=small commerce, services, salaried employees and manual workers; others=students and unemployed/retired.

Safe source of water included water from a tap and other sources that were treated.

Anaemia, iron and vitamin A status of mothers and children

Anaemia was present in 47·7 % of women while their prevalence of ID was 18·3 %, with 11·3 % of them classified as having IDA (Table 2). The prevalence of VAD was also high, affecting 17·7 % of surveyed women. As for inflammation status, 3·1 % had elevated CRP only, 14·0 % elevated AGP only, and 5·1 % had elevated CRP and AGP. Anaemia affected more than three-quarters (82·4 %) of the children (Table 3). Their prevalence of ID and IDA was respectively 23·6 and 21·2 %. One-third of children had VAD, while 38·9 % had evidence of suboptimal biochemical status for both micronutrients. The children’s prevalence of infection was also high: elevated CRP 1·6 %, elevated AGP 29·8 %, and elevated CRP and AGP 21·2 %.

Table 2 Vitamin A and iron status indicators and prevalence of deficiencies among non-pregnant women of reproductive age; Kalalé district, northern Benin, January–March 2014

sem, standard error of the mean; sep, standard of error of the prevalence; SF, serum ferritin; BIS, body Fe stores; sTfR, soluble transferrin receptor; ID, Fe deficiency; IDA, Fe-deficiency anaemia; VAD, vitamin A deficiency; CRP, C-reactive protein; AGP, α1-acid glycoprotein.

* Anaemia defined as Hb<12 mg/dl.

ID defined as SF<15 mg/l (with AGP and CRP normal), <19 mg/l (with raised CRP), <19 mg/l (with raised AGP), <27 mg/l (with raised AGP and CRP) and using corresponding correction factors for SF concentration.

IDA defined as ID deficiency and Hb<12 mg/dl.

§ VAD defined as serum retinol <20 µg/dl (with serum retinol concentrations corrected where infection existed).

Elevated CRP (CRP>5 mg/l) and elevated AGP (AGP>1 g/l).

Table 3 Vitamin A and iron status indicators and prevalence of deficiencies among children aged 6–59 months; Kalalé district, northern Benin, January–March 2014

sem, standard error of the mean; sep, standard of error of the prevalence; SF, serum ferritin; BIS, body Fe stores; sTfR, soluble transferrin receptor; ID, Fe deficiency; IDA, Fe-deficiency anaemia; VAD, vitamin A deficiency; CRP, C-reactive protein; AGP, α1-acid glycoprotein.

* Anaemia defined as Hb<11 mg/dl.

ID defined as SF<12 mg/l (with AGP and CRP normal), <15 mg/l (with raised CRP), <15 mg/l (with raised AGP), <22 mg/l (with raised AGP and CRP) and using corresponding correction factors for SF concentration.

IDA defined as ID deficiency and Hb<11 mg/dl.

§ VAD defined as serum retinol <20 µg/dl (with serum retinol concentrations corrected where infection existed).

Elevated CRP (CRP>5 mg/l) and elevated AGP (AGP>1 g/l).

Associated factors of anaemia and deficiencies of iron and vitamin A in mothers

Logistic regression analysis (Table 4) revealed that infected and low-SES women had respectively 2·0 and 1·8 times greater risk of anaemia diagnosis (P<0·05). However, overweight showed a protective effect (AOR=0·46; 95 % CI 0·24, 0·88). On the other hand, significantly greater risk of ID was found for low DDS (AOR=2·13), low BMI (AOR=5·48), low fruits and vegetables consumption (AOR=4·12) and low frequency of listening to the radio (AOR=2·12), as well as in the Boo ethnic group (AOR=3·01) and households without a latrine (AOR=2·68). However, women’s involvement in business/service was negatively associated with maternal ID (AOR=0·20; CI 0·03, 0·95). Similar patterns of associations were also observed between the risk of IDA and maternal occupation, infection, and low fruits and vegetables consumption. However, women from large family size (AOR=4·02) had a significantly greater risk of IDA while women 30–39 years of age (AOR=0·40) had a significantly lower risk of IDA. As for maternal VAD, the major determinants identified were lack of education (AOR=3·89), lack of fruits and vegetables consumption (AOR=2·72), low consumption of protein foods (AOR=2·54) and low frequency of radio listening (AOR=1·40). However, high BMI (AOR=0·26; CI 0·07, 0·92) and some ethnicities (Boo, Boko and Bariba) showed a significant protective effect. Interestingly, women with ID had a significantly greater risk of VAD (AOR=1·60; CI 0·13, 4·30).

Table 4 Determinants of anaemia, iron and vitamin A statusFootnote * among non-pregnant women of reproductive age; Kalalé district, northern Benin, January–March 2014

ID, Fe deficiency; IDA, Fe-deficiency anaemia; VAD, vitamin A deficiency; AOR, adjusted OR; NWG, non-women’s group; WG, women’s group; ref., reference category; n/s, not retained in model.

* Twenty-five independent variables were initially entered into each logistic regression equation. Variables with a P value >0·2 were eliminated from the model (n/s). The reported AOR are adjusted for the independent variables remaining in the equation. Bold font indicates a statistically significant association.

Associated factors of anaemia and deficiencies of iron and vitamin A in children

With regard to household characteristics, the risk of presenting anaemia among children was significantly greater with untreated water consumption (AOR=2·18) and low frequency of radio listening (AOR=2·15; Table 5). Children were more prone to have ID in households with low SES (AOR=2·89), low frequency of radio listening (AOR=3·46) and large size of five or more residents (AOR=2·79), whereas significantly greater risk of VAD was observed among NWG children (AOR=2·88; CI 1·03, 6·25). Among the maternal variables, children of underweight mothers presented a greater risk of ID (AOR=4·06; 95 % CI 1·31, 12·62) and IDA (AOR=5·31; 95 % CI 1·40, 20·14) than children of mothers with normal weight. Children of farming mothers had a significantly greater risk of anaemia (AOR=2·42; 95 % CI 1·12, 5·22), ID (AOR=2·26; 95 % CI 1·06, 4·78) and IDA (AOR=4·60; 95 % CI 1·67, 12·62) compared with children of retired/student women, and children of 30–39-year-old mothers had greater anaemia risk (AOR=1·47) compared with children of younger women. Interestingly, children whose mothers had anaemia, IDA or VAD had equal significantly greater risk of deficiencies (AOR=2·42, 2·85 and 3·42, respectively). As for child characteristics, younger age (6–23 months) corresponded with a significantly greater risk of anaemia diagnosis, whereas 12–23-month-old children had higher risk of ID (AOR=1·39; 95 % CI 1·17, 5·21) and IDA (AOR=1·67; 95 % CI 1·05, 4·93). The prevalence of ID (AOR=2·17) and IDA (AOR=2·16) was also significantly increased among stunted children, whereas low child DDS resulted in greater prevalence of anaemia (AOR=2·51; 95 % CI 1·08, 5·86) and VAD (AOR=4·19; 95 % CI 1·52, 11·56). Finally, the occurrence of ID, IDA and VAD was significantly greater among children with infections (AOR=3·48, 1·85 and 3·12, respectively).

Table 5 Determinants of anaemia, iron and vitamin A statusFootnote * among children aged 6–59 months; Kalalé district, northern Benin, January–March 2014

ID, Fe deficiency; IDA, Fe-deficiency anaemia; VAD, vitamin A deficiency; AOR, adjusted OR; NWG, non-women’s group; WG, women’s group; ref., reference category; n/s, not retained in model.

* Thirty independent variables were initially entered into each logistic regression equation. Variables with a P value >0·2 were eliminated from the model (n/s). The reported AOR are adjusted for the independent variables remaining in the equation. Bold font indicates a statistically significant association.

Discussion

The present study showed that, according to the WHO classification( 28 ), the prevalence of anaemia was a severe public health problem in both women of reproductive age and their children aged 6–59 months (>40 %). In the last Benin DHS report, anaemia prevalence in the same study area was 66·6 % in children under 5 years of age and 42·4 % in women of reproductive age( 7 ). In the present study, the prevalence of anaemia in women and children is much higher, suggesting no improvement from 2011 to 2015. Several factors might explain these findings. First, although the health authorities in Benin included different strategies to reduce child malnutrition and low birth weight, and also vitamin A, Fe and iodine deficiencies through supplementation, food diversification and fortification( Reference Ngnie-Teta, Receveur and Kuate-Defo 13 , Reference Sablah, Klopp and Steinberg 32 Reference Buttriss, Stanner and Wyness 34 ), there is a lack of information to evaluate the coverage and effectiveness of these interventions at the regional level. Second, about 21 % of households in the study area were reported food insecure since farming, which is the primary means of survival, is limited to the rainy season( Reference Mitchikpe, Dossa and Ategbo 5 ). Diets are also based predominantly on starchy staples with little or no animal products and few fresh fruits and vegetables( Reference Alaofè, Zee and Dossa 1 , Reference Sodjinou, Agueh and Fayomi 2 , 7 ). According to the 2012 Benin DHS, only 28·3 and 33·8 % of children received the minimum diet diversity and minimum acceptable diet, respectively( 7 ), reflecting the higher rates of poverty and less diverse production portfolios in the study area. The prevalence of undernutrition among children in our sample was also greater than in the rest of the country (stunting 40 v. 37 %, wasting 11 % v. 5 %, underweight 24 % v. 17, respectively), again reflecting higher poverty rates. However, it is important to note that our data were obtained from a non-randomized study population; therefore, results should be interpreted with caution.

The measure of Fe status, not often included in surveys in Benin, indicated high prevalence of ID among women and children (>15 %), which highlights the significance of this nutritional deficit in the studied area. In 2013, Rohner et al.( Reference Rohner, Northrop-Clewes and Tschannen 35 ) found lower prevalence of ID among both populations in rural areas of the Ivory Coast: women 13·5 v. 18·3 % and children 8·6 v. 23·6 %. Geographical, economic, seasonal and behavioural variations of factors across these different settings may account for the difference. Contrary to Kassebaum et al.( Reference Kassebaum, Jasrasaria and Naghavi 36 ), ID accounted for a small proportion of anaemia (women 23·7 %, children 25·8 %) in the present study. A similar pattern of anaemia and ID was also observed by Nguyen et al. in Vietnam( Reference Nguyen, Gonzalez-Casanova and Nguyen 37 ), suggesting that causes for anaemia other than ID, such as other micronutrient deficiencies (vitamin A, folate or vitamin B12), intestinal parasites, malaria or haemoglobinopathies, could all be important factors. Haemoglobinopathies can cause a shift to the left in the Hb distribution, leading to more people having anaemia, while chronic inflammation can lead to anaemia through reduced erythropoiesis( Reference Williams and Weatherall 38 Reference Payandeh, Rahimi and Zare 42 ). Unfortunately, we do not have data to identify which of these factors caused the anaemia in the present survey. Finally, the fact that more than half of the ID was not associated with anaemia suggests that daily Fe intake of the study population was sufficient to allow normal physiological functions but not adequate to build Fe stores. About 39 % of children and 17 % of women had SF concentration <30 mg/l. This is particularly important for women of reproductive age, as Fe stores of 300–500 mg/kg before pregnancy are recommended( Reference Viteri and Berger 43 ).

VAD was also recognized as a public health problem among young children as more than 20 % were deficient, whereas it was mild in women (<20 %)( 28 ). The 2006 Benin DHS showed a national prevalence of VAD in children of 70 % and of 12 % for women in the study area( 9 ). Although significant progress has been reported in reducing the prevalence of VAD in children, the high prevalence of VAD among both populations suggests that efforts to prevent VAD have to be maintained and even strengthened, especially for the under 5-year-old children( Reference Serlemitsos and Fusco 44 , Reference Fiedler, Mubanga and Siamusantu 45 ). Eliminating VAD through biannual mass supplementation with vitamin A has been the focus of Beninese government efforts. About 65 % of children in our sample received vitamin A supplements in the last 6 months. Of concern in the present study is that about 40 % of the surveyed children were at risk of two coexisting micronutrient deficiencies. This result could explain why some interventions focused on single micronutrients such as Fe lack effectiveness in Benin. In India, for instance, vitamin A supplementation of deficient children resulted in a significant increase in Hb and serum Fe( Reference Mohanram, Kulkarni and Reddy 46 ). However, Stoltzfus found that vitamin A supplementation could not overcome ID in all settings( Reference Stoltzfus 47 ). Therefore, Beninese children need combinations of multi-micronutrient sources. Other complementary types of intervention, such as food fortification or food diversification, should also be planned and evaluated.

There is evidence that ID may result in low serum retinol due to impaired enzymatic activity for the synthesis of retinol-binding protein in the liver( Reference Oliveira, Michelazzo and Stefanello 48 ). Our positive associations between maternal VAD and ID may also be due to poor diet quality, which is an important determinant of both nutrient deficiencies in our study population( Reference Olumakaiye 49 ). Additionally, we found that a lack of fruits and vegetables in the diet was significantly associated with ID and VAD whereas low consumption of protein foods was significantly associated with VAD, indicating that lack of access to those varieties of food items eventually deteriorates further the dietary quality of the study population( Reference Desalegn, Mossie and Gedefaw 50 ). Inflammation (e.g. due to intestinal parasites or malaria) was also a risk factor for anaemia, ID, IDA and VAD, while higher risks of anaemia and ID were found in households drinking untreated water and without a latrine. These findings suggest that more work is needed on examining the implementation of the current policy and the role of other interventions such as improvements in sanitation and hygiene that could potentially contribute to its prevention( Reference Pasricha, Drakesmith and Black 51 ). Finally, strong differences were found by ethnicity in the odds of ID and VAD. These findings serve as an important indicator of inequities in nutrition in Benin and indicate the need for further analysis of micronutrient deficiencies among and within ethnic groups.

On the other hand, most of the usual social determinants (age, family size, occupation, education and SES) showed significant associations with anaemia, ID, IDA and VAD. A similar non-nutritional factors-related trend in micronutrient deficiencies has been documented among women and children earlier( Reference Darnton-Hill, Webb and Harvey 52 Reference Zerfu and Ayele 55 ). For example, low SES was associated with increased odds of anaemia and ID while mothers’ involvement in business/service was an important socio-economic factor for the non-occurrence of ID. This probably may be due to financial access to foods rich in Fe( Reference Desalegn, Mossie and Gedefaw 50 , Reference Osorio, Lira and Ashworth 56 , Reference Maryam, Hina and Khawaja 57 ). However, farming mothers in the present study had higher risk of anaemia and IDA compared with retired/student women, highlighting the need for appropriate behaviour change communication messages that could teach caregivers about the importance of dietary quality in a child’s general health. Finally, the risk of anaemia was significantly greater in our study for the 6–11 months age group and the risks of ID and IDA in the 12–23 months age group. The last DHS of infant and young child feeding practices in Benin showed that complementary foods for young children have low energy density and low protein and micronutrient content because cereal flours and cereal porridges are the most commonly used foods, which might increase the risk of ID( 7 , 58 ).

Although the present study provides useful data on prevalence of anaemia and vitamin A and Fe status in connection with dietary, socio-economic and demographic factors in vulnerable populations, it nevertheless has limitations. In Benin, seasonal undernutrition has been previously described as highly unpredictable, with considerable variations in the impact of seasonal stress within localities and even within households( Reference Mitchikpe, Dossa and Ategbo 5 ). Serum micronutrient levels may also be affected by the time of day of blood sample collection, the fasting status of the study subjects and/or the seasonality of certain conditions such as the incidence of endemic infectious diseases. Therefore, consecutive and prospective measures are needed to better explore these associations over time. In consequence, periodical and longitudinal measurements may be desirable to test the role of seasonality in micronutrient deficiency prevalence. In addition, our results might not be generalizable to the rural Beninese population due to the non-randomization of women’s groups, although no significant differences were found between WG and NWG. Another limitation of the present study is the lack of detailed information on vitamin A (timing of assessment) and Fe supplementation, which may provide useful information to explain the situation of micronutrient status in both populations studied. Finally, pre-analytical bias due to the complex field logistics and the samples’ transport might have occurred. To reduce these potential biases, detailed guidelines on sample collection, preservation and transport were prepared and piloted prior to the fieldwork.

Conclusion

In summary, our findings highlight that anaemia and ID are public health problems among rural women and children in the Kalalé district of northern Benin. However, an important outcome from the study, and contrary to expectations, was that ID accounted for a small proportion of anaemia in the study area. Although the prevalence of VAD has decreased in children compared with previous surveys, VAD is still high in both populations. Furthermore, children from 12 to 59 months of age were particularly at risk of two coexisting micronutrient deficiencies, which could limit the effectiveness of programmes to optimize status for some micronutrients. Consequently, coordinated multi-micronutrient interventions for this age group are urgently needed to improve food diversity and the quality of complementary feeding. The findings also show the potential importance of programmes aimed simultaneously at improving economic, social and environmental conditions. Given the paucity of previous data in rural populations in Benin, our results represent a starting point for future research. These call for a coordinated study in various parts of the country to substantiate the current data so that appropriate and beneficial strategies for micronutrient supplementation can be planned.

Acknowledgements

Acknowledgements: The authors thank the participants and the village delegates, nurses and enumerators who participated in the study. They wish to express their very special appreciation to ADESCA-ONG, specifically Amidou Mama Sambo, Zacharie Sero Tamou and Sandra Phillips whose contribution was central to this project. Financial support: This work was supported by the University of Stanford, Hellman Fellows Program at UC San Diego and the University of Arizona. The funders had no role in the design, analysis or writing of this article. Conflict of interest: None. Authorship: J.B. and R.N. participated in the design and interpretation of the reported results. H.A. and D.T. participated in the analysis of data. All the authors participated in drafting and revising the manuscript. Ethics of human subject participation: The study was approved by the National Ethics Committee for Health Research of Benin. Ethical clearance was obtained from the institutional review boards charged with the protection of human research subjects of the University of Arizona. All women were informed verbally about the aims and procedures of the study, and informed consent was obtained from all women and children, via their mother or guardian’s approval for the latter, before enrolment.

References

1. Alaofè, H, Zee, J, Dossa, R et al. (2008) Iron status of adolescent girls from two boarding schools in southern Benin. Public Health Nutr 11, 737746.CrossRefGoogle ScholarPubMed
2. Sodjinou, R, Agueh, V, Fayomi, B et al. (2009) Dietary patterns of urban adults in Benin: relationship with overall diet quality and socio-demographic characteristics. Eur J Clin Nutr 63, 222228.CrossRefGoogle ScholarPubMed
3. Ochola, S & Masibo, PK (2014) Dietary intake of schoolchildren and adolescents in developing countries. Ann Nutr Metab 64, 2440.CrossRefGoogle ScholarPubMed
4. Agueh, VD, Tugoué, MF, Sossa, C et al. (2015) Dietary calcium intake and associated factors among pregnant women in southern Benin in 2014. Food Nutr Sci 6, 945954.Google Scholar
5. Mitchikpe, CE, Dossa, RA, Ategbo, EA, Van et al. (2009) Seasonal variation in food pattern but not in energy and nutrient intakes of rural Beninese school-aged children. Public Health Nutr 12, 414422.Google Scholar
6. Honfo, FG, Hell, K, Akissoe, N et al. (2010) Diversity and nutritional value of foods consumed by children in two agro-ecological zones of Benin. Afr J Food Sci 4, 184191.Google Scholar
7. Institut National de la Statistique et de l’Analyse Économique & ICF International (2013) Enquête Démographique et de Santé du Bénin 20112012 . Calverton, MD: INSAE and ICF International.Google Scholar
8. Scaling Up Nutrition (2015) Strategic Processes for Scaling Up Nutrition, Benin. http://scalingupnutrition.org/sun-countries/benin (accessed November 2015).Google Scholar
9. Food and Agriculture Organization of the United Nations (2011) Profil nutritionnel de pays: République du Bénin, 2011. ftp://ftp.fao.org/ag/agn/nutrition/ncp/ben.pdf (accessed November 2015).Google Scholar
10. Mitchikpe, CE, Dossa, RA, Ategbo, EA et al. (2010) Growth performance and iron status of rural Beninese school-age children in post-and pre-harvest season. Afr J Food Agric Nutr Dev 10, issue 1; available at http://www.ajol.info/index.php/ajfand/article/view/51481 Google Scholar
11. Bodeau-Livinec, F, Briand, V, Berger, J et al. (2011) Maternal anemia in Benin: prevalence, risk factors, and association with low birth weight. Am J Trop Med Hyg 85, 414420.Google Scholar
12. Ouédraogo, S, Koura, GK, Accrombessi, MM. et al. (2012) Maternal anemia at first antenatal visit: prevalence and risk factors in a malaria-endemic area in Benin. Am J Trop Med Hyg 87, 418424.CrossRefGoogle Scholar
13. Ngnie-Teta, I, Receveur, O & Kuate-Defo, B (2007) Risk factors for moderate to severe anemia among children in Benin and Mali: insights from a multilevel analysis. Food Nutr Bull 28, 7689.Google Scholar
14. Alaofè, H, Burney, J, Naylor, R et al. (2016) Solar-powered drip irrigation impacts on crops production diversity and dietary diversity in Northern Benin. Food Nutr Bull 37, 164175.Google Scholar
15. Hamilton, D (2015) Slavery, Memory and Identity: National Representations and Global Legacies. New York/London: Routledge.Google Scholar
16. Institut National de la Statistique et de l’Analyse Économique (2004) Cahier des villages et quartiers de ville du département du Borgou. http://www.insae-bj.org/recensement-population.html/Cahiers Villages 2002/ALIBORI (accessed November 2015).Google Scholar
17. Nierenberg, D & Halweil, B (2011) State of the World 2011: Innovations that Nourish the Planet. Washington, DC: Worldwatch Institute.Google Scholar
18. Burney, J, Woltering, L, Burke, M et al. (2010) Solar powered drip irrigation enhances food security in the Sudano-Sahel. Proc Natl Acad Sci U S A 107, 18481853.CrossRefGoogle ScholarPubMed
19. Burney, JA & Naylor, RL (2012) Smallholder irrigation as a poverty alleviation tool in sub-Saharan Africa. World Dev 40, 110123.Google Scholar
20. Bruhn, M & McKenzie, D (2008) In Pursuit of Balance: Randomization in Practice in Development Field Experiments. Washington, DC: World Bank.Google Scholar
21. Vyas, S & Kumaranayake, L (2006) Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan 21, 459468.CrossRefGoogle ScholarPubMed
22. Gwatkin, D, Rutstein, S, Johnson, K et al. (2007) Socioeconomic differences in health, nutrition, and population within developing countries: an overview. Niger J Clin Pract 10, 272282.Google ScholarPubMed
23. Kennedy, G, Ballard, T & Dop, M (2011) Guidelines for Measuring Household and Individual Dietary Diversity. New York: FAO, Nutrition and Consumer Protection Division.Google Scholar
24. de Onis, M, Onyango, AW, Borghi, E et al. (2006) Comparison of the World Health Organization (WHO) Child Growth Standards and the National Center for Health Statistics/WHO international growth reference: implications for child health programmes. Public Health Nutr 9, 942947.Google Scholar
25. World Health Organization (1995) Physical Status: The Use and Interpretation of Anthropometry. Report of a WHO Expert Committee. WHO Technical Report Series no. 854. Geneva: WHO.Google Scholar
26. Craft, NE, Bulex, J, Valdez, C et al. (2000) Retinol concentration in capillary dried blood spots from healthy volunteers: method validation. Am J Clin Nutr 72, 450454.Google Scholar
27. Craft, NE, Haitema, T, Brindle, LK et al. (2000) Retinol analysis in dried blood spot by HPLC. J Nutr 130, 882885.CrossRefGoogle Scholar
28. World Health Organization (2006) Guidelines on Food Fortification with Micronutrients. Joint WHO/FAO Expert Consultation. Geneva: WHO.Google Scholar
29. Thurnham, DI, McCabe, LD, Haldar, S et al. (2010) Adjusting plasma ferritin concentrations to remove the effects of subclinical inflammation in the assessment of iron deficiency: a meta-analysis. Am J Clin Nutr 92, 546555.Google Scholar
30. De Pee, S & Dary, O (2002) Biochemical indicators of vitamin A deficiency: serum retinol and serum retinol binding protein. J Nutr 132, Suppl. 9, S2895S2901.Google Scholar
31. Thurnham, DI, McCabe, GP, Northrop-Clewes, CA et al. (2003) Effects of subclinical infection on plasma retinol concentrations and assessment of prevalence of vitamin A deficiency: meta-analysis. Lancet 362, 20522058.CrossRefGoogle ScholarPubMed
32. Sablah, M, Klopp, J, Steinberg, D et al. (2012) Thriving public–private partnership to fortify cooking oil in the West African Economic and Monetary Union (UEMOA) to control vitamin A deficiency: Faire Tache d’Huile en Afrique de l’Ouest. Food Nutr Bull 33, Suppl. 3, S310S320.Google Scholar
33. Omuemu, VO & Ofuani, IJ (2012) Knowledge and use of zinc supplementation in the management of childhood diarrhoea among health care workers in public primary health facilities in Benin-city, Nigeria. Glob J Health Sci 2, 68.Google Scholar
34. Buttriss, JL, Stanner, SA & Wyness, LA (2013) Nutrition and Development: Short- and Long-Term Consequences for Health. London: British Nutrition Foundation.Google Scholar
35. Rohner, F, Northrop-Clewes, C, Tschannen, AB et al. (2014) Prevalence and public health relevance of micronutrient deficiencies and undernutrition in pre-school children and women of reproductive age in Cote d’Ivoire, West Africa. Public Health Nutr 17, 20162028.Google Scholar
36. Kassebaum, NJ, Jasrasaria, R, Naghavi, M et al. (2014) A systematic analysis of global anemia burden from 1990 to 2010. Blood 123, 615624.Google Scholar
37. Nguyen, PH, Gonzalez-Casanova, I, Nguyen, H et al. (2015) Multicausal etiology of anemia among women of reproductive age in Vietnam. Eur J Clin Nutr 69, 107113.Google Scholar
38. Williams, TN & Weatherall, DJ (2012) World distribution, population genetics, and health burden of the hemoglobinopathies. Cold Spring Harb Perspect Med 2, a011692.Google Scholar
39. Gelaw, A, Anagaw, B, Nigussie, B et al. (2013) Prevalence of intestinal parasitic infections and risk factors among schoolchildren at the University of Gondar Community School, Northwest Ethiopia: a cross-sectional study. BMC Public Health 13, 1.Google Scholar
40. Bain, LE, Awah, PK, Geraldine, N et al. (2014) Malnutrition in Sub–Saharan Africa: burden, causes and prospects. Pan Afr Med J 15, 120.Google Scholar
41. Griffin, JT, Ferguson, NM & Ghani, AC (2014) Estimates of the changing age-burden of Plasmodium falciparum malaria disease in sub-Saharan Africa. Nat Commun 5, 3136.Google Scholar
42. Payandeh, M, Rahimi, Z, Zare, ME et al. (2014) The prevalence of anemia and hemoglobinopathies in the hematologic clinics of the Kermanshah Province, Western Iran. Int J Hematol Oncol Stem Cell Res 8, 33.Google Scholar
43. Viteri, FE & Berger, J (2005) Importance of pre-pregnancy and pregnancy iron status: can long-term weekly preventive iron and folic acid supplementation achieve desirable and safe status? Nutr Rev 63, Suppl. 2, S65S76.CrossRefGoogle ScholarPubMed
44. Serlemitsos, JA & Fusco, H (2001) Vitamin A Fortification of Sugar in Zambia 19982001. Washington, DC: MOST (US Agency for International Development Micronutrient Program).Google Scholar
45. Fiedler, JL, Mubanga, F, Siamusantu, W et al. (2014) Child Health Week in Zambia: costs, efficiency, coverage and a reassessment of need. Health Policy Plan 29, 1229.Google Scholar
46. Mohanram, M, Kulkarni, KA & Reddy, V (1977) Hematological studies in vitamin A deficient children. Int J Vitam Res 47, 389393.Google Scholar
47. Stoltzfus, R (1997) Effect of maternal vitamin A or β-carotene supplementation on iron deficiency anemia in Nepalese pregnant women, postpartum mothers and infants. In Report of the XVIII IVACG Meeting, Cairo, 1977, p. 86. Washington, DC: International Vitamin A Consultative Group.Google Scholar
48. Oliveira, JM, Michelazzo, FB, Stefanello, J et al. (2008) Influence of iron on vitamin A nutritional status. Nutr Rev 66, 141147.Google Scholar
49. Olumakaiye, MF (2013) Adolescent girls with low dietary diversity score are predisposed to iron deficiency in Southwestern Nigeria. ICAN Infant Child Adolesc Nutr 5, 8591.Google Scholar
50. Desalegn, A, Mossie, A & Gedefaw, L (2014) Nutritional iron deficiency anemia: magnitude and its predictors among school age children, southwest Ethiopia: a community based cross-sectional study. PLoS One 9, e114059.Google Scholar
51. Pasricha, SR, Drakesmith, H, Black, J et al. (2013) Control of iron deficiency anemia in low-and middle-income countries. Blood 121, 26072617.Google Scholar
52. Darnton-Hill, I, Webb, P, Harvey, PW et al. (2005) Micronutrient deficiencies and gender: social and economic costs. Am J Clin Nutr 81, Suppl. 5, S1198S1205.Google Scholar
53. Haidar, J (2010) Prevalence of anaemia, deficiencies of iron and folic acid and their determinants in Ethiopian women. J Health Popul Nutr 28, 359368.Google Scholar
54. Laillou, A, Van Pham, T, Tran, NT et al. (2012) Micronutrient deficits are still public health issues among women and young children in Vietnam. PLoS One 7, e34906.Google Scholar
55. Zerfu, TA & Ayele, HT (2013) Micronutrients and pregnancy; effect of supplementation on pregnancy and pregnancy outcomes: a systematic review. Nutr J 12, 1.Google Scholar
56. Osorio, MM, Lira, PI & Ashworth, A (2004) Factors associated with hemoglobin concentration in children of the State of Pernambuco, Brazil. Br J Nutr 91, 307315.Google Scholar
57. Maryam, F, Hina, R, Khawaja, T et al. (2011) Factors responsible for iron deficiency anemia in children. J Biomed Sci Res 3, 308314.Google Scholar
58. World Health Organization (2000) Complementary Feeding: Family Foods for Breastfed Children. Joint WHO/FAO Expert Consultation. Geneva: WHO.Google Scholar
Figure 0

Fig. 1 Study selection process (vit. A, vitamin A)

Figure 1

Table 1 Characteristics of children, their mothers/caregivers and their households; Kalalé district, northern Benin, January–March 2014

Figure 2

Table 2 Vitamin A and iron status indicators and prevalence of deficiencies among non-pregnant women of reproductive age; Kalalé district, northern Benin, January–March 2014

Figure 3

Table 3 Vitamin A and iron status indicators and prevalence of deficiencies among children aged 6–59 months; Kalalé district, northern Benin, January–March 2014

Figure 4

Table 4 Determinants of anaemia, iron and vitamin A status* among non-pregnant women of reproductive age; Kalalé district, northern Benin, January–March 2014

Figure 5

Table 5 Determinants of anaemia, iron and vitamin A status* among children aged 6–59 months; Kalalé district, northern Benin, January–March 2014