Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries: Evidence from nationally representative surveys

Dev Ram Sunuwar; Devendra Raj Singh; Narendra Kumar Chaudhary; Pranil Man Singh Pradhan; Pushpa Rai; Kalpana Tiwari

doi:10.1371/journal.pone.0236449

. 2020 Aug 13;15(8):e0236449. doi: 10.1371/journal.pone.0236449

Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries: Evidence from nationally representative surveys

Dev Ram Sunuwar ^1,^2,^*, Devendra Raj Singh ^2,³, Narendra Kumar Chaudhary ⁴, Pranil Man Singh Pradhan ⁵, Pushpa Rai ⁶, Kalpana Tiwari ⁷

Editor: Marly A Cardoso⁸

PMCID: PMC7425935 PMID: 32790764

Abstract

Background

Anemia remains a major public health challenge with high prevalence among women in South and Southeast Asian countries. Reductions in anemia rates have been stalled, despite the implementation of different maternal health and nutrition programs. This study aimed to assess the prevalence and factors associated with anemia among women of reproductive age in seven selected South and Southeast Asian countries.

Methods

This cross-sectional analysis utilized data from the most recent demographic and health surveys from seven selected South and Southeast Asian countries (Bangladesh, Cambodia, India, Maldives, Myanmar, Nepal, and Timor-Leste) between 2011 and 2016. This study included 726,164 women of reproductive age. Multiple logistic regression was performed to assess the factors associated with anemia among women for each country separately.

Results

The combined prevalence of anemia was 52.5%, ranged from 22.7% in Timor-Leste to 63% in the Maldives. Results from multiple logistic regression suggest that likelihood of anemia is significantly higher among younger women (15–24 years), women with primary or no education, women from the poorest wealth quintile, women without toilet facilities and improved water sources, underweight women, and women with more than one children born in last five years in most of the countries.

Conclusions

The prevalence of anemia is high among women of reproductive age in the seven selected South and Southeast Asian countries. The results of this study suggest that various household, environmental and individual factors contribute to the increased likelihood of anemia. Evidence-based, multidisciplinary policies and programs targeting mothers' health and nutrition status, in addition to scaling-up women's education and socioeconomic status, are warranted to combat anemia.

Introduction

Anemia, which is defined as a hemoglobin (Hb) concentration less than normal [1], remains a major public health challenge with a prevalence rate of 47% among non-pregnant and 52% in pregnant women in South and Southeast Asian (SSEA) countries [1,2]. Globally, approximately one-third of the population is affected by anemia and its epidemiology varies according to population age, sex, socio-cultural contexts, and geographical regions [2,3]. Women of reproductive age (WRA) are physiologically more prone to anemia due to persistent menstrual blood loss and the demands of repeated childbearing and pregnancy [4]. According to the World Health Organization (WHO), worldwide approximately 39% of WRA, 46% of pregnant women were affected by anemia in 2016 [5]. Anemia is associated with increased morbidity and mortality in women, child growth faltering, impairment of cognitive function, increased chances of various kinds of infection, loss of productivity from impaired work capacity resulting in substantial economic burden to the family and entire population [6–8].

The prevalence of anemia varies according to geographic regions. Sub-Saharan Africa (SSA) and South Asia had the highest prevalence of anemia across all age groups [9]. Likewise, at the country level, anemia among WRA is a moderate-to-severe public health problem (20% or greater as defined by WHO) in the majority of the developing countries [2,10]. Determinants and distribution of prevalence of anemia in a population include a complex interplay of political, ecological, social, and biological factors [4]. In most of the countries, anemia varies by socioeconomic factors such as education, household wealth status, occupation, and residence [2,6]. A pooled analysis conducted by Balarajan et al [6] reported that the risk of anemia among women living in the lowest wealth quintile, with no education, and also differed by urban or rural settings. Likewise, previous studies have highlighted the probable causes of anemia among women including undernutrition, repeated childbearing, pregnant and lactation, inadequate dietary intake during pregnancy, inadequate water hygiene and sanitation status, rural residency, and parasitic infection [11–13]. Though several causes are associated with anemia, iron deficiency anemia is the most common type of anemia worldwide that is usually caused by inadequate intake of iron-rich foods in regular diets and excessive loss of red blood cells or a combination of both [3]. Various studies conducted from the developing countries have reported a high prevalence of iron deficiency anemia among pregnant women [14,15]. In low and middle-income countries (LMICs), the causes of anemia can be broadly classified into three major groups: nutritional deficiencies, infectious diseases, and genetic hemoglobin disorders [16]. Anemic condition in mothers has multiple adverse health consequences, such as the increased risk of miscarriage, stillbirth, premature, and low birth weight [17–19]. Approximately 20% of maternal deaths are caused by anemia and it is also considered as an additional risk factor for 50% of all maternal deaths [15,20]. To prevent anemia among WRA, pregnant women, and young children, different approaches at population and individual levels have been implemented [21]. For example, micronutrient supplementation among adolescents girls and pregnant women, food fortification, provision of nutrition education, counseling, and iron-rich food-based diet plan to at-risk populations are strategies used to improve dietary diversity and quality [21,22].

Despite the noticeable progress in socio-economic and health status in the majority of low-income countries in the SSEA region, countries are still challenged with reducing a high burden of malnutrition among WRA [21]. The prevalence of anemia has declined from an estimated 40% in 1990 to an estimated 33% in 2016 with a decrease of roughly seven percentage points over this time [3]. However, the progress made in reducing the prevalence of anemia is far less than the expected and its socioeconomic burden, particularly in resource-poor countries, is still a major concern [3]. The prevalence of anemia among non-pregnant women in South Asian countries declined slightly from an estimated 53% in 1995 to an estimated 47% in 2011, whilst the prevalence of anemia among pregnant women in the same region was almost stagnant (53% in 1995 and 52% in 2011) [2]. The Southeast Asian region has little progress in the reduction of anemia among WRA [3]. Considering the slow progress in the reduction of anemia prevalence, during the 2012 World Health Assembly, the World Health Organization endorsed a target of a 50% reduction of anemia among women of reproductive age by 2025 [17,23]. Based on the global prevalence of 29–38% anemia among WRA in both pregnant and non-pregnant women in 2011, a reduction of 1.8–2.4% points per year would be required to meet this target [9]. The Sustainable Development Goals (SDGs) also outline targets under SDG-2 to reduce the different forms of malnutrition among children under five years of age, pregnant women, lactating mothers, adolescents girls, and older people [24].

To achieve the WHO global nutrition targets 2025 and nutrition targets of the Sustainable Development Goals-2030, it is necessary to generate adequate evidence on contextual determinants of anemia to contribute to the development of timely interventions in anemia prevention. In addition, exploring the commonalities and differences across the states in the South and Southeast Asia region can inform the regional policy. Although previous studies have attempted to estimate the prevalence of anemia, very few studies have utilized nationally representative data to investigate the prevalence and determinants of anemia among WRA in the SSEA region. Furthermore, the updated evidence on prevalence and factors associated with anemia among at-risk populations is lacking for the SSEA context.

Therefore, this study aims to identify the prevalence and factors associated with anemia among WRA in seven selected SSEA countries.

Methods

Data sources

This study utilized the data from the Demographic and Health Surveys (DHSs) of seven selected SSEA countries conducted between 2011 and 2016 (Bangladesh DHS 2011, Cambodia DHS 2014, India NFHS 2016, Maldives DHS 2016, Myanmar DHS 2015, Nepal DHS 2016, and Timor-Leste 2015). We excluded the remaining SSEA countries due to a lack of availability of data on anemia among WRA (15–49 years old). All WRA women from the selected countries were included in the analysis. DHS is large, nationally representative, household surveys which are usually conducted by in-country/local institutions and are funded by the United States Agency for International Development (USAID), with technical assistance from ORC (Opinion Research Corporation) Macro international Inc. Calverton, Maryland, USA [25].

The DHS datasets for the selected countries were obtained from the DHS program website (URL: https://www.dhsprogram.com/data/available-datasets.cfm) after receiving approval to access and download the DHS data file. All DHS utilizes a multistage cluster sampling design to provide representative estimates for all enumeration areas. Probability proportional to size (PPS) methodologies areas employed by DHS to include both rural and urban residence, followed by a random selection of households from within the selected clusters or enumeration areas. All surveys included sample weights in the dataset. A more detailed sampling methodology of DHS has been published elsewhere [26–32]. Trained interviewers collected data on socio-demographic factors, health, and nutrition status. All eligible women were interviewed by trained interviewers in a local language.

Analytic sample

WRA (pregnant and non-pregnant) with available data on anemia, complete socio-demographic, and nutritional information were included in the analysis. A total sample used in the analysis for each survey is given in S1 Table.

Outcome variables

According to the WHO, for non-pregnant and pregnant women aged 15–49 years, any form of anemia was defined as hemoglobin concentration <12 g/dL, and <11 g/dL respectively [1]. Hemoglobin level in capillary blood was assessed using HemoCue rapid testing technique in all seven SSEA countries. For further analysis of the outcome variable, the categories of anemia were further dichotomized into 'anemic' and 'not anemic'.

Predictor's variables

Predictors of anemia were selected based on the literature review to the risk of development of anemia among women in LMICs including the South and Southeast regions [2,4,6,16].

The variables used in this study were similar across the seven SSEA countries. The predictor' variables used in this study included household, environmental and individual factors. Household factors include residence, education level, wealth status, marital status, occupation, type of toilet facility use, and water source. The place of residences of the respondents was classified as rural and urban. The educational status was classified according to the DHS categories. The wealth index was already included in all datasets and further classified as poor middle and rich. The wealth index is a standardized measure, quantified using principal component analysis (PCA) from household assets [33]. The wealth index variables were already included in the DHS dataset as five quintiles ranked as poorest, poorer, middle, richer, and richest. In this study, we further re-categorized as poor (poorest and poorer), middle and rich (richer and richest) for analysis [13]. Marital status was classified as being married/living together, never in the union, and widowed/divorced/separated. The respondent's occupation was dichotomized as working and not working. Source of drinking water and type of toilet facility used were classified into improved and not improved. Similarly, individual factors include age, BMI, and iron supplementation during most recent pregnancy, birth spacing, and ever terminated pregnancy (Whether the respondent ever had a pregnancy that terminated in a miscarriage, abortion, and stillbirth), antenatal checkup (ANC) during pregnancy (number of antenatal visits during pregnancy), currently breastfeeding, and total children ever born. The age of the respondents was recoded into 15–24, 25–34, and 35–49 years. Body mass index (BMI) was categorized into underweight (<18.5 kg/m²), normal (18.5–24.9 kg/m²), overweight (25–29.9 kg/m²) and obesity (≥30 kg/m²) according to the WHO classification. Iron supplementation during most recent pregnancy, ever terminated pregnancy, and currently, breastfeeding was classified as no and yes. Birth spacing was categorized into none, one and more than one year. Antenatal checkup visits during the pregnancy were classified as no, less than five times, and more than or equals to five times visit.

Data analysis

Data were analyzed using Stata/MP version 14.1 (StataCorp LP, College Station, Texas). The 'svy' command was used to adjust for enumeration areas (EAs) and disproportionate sampling weight and non-response. The datasets from seven countries were pooled and merged for analysis. For each country, we estimated overall and country-level weighted prevalence rates and their 95% confidence intervals (CIs) of anemia among WRA. The weighted prevalence of anemia among WRA was examined according to household, and individual factors. Multiple logistic regression models were performed to assess the association between anemia and associated factors in each country. To prevent statistical bias in the multiple logistic regression model, we examined and reported multicollinearity among the predictor variables using variation inflation factors (VIF). In this study, we used "10" as a cut-off value for the maximum level of VIF [34]. Results were presented as adjusted odds ratio (aOR) with 95% confidence intervals (CIs). P-values <0.05 were considered as statistically significant. Additionally, ArcGIS software version 10.8 was used to generate the study area map, and base files of the administrative national boundaries for seven selected SSEA countries were obtained from Natural Earth [35].

Ethical consideration

The study protocols were reviewed and approved by the National Ethics Committee of the Bangladesh Medical Research Council, Cambodian National Ethical Committee for Health Research, Ethics Review Board of the International Institute for Population Sciences, Mumbai, India, Ethics Review Committee on Medical Research, Ministry of Health, Maldives, Ethics Review Committee on Medical Research, Ministry of Health and Sports, Myanmar, Nepal Health Research Council (NHRC), Timor-Leste Ministry of Health, [26–32] and the Institutional Review Board (IRB) of ICF Macro. We registered and requested for access to data from the DHS website (URL: https://www.dhsprogram.com/data/available-datasets.cfm) and received an approval to access and download the DHS data file. DHS programs collect data following written informed consent from each individual. This study did not include any identifying of individuals during the variables selection process.

Results

A total of 726,164 women aged 15–49 years were included in the pooled analysis of seven SSEA countries (Table 1).

Table 1. Socio-demographic information with weighted prevalence rates for anemia among women of reproductive age in seven South and Southeast Asian countries.

	Anemia status % (95% CI)
	Cambodia (DHS 2014)	India (NFHS 2016)	Maldives (DHS 2016/17)	Myanmar (DHS 2015)	Nepal (DHS 2016)	Timor-Leste (DHS 2016)	Bangladesh (DHS 2011)	SSEA %
N	11,286	679,445	6,653	12,489	6,414	4,201	5,676	726,164
Overall prevalence	45.3 [44.1, 46.5]	53.1 [52.8, 53.3]	63 [61.1, 64.9]	46.5 [45.1, 47.9]	40.7 [38.5, 42.9]	22.7 [21.1, 24.3]	42.4 [40.6, 44.2]	52.5 [52.3, 52.8]
Study variables
household factors
Residence
Urban	39.3 [37.4, 41.3]	50.8 [50.3, 51.3]	73.3 [69.3, 76.9]	46.4 [43.3, 49.5]	39.6 [36.8, 42.4]	24.7 [21.8, 28]	36.1 [32.5, 39.7]	50.5 [50, 50.9]
Rural	46.7 [45.3, 48.1]	54.25 [54, 54.5]	55.6 [53.8, 57.3]	46.5 [44.9, 48]	42.6 [39, 46.3]	21.7 [19.8, 23.6]	44.6 [42.5, 46.7]	53.6 [53.4, 53.8]
Education
No education	47.7 [44.4, 51.1]	56.4 [56.1, 56.7]	64.2 [55.9, 71.7]	44.9 [41.8, 48.1]	41.5 [38.2, 44.9]	24.6 [21.7, 27.6]	47 [43.8, 50.2]	55.8 [55.5, 56.2]
Primary	47.5 [45.8, 49.2]	54.6 [54.1, 55]	62.2 [59.2, 65.1]	47.2 [45.3, 49.1]	38.4 [34.2, 42.8]	23.8 [20.1, 28]	44.6 [41.8, 47.5]	53 [52.9, 53.9]
Secondary	42.6 [40.8, 44.3]	52.1 [51.8, 52.4]	60.7 [58.2, 63.1]	46 [43.9, 48.1]	42.6 [39.6, 45.7]	21.7 [19.7, 23.9]	39.1 [36.5, 41.6]	51.7 [51.4, 52.1]
Higher	37.5 [33.3, 41.8]	47 [46.9, 48.2]	69.6 [65.4, 73.5]	47.2 [43.6, 50.7]	36.7 [32.3, 41.3]	21.6 [17, 27.1]	42.4 [40.6, 44.2]	47.5 [46.9, 48.1]
Wealth status
Poor	1.1 [48.9, 53.1]	56.8 [56.5, 57.1]	56.7 [54.5, 58.9]	47.5 [45.5, 49.5]	37.1 [34.5, 39.9]	21.8 [19.3, 24.6]	48.9 [46.2, 51.6]	56.1 [55.8, 56.4]
Middle	44.5 [41.8, 47.2	53.3 [52.9, 53.7]	60.3 [56.9, 63.5]	47.4 [44.6, 50.2]	48.9 [45.1, 52.8]	23.6 [19.9, 27.8]	42.6 [39.1, 46.2]	52.8 [52.4, 53.2]
Rich	40.9 [39.2, 42.7]	49.6 [49.1, 50]	70.2 [66.4, 73.8]	45.2 [43, 47.3]	39.8 [36.4, 43.3]	22.9 [20.4, 25.6]	36.4 [33.7, 39.1]	49.2 [48.8, 49.5]
Marital status
Never in union	45.8 [43.6, 48.1]	52.4 [52.1, 52.8]	49.3 [47.1, 51.5]	35.1 [33.5, 36.6]	42.1 [38.5, 45.8]	20 [17.2, 23.1]	-	51.9 [51.5, 52.3]
Married/living together	44.7 [43.3, 46.1]	53.1 [52.8, 53.3]	44.6 [43.1, 46.2]	58 [56.3, 59.7]	40.7 [38.5, 42.9]	23.8 [22.1, 25.7]	42.3 [40.5, 44.1]	52.5 [52.3, 52.8]
Widowed/divorced/separated	49.4 [45.5, 53.3]	55.9 [55.1, 56.8]	49.4 [44.9, 54]	6.8 [6.1, 7.7]	31.6 [24.1, 40.1]	33.4 [23.8, 44.7]	43.7 [40.6, 44.2]	55.4 [54.6, 56.3]
Occupation
Not working	46.3 [43.7, 49.1]	52.9 [52.3, 53.5]	60.8 [58.5, 63.1]	47.4 [44.8, 49.9]	42.9 [39.6, 46.2]	22.8 [20.93, 24.9]	NA	51.8 [51.3, 52.3]
Working	45.1 [43.7, 46.4]	55 [54.1, 55.9]	65.1 [62.5, 67.5]	46.2 [44.7, 47.7]	39.7 [37.2, 42.2]	22.3 [20, 24.8]		50.8 [50.2, 51.5]
Toilet type
Improved	42.6 [41.1, 44.1]	50.7 [50.3, 51.1]	62.8 [60.8, 64.7]	45.5 [43.4, 47.6]	37.3 [35.1, 39.6]	21.8 [19.5, 24.4]	33.7 [29.1, 38.7]	50.3 [50, 50.7]
Not improved	49 [47.1, 50.8]	55.8 [55.5, 56.1]	67.7 [56.2, 77.4]	47.1 [45.3, 49]	51.9 [47.5, 56.3]	23.4 [20.9, 26]	42.4 [40.1, 44.8]	55.2 [54.9, 55.5]
Water source
Improved	NA	49.4 [48.9, 50]	69.5 [66.3, 72.6]	47 [44.8, 49.2]	31.2 [28.3, 34.3]	22.2 [20.4, 24.2]	25.9 [19.5, 33.6]	49.1 [48.6, 49.6]
Not improved		54.2 [53.9, 54.4]	45.4 [36.1, 55.1]	46 [44.3, 47.7]	44.5[42.1, 47]	23.5 [20.9, 26.2]	43.5 [41.6, 45.3]	53.8 [53.5, 54.1]
Individual factors
Age group (years)
15–24	46.6 [44.8, 48.5]	53.8 [53.4, 54.1]	60.7 [57.8, 63.5]	47.5 [45.3, 49.7]	43.5 [40.6, 46.5]	23.7 [21, 26.7]	41.6 [38.6, 44.6]	53.2 [52.9, 53.6]
25–34	42.3 [40.2, 44.5]	52.3 [52, 52.7]	63.6 [60.6, 66.4]	43.4 [41.4, 45.5]	41.3 [38.4, 44.2]	20.1 [17.8, 22.7]	42.6 [40.1, 45.1]	51.8 [51.4, 52.1]
≥35	47.1 [45, 49.1]	52.9 [52.6, 53.3]	64.3 [61.6, 66.9]	48.1 [46.2, 49.9]	36.7 [34, 39.6]	23.7 [20.9, 26.8]	42.9 [40.1, 45.7]	52.5 [52.2, 52.8]
BMI
Normal	46.5 [45, 48.1]	53.1 [52.8, 53.4]	65.8 [63.2, 68.4]	48.3 [46.7, 49.9]	42.6 [39.7, 45.5]	22.3 [20.3, 24.5]	41.7 [39.5, 43.9]	52.6 [52.3, 52.8]
Underweight	50.5 [47.3, 53.7]	58.6 [58.2, 59]	66.5 [60.8, 71.7]	52.4 [49.5, 55.3]	48.1 [44.6, 51.6]	24.2 [21.3, 27.3]	51.6 [48.4, 54.8]	58.1 [57.7, 58.5]
Overweight	37.6 [34.9, 40.4]	46.9 [46.4, 47.4]	60.1 [57.2, 62.9]	38.7 [35.9, 41.6]	30.6 [27.1, 34.3]	19.3 [14.8, 24.8]	32 [28.3, 35.9]	46.5 [45.9, 47]
Obesity	33.4 [27.1, 40.5]	46.8 [45.9, 47.7]	59.7 [56.2, 63.2]	37.4 [33.2, 41.8]	27.9 [22.2, 34.4]	26.7 [15.3, 42.2]	27.9 [20.6, 36.6]	46.6 [45.8, 47.5]
Iron intake
No	45.2 [43.2, 47.2]	56.7 [56.3, 57.2]	NA	43.8 [41.6, 45.9]	44.4 [41.5, 47.5]	27.2 [24.2, 30.4]	43.9 [41.3, 46.6]	55.6 [55.2, 56]
Yes	47.4 [37.6, 57.3]	54.7 [53.9, 55.5]		40.7 [34.3, 47.5]	38.1 [28.1, 49.1]	22.8 [19.2, 26.9]	30.9 [19.8, 44.9]	54.1 [53.4, 54.9]
Births in last 5 years
No birth	45.3 [44, 46.7]	51.9 [51.6, 52.2]	63.1 [60.8, 65.4]	47.5 [45.9, 49.2]	39.2 [36.9, 41.5]	20.4 [18.4, 22.6]	41.4 [39.2, 43.7]	51.5 [51.3, 51.8]
1	43.8 [41.4, 46.2]	54.7 [54.3, 55.2]	62.2 [59.3, 65.1]	42.4 [40.1, 44.6]	41.6 [38.3, 44.9]	25.6 [22.6, 28.7]	41.6 [38.9, 44.4]	53.8 [53.3, 54.2]
>1	51.2 [46.4, 56.1]	59.4 [58.8, 53.3]	64.5 [57.3, 71.1]	50.3 [45.3, 55.2]	52.1 [46.5, 57.6]	26.4 [22.3, 31]	53.5 [48.1, 58.8]	58.7 [58.2, 59.3]
Ever terminated pregnancy
No	45.5 [44.1, 46.9]	53.1 [52.8, 53.3]	63 [60.9, 65]	46.2 [44.7, 47.7]	40.9 [38.4, 43.4]	22.4 [20.8, 24.1]	42.1 [40.1, 44.1]	52.5 [52.3, 52.8]
Yes	44.7 [42.4, 47.1]	53.1 [52.5, 53.6]	63.1 [58.6, 67.3]	49 [45.8, 42.1]	40.1 [36.9, 43.4]	34.9 [23.1, 49]	43.4 [40.1, 46.8]	52.5 [52, 53]
ANC visits during pregnancy
No	48.1 [39.3, 56.9]	58.9 [58.2, 59.7]	81.3 [64.6, 91.2]	43.9 [38.2, 49.8]	47 [36.4, 57.7]	25.3 [19.6, 32.1]	46.2 [42.1, 50.5]	58.1 [57.3, 58.8]
<5 times	46.8 [44.1, 49.5]	57 [56.5, 57.4]	59.1 [44.8, 72.1]	44.9 [41.9, 47.9]	44.5 [41.2, 47.8]	28.2 [23.8, 33]	43.4 [40.1, 46.8]	56.1 [55.6, 56.4]
≥5 times	43.1 [40, 46.2]	53.6 [53, 54.4]	62.5 [59.8, 65.2]	41.9 [38.5, 45.9]	41.8 [35.8, 48.1]	24.6 [21.6, 27.9]	38.9 [32.3, 45.9]	52.9 [52.3, 53.6]
Currently breastfeeding
No	44.3 [43.1, 45.6]	52.2 [51.9, 52.4]	63.4 [61.3, 65.4]	46.3 [44.7, 47.8]	39.3 [37.1, 41.6]	22.1 [20.2, 24]	40.5 [38.5, 42.6]	51.7 [51.5, 51.9]
Yes	51.4 [48.5, 54.3]	57.7 [57.3, 58.1]	60.5 [56.5, 64.3]	47.7 [45, 50.2]	45.8 [42.2, 49.3]	25.5 [22.1, 29.4]	48 [44.9, 51.1]	57 [56.6, 57.4]
Total children ever born
No child	46.4 [44.4, 48.4]	51.7 [51.3, 52.1]	60.9 [58.1, 63.5]	48.7 [46.7, 50.7]	41.8 [38.2, 45.4]	20.8 [18.2, 23.6]	39.6 [34.8, 44.5]	51.3 [50.9, 51.6]
1–4	44 [42.4, 45.5]	53.5 [53.2, 53.7]	64.3 [62, 66.5]	43.9 [42.1, 45.6]	40 [37.7, 42.3]	24 [21.8, 26.4]	41.5 [39.6, 43.4]	52.9 [52.7, 53,2]
>4	49.4 [45.8, 52.9]	55 [54.4, 55.6]	62.4 [57.9, 66.7]	50.9 [47.4, 54.4]	42.3 [37.8, 46.9]	23.7 [20.4, 27.5]	48.6 [44.7, 52.6]	54.1 [53.6, 54.7]

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Percentage and frequency are weighted.

SSEA: South and Southeast Asia.

Prevalence of anemia among women of reproductive age

The overall weighted prevalence of anemia among these populations was 52.5% ranged from 22.7% in Timor-Leste to 63% in the Maldives (Fig 1). The prevalence of mild, moderate and severe anemia was 39.4%, 12.1%, and 1% respectively in this region. Whereas the prevalence of mild and moderate anemia was higher in the Maldives (mild anemia: 49.1% and moderate anemia: 13.3%) and lower in Timor-Leste (mild anemia: 18.5% and moderate anemia: 3.7%), while the prevalence of severe anemia was less than 1% in most of the countries except India (1%) (Fig 2 and Table 1).

The prevalence of anemia among WRA in pooled analysis was higher in rural areas compared to urban areas in most of the countries (ranged from 42.6% in Nepal and 54.2% in India), except Maldives (urban Vs rural: 73.3% Vs 55.6%) and Timor-Leste (urban Vs rural: 24.7% Vs 21.7%). In the pooled analysis, the prevalence of anemia was generally higher among the least educated women and the lower among the most educated women in Cambodia, India, Bangladesh, and Timor-Leste. However, in Maldives and Myanmar, the prevalence was highest in the most educated women. The prevalence of anemia among WRA was higher among the poorest economic class group in Cambodia (Poorest Vs richest: 51.1% Vs 40.9%), India (Poorest Vs richest: 56.8% Vs 49.6%), Bangladesh (Poorest Vs richest: 48.9% Vs 36.4%) and Mynamar (Poorest Vs richest: 47.5% Vs 45.2%). While the prevalence of anemia was highest in the middle-class group in Nepal and Timor-Leste. The prevalence of anemia was highest among the widow/divorced/separated women in all countries except Nepal and Myanmar where prevalence was higher among married women. Likewise, the prevalence was higher among those women who did not use not improving toilet facilities in all countries. Among WRA, the prevalence of anemia was highest among older age groups (≥35 years) in Cambodia (47.1%), Maldives (64.3%), Bangladesh (42.9%), and Myanmar (48.1%). The prevalence of anemia was highest among underweight nutritional status women in all countries. Among WRA, the prevalence of anemia was higher in those women who didn't consume iron supplementation during most recent pregnancy in all countries. Similarly, the prevalence was highest among those women who didn't ANC visit once in all countries except in Myanmar and Timor-Leste. The prevalence of anemia was highest among the women's having more than four children in Cambodia, India, Bangladesh and Maldives, and Nepal.

Factors associated with anemia among women of reproductive age

Various factors were associated with anemia in each country (Table 2). In environmental and household factors, women's having no education had higher odds of anemia compared to those who have attended higher level of education in India (aOR = 1.24), but in Cambodia (aOR = 1.37) and Timor-Leste (aOR = 1.47), women's who attended at least primary level of education were more likely to be anemic. Women who had poorer wealth status were more likely to be anemic compared to women with richer wealth status in Cambodia (aOR = 1.38), India (aOR = 1.15), Maldives (aOR = 1.61), Myanmar (aOR = 1.18) and Bangladesh (aOR = 1.35), but were less likely to be anemic in Nepal (aOR = 0.77). Women having widowed/divorced/separated were more likely to be anemic compared to never union women in Timor-Leste (aOR = 1.73), but higher odds of the increased risk of anemic among Maldivian women (aOR = 1.33). Conversely, married women were less likelihood of anemia in Cambodia (aOR = 0.84) and Myanmar (aOR = 0.78). Women who had a household with not improved toilet facilities were higher odds of anemia compared to improved toilet facilities in India (aOR = 1.14), Nepal (aOR = 1.63), and Timor-Leste (aOR = 1.34). Likewise, women who did not improve water sources were more likely to be anemic compared to those with an improved water source in India (aOR = 1.12).

Table 2. Multiple logistic regression analysis for factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries.

Study variables	Cambodia	India	Maldives	Myanmar	Nepal	Timor-Leste	Bangladesh
	aOR(95% CI)	aOR(95% CI)	aOR(95% CI)	aOR(95% CI)	aOR(95% CI)	aOR(95% CI)	aOR(95% CI)
Environmental and household factors^a
Residence
Urban	Ref	Ref	Ref	Ref	Ref	Ref	Ref
Rural	1.12(0.98–1.27)	1.02(0.98–1.05)	0.33(0.22–0.48)^***	1.01(0.84–1.20)	1.07(0.89–1.28)	0.77(0.63–0.95)^*	1.20(0.95–1.51)
Education
No education	1.29(0.97–1.69)	1.24(1.18–1.30)^***	0.72(0.32–1.57)	0.91(0.71–1.07)	1.01(1.80–1.27)	1.26(0.87–1.82)	1.36(0.94–1.95)
Primary	1.37(1.07–1.75)^*	1.11(1.06–1.18)^***	0.93(0.61–1.42)	0.95(0.77–1.17)	0.93(0.72–1.20)	1.47(1.01–2.14)^*	1.41(0.98–2.02)
Secondary	1.19(0.94,1.49)	1.11(1.06–1.15)^***	0.75(0.53–1.28)	0.86(0.72–1.03)	1.15(0.93–1.41)	1.20(0.87–1.64)	1.13(0.82–1.56)
Higher	Ref	Ref	Ref	Ref	Ref	Ref	Ref
Wealth status
Poor	1.38(1.17–1.64)^***	1.15(1.10–1.19)^***	1.61(1.05–2.47)^*	1.18(1.01–1.39)^*	0.77(0.65–0.91)^**	0.89(0.69–1.16)	1.35(1.07–1.70)^**
Middle	1.08(0.92–1.27)	1.02(0.98–1.05)	1.54(1.01–2.35)^*	1.15(0.96–1.36)	1.10(0.91–1.34)	0.97(0.76–1.26)	1.19(0.92–1.55)
Rich	Ref	Ref	Ref	Ref	Ref	Ref	Ref
Marital status							NA
Never in union	Ref	Ref	Ref	Ref	Ref	Ref
Married/living together	0.84(0.75–0.94)^**	0.97(0.94–1.00)	1.33(1.00–1.77)^*	0.78(0.70–0.87)^***	0.87(0.75–1.01)	1.22(1.01–1.47)^*
Widowed/divorced/separated	1.04(0.85–1.25)	0.99(0.92–1.06)	1.99(1.13–3.48)	0.92(0.75–1.12)	0.62(0.41–0.94)^*	1.73(1.04–2.89)^*
Occupation
Not working	Ref	Ref	Ref	Ref	Ref	Ref	NA
Working	0.93(0.82–1.05)	1(0.98–1.03)	0.97(0.80–1.17)	0.97(0.86–1.09)	0.96(0.82–1.11)	0.97(0.81–1.15)
Toilet type^¥
Improved	Ref	Ref	Ref	Ref	Ref	Ref	Ref
Not improved	1(0.89–1.12)	1.14(1.10–1.18)^***	2.09(0.64–6.78)	1.03(0.91–1.15)	1.63(1.36–1.96)^***	1.34(1.11–1.63)^**	0.99(0.77–1.26)
Water source^€
Improved		Ref	Ref	Ref	Ref	Ref	Ref
Not improved		1.12(1.09–1.16)^***	0.62(0.39–0.97)*	0.95(0.86–1.06)	1.59(1.34–1.88)	1.11(0.93–1.33)	1.43(0.96–2.13)
Individual factors^b
Age group (years)
15–24	1.04(0.85–1.25)	1.07(1.05–1.09)^***	0.78(0.61–0.99)^*	0.85(0.69–1.06)	0.92(0.72–1.17)	1.74(1.29–2.34)^***	1.16(0.94–1.42)
25–34	Ref	Ref	Ref	Ref	Ref	Ref	Ref
≥35	1.26(1.00–1.59)^*	1.03(0.99–1.07)	0.99(0.79–1.23)	1.05(0.85–1.28)	0.63(0.43–0.94)^*	1.16(0.83–1.62)	0.95(0.62–1.46)
BMI
Normal	Ref	Ref	Ref	Ref	Ref	Ref	Ref
Underweight	1.36(1.05–1.77)^*	1.31(1.27–1.33)^***	2.43(1.55–3.81)^***	1.16(0.89–1.51)	1.18(0.91–1.53)	1.05(0.79–1.40)	1.24(0.97–1.57)
Overweight	0.74(0.58–0.94)^*	0.76(0.74–0.78)^***	0.80(0.66–0.97)^*	0.65(0.52–0.80)^***	0.60(0.45–0.81)^**	0.84(0.56–1.26)	0.61(0.42–0.90)^*
Obesity	0.74(0.39–1.40)	0.76(0.73–0.81)^***	0.82(0.65–1.03)	0.39(0.27–0.58)^***	0.85(0.44–1.63)	1.31(0.59–2.88)	0.76(0.38–1.52)
Iron intake
No	0.85(0.56–1.28)	1.01(0.99–1.04)	-	1.13(0.94–1.51)	1.28(0.79–2.05)	1.11(0.86–1.41)	1.69(0.90–3.15)
Yes	Ref	Ref		Ref	Ref	Ref	Ref
Births in the last 5 years
No	Ref	Ref	Ref	Ref	Ref	Ref	Ref
1	-	-	-	-	-	-	-
>1	1.19(0.93–1.50)	1.16(1.13–1.18)^***	1.17(0.92–1.47)	1.15(0.92–1.44)	1.40(1.08–1.80)^**	1.22(0.95–1.56)	1.29(1.00–1.66)^*
ANC visits during pregnancy
No	1.03(0.69–1.52)	1.08(1.04–1.11)^***	2.10(0.93–4.73)	0.81(0.59–1.09)	1.06(0.67–1.67)	1.04(0.73–1.48)	1.12(0.79–1.58)
<5 times	1.10(0.95–1.31)	1.07(1.03–1.08)^***	1.23(0.85–1.82)	0.82(0.89–1.22)	0.94(0.71–1.22)	1.09(0.84–1.41)	1.05(0.76–1.46)
≥5 times	Ref	ref	Ref	Ref	Ref	Ref	Ref
Currently breastfeeding
No	0.70(0.59–0.83)^***	0.92(0.90–0.94)^***	1.23(1.03–1.45)^*	0.74(0.63–0.87)^***	0.91(0.69–1.18)	1.02(0.79–1.29)	0.65(0.53–0.80)^***
Yes	Ref	Ref	Ref	Ref	Ref	Ref	Ref
Total children ever born
No	Ref	Ref	Ref	Ref	Ref	Ref	Ref
1–4	-	-	-	-	-	-	-
>4	1.10(0.77–1.57)	1.09(1.05–1.14)^***	0.85(0.57–1.26)	1.51(1.16–1.98^**)	1.33(0.86–2.04)	1.19(0.86–1.65)	1.31(0.91–1.87)

Open in a new tab

aOR: adjusted odds ratio for the logistic regression.

^adenotes for the adjusted prevalence ratios and 95% confidence intervals for the logistic regression model which included environmental and household factors.

^bdenotes for the adjusted prevalence ratios and 95% confidence intervals for the logistic regression model which included individual factors.

***p<0.001

**p<0.01

*p<0.05.

^¥Improved toilet facility (flush toilet, piped sewer system, septic tank, flush/pour flush to pit latrine, ventilated improved pit latrine, pit latrine with slab, and composting toilet) [36].

^€Improved water source (piped water into dwelling, piped water to yard/plot, public tap or standpipe, tube well or borehole, protected dug well-protected spring and rainwater) [36].

In terms of individual factors among these populations, numerous factors were more likely to be anemic in most countries. The younger women (15–24 years) were more likely to be anemic compared to women in the age group of 25–34 years in India (aOR = 1.07) and Timor-Leste (aOR = 1.74), but ≥35 years age groups were less likely to be anemic in Nepal (aOR = 0.63), and Cambodia (aOR = 1.26). Being underweight (BMI<18.5 kg/m2) among WRA was more likely to be an increased risk of anemia compared to normal BMI in Cambodia (aOR = 1.36), India (aOR = 1.31) and Maldives (aOR = 2.43). Overweight and obesity were protective against the increased likelihood of anemia in Cambodia (aOR = 0.74), India (aOR = 0.76), Maldives (aOR = 0.80) Myanmar (aOR = 0.65), Nepal (aOR = 0.60) and Bangladesh (aOR = 0.61). Women who had more than one year of birth spacing were more likely to be anemic compared to no birth spacing in India (aOR = 1.16), Nepal (aOR = 1.40), and Bangladesh (aOR = 1.29). Among WRA, who never ANC visits during their pregnancy were more likely to be anemic compared to more than five times ANC visits in India (aOR = 1.08). Women who didn't currently breastfeed were more likely to be anemic than those with currently breastfeeding in Myanmar (aOR = 1.23), but not in Cambodia, India, Bangladesh, and the Maldives. Women who have more than four children were more likely of anemic compared to those with no children in India (aOR = 1.09) and Myanmar (aOR = 1.51).

Discussion

This study provides country-level prevalence and associated factors of anemia among WRA in seven selected SSEA countries. The prevalence of anemia was 52.6%, ranged from 22.7% in Timor-Leste to 63% in the Maldives. According to WHO guidelines, the prevalence of anemia with the level above 40% among WRA is a serious public health problem [37]. This reflect anemia as a major public health problem in SSEA countries [38]. In our study, the prevalence of anemia varied from country to country. The possible reason may be characterized by the different dietary patterns, geographical, and cultural factors in these countries [13]. The systematic analysis reported the prevalence of anemia among non-pregnant women in South Asian countries declined slightly from an estimated 53% in 1995 to an estimated 47% in 2011, whilst the prevalence of anemia among pregnant women in the same region was almost stagnant (53% in 1995 and 52% in 2011) [2]. In Southeast Asian countries, the prevalence of anemia was 21% in non-pregnant and 25% in pregnant women [2]. We assume that these findings are consistent with our results because four out of seven countries in this study were from South Asia with a larger representation and had a higher burden of anemia among WRA [2,3]. High prevalence of anemia among women from this region are attributed by the social and biological vulnerability within both household and community [39]. In SSEA countries, along with the nutritional anemia poverty and gender inequality also play a significant role in contributing anemia [3].

The present study found the various household factors: women with low socioeconomic status, lack of education, not improved toilet facilities and water sources were an important predictor of anemia in the SSEA countries, which is similar to determinants of anemia in studies from Bangladesh [40] Timor-Leste [41] India [42]. These results are also consistent with a multi-country study across the LMICs which found that women's years of education, wealth status, cultural norms, values, and behavior were important predictors of anemia among women [3]. The systematic review conducted across the low-income countries exhibited that the education level along with wealth and cultural norms and behavior were overarching determinants of anemia among women [6]. Yang et al [39] also reported that the prevalence of anemia was observed higher among those individuals with low socioeconomic status from LMICs. In contrast, women in poorer wealth status were less likely to be anemic in Nepal. The possible reason could be Nepal is an agrarian-based country and the eating pattern is almost the same for all [43]. Most of the Nepalese people consume iron-rich staple foods regardless of wealth status [43].

Women's level of education was not a determinant of anemia in Nepal, Maldives, and Myanmar. These findings are similar to Harding et al [11] results who found that women's education was not likely to be anemic in Nepal and Pakistan. Among women who belong to rural areas were less likely to be suffering from anemia in Maldives and Timor-Leste. Anemia is more prevalent in city areas than those with the rural areas in both countries (In Maldives: 73% in urban and 56% in rural areas and In Timor-Leste: 25% in urban and 22% in rural areas) [27,28]. According to the DHSs reports, Women living in urban areas with wealthier wealth status tended to increase anemia in these two countries [27,28]. The convergent findings could be attributed to the selection of apparently healthy women living in rural areas and non-endemic areas for malaria and hookworm infestation prone areas in both countries. Moreover, in the Maldives the traditional staple foods consumed in rural households are more diversified and rich in iron contains compared to other countries in the same region. Such diversified food patterns in the rural areas of Maldives might have a positive role in meeting the adequacy of iron requirements for the reproductive age of women [44,45].

This study found the prevalence of anemia was more prevalent in those households with not having improved toilets and water facilities. These findings are in line with the results from the nationally representative DHS dataset, where lack of toilet facility and water facility was more tended to increase the risk of anemia in Nepal, Pakistan, and Bangladesh [11,46]. In this study, women with underweight nutritional status (<18.5 kg/m² BMI) were more likely to be anemic in most of the South Asian countries. These findings are in line with a study from India [47], Bangladesh [40], Nepal, and Pakistan [11]. The possible reason could be exhibited by the fact that malnourished women have a greater chance of iron deficiency anemia which is usually associated with poor wealth status [48]. Our study found that the mothers who breastfeed their children are less likely to suffer from anemia in the case of Cambodia, India, Myanmar, and Bangladesh except for Maldives, Nepal, and Timor-Leste. Exclusive breastfeeding may reduce the anemia as it reduces the return of the menstrual cycle to 20–30 weeks. The lactating mothers who breastfed for two years had the lower odds of anemia than the mother who breastfed for one year's [49].

This study comprises of some limitations. First, due to the cross-sectional nature of data, it could not establish the causal pathway of the association between the predictors and explanatory variables. Second, comparable data on anemia among WRA were not accessible from all South and Southeast Asian countries, thus our analysis was limited to the selected seven South and Southeast Asian countries. Third, this study could not consider the assessment of dietary factors among women of reproductive age that might have attributed to the risk of development of anemia. Fourth, the DHSs data used from the seven different countries were taken from different years and periods between the surveys. Despite these limitations, the strengths of this study were the use of a multi-country population-based nationally representative samples. This study also provides important information on the prevalence and factors associated with anemia among WRA across this region using comparable datasets.

Conclusions

This study highlighted a high prevalence of anemia among WRA in seven selected SSEA countries. Multiple factors related to household, environmental, and individual were associated with the continued rises of anemia among WRA. Improved water and sanitation status, completion of recommended ANC visits, normal BMI status, and better household income status are crucial in reducing anemia in the SSEA region. The findings of the study urge the realistic multi-pronged approach to tackle the high prevalence of anemia across the countries in the region. Likewise, among WRA from low socio-economic status, having low nutrition education should be given high priority during both nutrition-sensitive and specific program implementation. Also, the existing national policies and programs need to be reviewed based on recent evidence to track the progress in meeting the WHO global nutrition targets 2025 and nutrition targets of SDGs 2030.

Supporting information

S1 Table. Data sources and sample size.

(DOCX)

Click here for additional data file.^{(13.3KB, docx)}

Acknowledgments

We would like to thank the DHS program, ICF international for providing us the data set for analysis.

Data Availability

We used data of Demographic and Health Surveys that are publicly available and can be freely downloaded upon the formal request from the DHS website (https://www.dhsprogram.com/data/available-datasets.cfm)

Funding Statement

The author(s) received no specific funding for this work

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PLoS One. doi: 10.1371/journal.pone.0236449.r001

Decision Letter 0

Marly A Cardoso

29 May 2020

PONE-D-20-10365

Prevalence and factors associated with anemia among women in seven South and Southeast Asian Countries: evidence from nationally representatives survey

PLOS ONE

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: This study aimed to assess the prevalence and factors associated with anemia among women of reproductive age (WRA) in seven selected South and Southeast Asian countries.

This study was a secondary analysis of the seven selected South and Southeast Asian countries. During the 2012 World Health Assembly, the World Health Organization endorsed a target of a 50% reduction of anemia among women of reproductive age by 2025. Therefore, the study deals with a well-updated subject.

Very few studies have utilized nationally representative data to investigate the prevalence and determinants of anemia among reproductive-aged women in the South and Southeast Asian context. With this, it adds important data.

Here are suggestions for the article.

Title

Suggestion: "Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian Countries: evidence from nationally representatives survey".

The insertion of the term "women of reproductive age" better specifies the study population. And, it would not lead to exceed the number of characters allowed.

Abstract

In lines 24, 28 and 31 of the Abstract section there is an abbreviation, which is not prohibited, but should be avoided in this part of the text, according to the rules of the journal. The inclusion of the term "women of reproductive age" in its entirety would not exceed the number of characters in the section (300). Or, this can be a term added in the title, also without exceeding the character limit of the title which would better define the population studied.

The keywords "associated factors" and "South Southeast Asia" were not found in the MESH descriptors.

The text is brief, presents the objective of the study, includes substantial results, focuses on positive and non-negative findings.

Introduction

The authors start from the macro idea, contextualize, and even identify the problem. The section is finished with the justification and the main objective of the work.

Methodology

Experiments, statistics, and other analyses were performed to a high technical standard and were described in sufficient detail.

Line 141 – change the unit gm/dl by g/dL for both hemoglobin <12g/dL and 11g/dL.

Line 142 – change Homocue for Hemocue.

In lines 146, 147 and 148, the authors say that the predictor variables were chosen according to the literature review. However, in the introduction they say that several approaches at the population level have been taken over the years, such as micronutrient supplementation among adolescent girls and women, food fortification, nutritional education, counseling and orientation of an iron-rich dietary plan for at-risk populations. However, these are not variables evaluated in the study.

In lines 154 and 155 the authors need to explain better that the "wealth index" is a measure calculated by DHS itself and that it is based on the possession of consumer goods. It was not clear how it was obtained and, above all, how the categories were categorized. The understanding that it is a variable calculated by DHS is only possible if the reader searches the DHS Program website further.

Line 159 defines abbreviations upon first appearance in the text of ANC.

The variable iron intake is mentioned in lines 158 and 162, but do not explain what type of iron intake was this: supplementation acquired by women, given by some public policy, homemade fortification, dietetics? In the discussion (line 337), the limitation of not having evaluated food consumption data is mentioned. This variable is external intake? It is not clear.

The research meets all applicable standards for the ethics of experimentation and research integrity.

Results

Table 2 -age group years - specify where women aged 35 entered. If it is in the third category express as ≥35 years.

Discussion

In line 297, a study that demonstrates the prevalence of anemia in an age group quite different from that of the study (children).

In lines 314 to 319, the authors return to the results of anemia prevalence in rural and urban areas, present a convergent reference to the finding, but do not discuss the possible causes of this.

In line 337, when they mention the absence of food intake data, they speak only of the intake of "mothers and children". They do not talk about the intake of non-pregnant women and the children's food intake would not reflect the mothers' food intake, because the eating pattern of such opposite age groups is different.

Conclusion

The conclusion section responds to the proposed objectives and closes the subject by resuming the justification of the study and makes a brief prospective observation of what should be done from the findings.

References

Almost all references are from the last 10 years.

Review formatting of article references by placing them in Vancouver style. Examples of changes that need to be made include:

- The issues of journals should come in parentheses - examples - References 12, 15, 18, 19, 20.

- You do not put pp. before referring to the pages of journals.

- Reference 20 - quote in the supplement standards.

- References 14 and 25 do not contain the names of journals.

- On the pages of the references use only the unit or dozen on the final pages mentioned.

The article can be published after the mentioned corrections.

Reviewer #2: PARECER PONE-D-20-10365

Prevalence and factors associated with anemia among women in seven South and Southeast Asian Countries: evidence from nationally representatives survey

The study aimed to assess the prevalence and factors associated with anemia in women of reproductive age in seven selected countries in South and Southeast Asia. Based on the most recent data obtained from the Demographic and Health Surveys (DHS) of these seven countries, they analyzed data from 726,164 women. Multivariable binary logistic regression was performed to assess the factors associated with anemia among women in each country separately. Therefore, it is of relevance to public health study, which used nationally representative sample and appropriate statistical analysis. With minor adjustments it will be in conditions of publication.

The introduction presents prolix writing and with redundant information or that should be in another section. For example, right in the second line of the introduction it defines the cutoff points for anemia, which is suitable for is in methods (as it is also). There is an exaggerated exploration of the factors associated with anemia, as well as prevalence values in different situations. Much of this information would be better used in the discussion, situating the results found.

Line 159 – “…ever terminated pregnancy, ANC during pregnancy”: ANC must be defined a priori.

Line 160-161 – delete the second BMI: BMI was categorized into underweight BMI...

Line 167 – “…analyzed using STATA/MP version 14.1” / Stata/MP, version 14.1

Line 190 – It refers to figure 1, but the figure shown is named as figure 2. By the way, the title of this figure should be more intelligible (self-sufficient), so that the reader can understand what it is about without having to resort to the text.

Line 219 – “...women who didn't consume iron in all countries.” Use more precise wording: although insufficient, some amount they consumed.

Line 227 – In the table title, write WRA in full.

Lines 247-248 – “The association of anemia among 15-49 years old women with environmental and individual factors was examined using the binary logistic regression model.” This has already been reported in methods.

Line 249 - Women's having... / women's having...

Lines 265-266 – “age groups 15-24 years was positively associated with an increased likelihood of anemia compared to age groups of 25-34…” the term positively seems misused. If the variables are categorical (and not ordinal or continuous) and the highest prevalence was in the youngest age group, how was the relationship positive? He's confused. Confirm the adequacy of this term in other parts of the article.

Line 296-301 – “The cross-sectional study from the DHS done in 27 Sub-Saharan Africa (SSA) between 2008 and 2014 found that the prevalence of anemia among children was 59.9% [33], which is slightly higher than our findings.” It makes no sense to compare data from children with those from women. If you want to use the information, make some bridge to make sense.

Line 333 – “This study comprises of some limitations. First, due to the cross-sectional nature of data, this study…” Delete the last this study.

Line 335 – “Second, Comparable data. / Second, comparable data…

Line 337 – “Third, dietary intake of mothers and children were not assessed…” the study does not address children.

**********

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Reviewer #1: No

Reviewer #2: Yes: HAROLDO DA SILVA FERREIRA

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PLoS One. 2020 Aug 13;15(8):e0236449. doi: 10.1371/journal.pone.0236449.r002

Author response to Decision Letter 0

11 Jun 2020

Manuscript ID: PONE-D-20-10365

Manuscript title: Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian Countries: evidence from nationally representative surveys

Dear Editor,

We would like to thank the reviewers for the specific and needful comments. We have modified the paper in response to the extensive and insightful reviewers' comments. Sincerest thanks for providing us an opportunity to submit a revised copy of our manuscript entitled "Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian Countries: evidence from nationally representative surveys" to esteemed Journal PLOS ONE. We appreciate the time and efforts that you and the reviewers have dedicated to providing your valuable feedback on our manuscript. We are grateful to the reviewers for their insightful comments on our papers. We believe the revisions have substantially improved our manuscript.

We have highlighted the changes within the manuscript where necessary. We hope that the manuscript is now suitable for publication. We look forward to hearing a positive response from you.

Here is a point-by-point response to the academic editor and reviewers' comments and concerns.

Academic editor comments and concern

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

Response: Thank you for your suggestions. We have revised the formatting of our manuscript as per the PLOS ONE's manuscript body formatting guidelines.

In your revised cover letter, please address the following prompts:

We will update your Data Availability statement on your behalf to reflect the information you provide.

Response: Thank you for your valuable suggestions and comments. We used data of Demographic and Health Surveys that are publicly available and can be freely downloaded upon the formal request from the DHS website (https://www.dhsprogram.com/data/available-datasets.cfm). As per the guidelines and regulations of DHS, the dataset obtained by the authors for the purpose of statistical reporting and analysis specifically for this paper is not allowed to share in the public domain. However, we have uploaded the modified datasets in the online manuscript submission system to be only shared with the journal editor/reviewers for the purpose of the manuscript review process.

We require you to either (a) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (b) remove the figures from your submission:

Response: Thank you very much for pointing out the important aspects of our manuscript. We assure you that the provided Fig1 contains a study area Map with anemia prevalence is copyright free. We created this map using Arc GIS software version 10.8 and base file of the administrative national and subnational bounderies for seven selected South and Southeast Asian (SSEA) country were obtained from the freely available copyright free resources Natural Earth (http://www.naturalearthdata.com/). The map was displayed by joining the prevalence of anemia with corresponding country. Also, we have mentioned this point within the manuscript, methods section of page number 9, line 187-189 within the revised manuscript.

Reviewers' comments:

Reviewer #1

Comment: This study aimed to assess the prevalence and factors associated with anemia among women of reproductive age (WRA) in seven selected South and Southeast Asian countries. This study was a secondary analysis of the seven selected South and Southeast Asian countries. During the 2012 World Health Assembly, the World Health Organization endorsed a target of a 50% reduction of anemia among women of reproductive age by 2025. Therefore, the study deals with a well-updated subject. Very few studies have utilized nationally representative data to investigate the prevalence and determinants of anemia among reproductive-aged women in the South and Southeast Asian context. With this, it adds important data.

Here are suggestions for the article.

Response: Thank you very much for your time spent and efforts to provide valuable comments on our manuscript.

Comments: Title Suggestion: "Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian Countries: evidence from nationally representatives survey".

The insertion of the term "women of reproductive age" better specifies the study population. And, it would not lead to exceed the number of characters allowed.

Response: Thank you very much for your valuable suggestion. We have added the term "women of reproductive age" accordingly in the title and where necessary within the revised manuscript.

Abstract

Comments: In lines 24, 28 and 31 of the Abstract section there is an abbreviation, which is not prohibited, but should be avoided in this part of the text, according to the rules of the journal. The inclusion of the term "women of reproductive age" in its entirety would not exceed the number of characters in the section (300). Or, this can be a term added in the title, also without exceeding the character limit of the title which would better define the population studied.

Response: Thank you for pointing this out. We have replaced the WRA with "women of reproductive age" in the abstract section and where necessary in our revised manuscript.

Comments: The keywords "associated factors" and "South Southeast Asia" were not found in the MESH descriptors.

The text is brief, presents the objective of the study, includes substantial results, focuses on positive and non-negative findings.

Response: Thank you for your suggestion. According to the PLOS ONE's Journal manuscript body formatting guidelines, guidelines for keywords are not mentioned (https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf). Also, most of the published articles have not used keywords in their article. Thus, in order to adhere to the manuscript body formatting guidelines, we removed all the keywords from the manuscript. However, we have submitted the appropriate keywords in the online manuscript submission form as per the PLOS one guideline.

Introduction

comments: The authors start from the macro idea, contextualize, and even identify the problem. The section is finished with the justification and the main objective of the work.

Response: Thank you very much.

Methodology

Comments: Experiments, statistics, and other analyses were performed to a high technical standard and were described in sufficient detail.

Response: Thank you.

Comments: Line 141 – change the unit gm/dl by g/dL for both hemoglobin <12g/dL and 11g/dL. Line 142 – change Homocue for Hemocue.

Response: Thank you for your comments. We have replaced the unit gm/dl with "g/dL" where necessary within the manuscript. Also, we have replaced the word Homocue with "Hemocue" in line 144 within the revised manuscript.

Comments: In lines 146, 147 and 148, the authors say that the predictor variables were chosen according to the literature review. However, in the introduction they say that several approaches at the population level have been taken over the years, such as micronutrient supplementation among adolescent girls and women, food fortification, nutritional education, counseling and orientation of an iron-rich dietary plan for at-risk populations. However, these are not variables evaluated in the study.

Response: Thank you. We agree with these constructive comments. We intended to explore the prevalence and factors associated with anemia among women of reproductive age in seven selected South and Southeast Asian countries. Based on the previous literature review regarding the risk of developing anemia among women in developing countries and the availability of data in the DHS dataset, we included household, environmental and individual factors as predictors' of anemia in our data analysis.. Meanwhile, we just underline the existing prevention and control strategy of anemia among women of reproductive age in the introduction section of our manuscript. These variables were not included because DHS does not collect this data. Even though these factors were not assessed in our study we believe highlighting these different approaches would provide the significance of the topic to the readers.

Comments: In lines 154 and 155 the authors need to explain better that the "wealth index" is a measure calculated by DHS itself and that it is based on the possession of consumer goods. It was not clear how it was obtained and, above all, how the categories were categorized. The understanding that it is a variable calculated by DHS is only possible if the reader searches the DHS Program website further.

Response: Thank you for pointing this out. We have added the "wealth index calculation through principal component analysis (PCA) which is a standardized measure from household assets" [1]. "The wealth index variables were already included in the DHS dataset as five quintiles ranked as poorest, poorer, middle, richer, and richest. In this study, we further re-categorized as poor (poorest and poorer), middle and rich (richer and richest) for the analysis purpose" [2] in page 7 and 8, line 156-161 within the revised manuscript.

Comments: Line 159 defines abbreviations upon first appearance in the text of ANC.

We agree with these constructive comments. We have added the full form of ANC with "Antenatal checkup" in the manuscript in line 166 within the revised manuscript .

Yes, we have included iron supplementation during the most recent pregnancy in our analysis and revised the sentence accordingly in lines 170-171 within the revised manuscript. Indeed, Iron deficiency anemia is considered as one of the most common nutritional deficiency anemia among pregnant women. Iron folic acid supplementation program has been implemented in most of the south and Southeast Asian countries. Considering the significant role of iron-folic acid supplementation to prevent the anemia among women of reproductive age, we incorporated the iron intake variable in the analysis.

Comments: The research meets all applicable standards for the ethics of experimentation and research integrity.

Response: Thank you very much.

Results

comments: Table 2 -age group years - specify where women aged 35 entered. If it is in the third category express as ≥35 years.

Response: Thank you for pointing this out. We have corrected the age group years in Table 2 with ">35 years".

Discussion

comments: In line 297, a study that demonstrates the prevalence of anemia in an age group quite different from that of the study (children).

Response: We removed the word children.

Comments: In lines 314 to 319, the authors return to the results of anemia prevalence in rural and urban areas, present a convergent reference to the finding, but do not discuss the possible causes of this.

Response: We agree with your valuable comments. We have added the relevant discussion in our revised manuscript in line 335-340 as "These convergent findings could be due to the selection of apparently healthy women living in rural areas and non-endemic areas for malaria and hookworm infestation prone areas in both countries. Moreover, in the Maldives the traditional staple foods consumed in rural households are more diversified and rich in iron contains compared to other countries in the same region. Such diversified food patterns in the rural areas of Maldives might have a positive role in meeting the adequacy of iron requirements for the reproductive age of women"[3,4].

Comments: In line 337, when they mention the absence of food intake data, they speak only of the intake of "mothers and children". They do not talk about the intake of non-pregnant women and the children's food intake would not reflect the mothers' food intake, because the eating pattern of such opposite age groups is different.

Response: Thank you for your comments. We have revised the sentence with "this study could not consider the assessment of dietary factors among women of reproductive age that might have attributed to the risk of development of anemia" in line 358-359 within the revised manuscript.

Conclusion

comments: The conclusion section responds to the proposed objectives and closes the subject by resuming the justification of the study and makes a brief prospective observation of what should be done from the findings.

Response: Thank you very much.

References

comments: Almost all references are from the last 10 years.

Review formatting of article references by placing them in Vancouver style. Examples of changes that need to be made include:

- The issues of journals should come in parentheses - examples - References 12, 15, 18, 19, 20.

- You do not put pp. before referring to the pages of journals.

- Reference 20 - quote in the supplement standards.

- References 14 and 25 do not contain the names of journals.

- On the pages of the references use only the unit or dozen on the final pages mentioned.

Response: We thank the reviewer for these important suggestions. We have corrected the references accordingly in our revised manuscript where necessary.

Reviewer #2:

Comments: Prevalence and factors associated with anemia among women in seven South and Southeast Asian Countries: evidence from nationally representatives survey

Response: Thank you very much for your time spent and efforts to provide valuable comments on our manuscript.

Comments: The introduction presents prolix writing and with redundant information or that should be in another section. For example, right in the second line of the introduction it defines the cutoff points for anemia, which is suitable for is in methods (as it is also). There is an exaggerated exploration of the factors associated with anemia, as well as prevalence values in different situations. Much of this information would be better used in the discussion, situating the results found.

Response: Thank you for your suggestion. We have revised the sentences accordingly in the introduction section of our revised manuscript. The cut-off points for anemia have been removed from the introduction section in line 48-49 and moved to the methods section accordingly in line 143-144 within the revised manuscript.

Also, we added the information in discussion section as " Stevens et al., (2013) reported the prevalence of anemia among non-pregnant women in South Asian countries declined slightly from an estimated 53% in 1995 to an estimated 47% in 2011, whilst the prevalence of anemia among pregnant women in the same region was almost stagnant (53% in 1995 and 52% in 2011)" [5] in line 303-306 within the revised manuscript.

Comments: Line 159 – “…ever terminated pregnancy, ANC during pregnancy”: ANC must be defined a priori.

Response: We have revised and elaborate the sentence ever terminated pregnancy as "Whether the respondent ever had a pregnancy that terminated in a miscarriage, abortion, and stillbirth" in line 168-170 within the revised manuscript with track changes. Also, Antenatal checkup (ANC) during pregnancy refers to the "number of antenatal visits during pregnancy" in line 165-167 within the revised manuscript.

Comments: Line 160-161 – delete the second BMI: BMI was categorized into underweight BMI...

Response: Thank you for pointing this out. We deleted the second BMI.

Comments: Line 167 – “…analyzed using STATA/MP version 14.1” / Stata/MP, version 14.1

Response: We replaced the word STATA/MP with "Stata/MP version 14.1" accordingly in line 176.

Comments: Line 190 – It refers to figure 1, but the figure shown is named as figure 2. By the way, the title of this figure should be more intelligible (self-sufficient), so that the reader can understand what it is about without having to resort to the text.

Response: Thank you for your comments. We have revised the title Fig 1 with "Prevalence of anemia among women of reproductive age by the geographical locations in seven South and Southeast Asia countries” in line 200-201, which implied to display the geographical pattern and distribution of anemia prevalence rate using the map in the selected seven South and Southeast Asian country. Also, the map implies the study area being chosen for the analysis. Also, we have modified the Fig 2 with "Prevalence of any form of anemia among women of reproductive age by country" in line 235 within the revised manuscript.

Comments: Line 219 – “...women who didn't consume iron in all countries.” Use more precise wording: although insufficient, some amount they consumed.

Response: We have added the sentence in the line 230 within the revised manuscript with "iron supplementation during most recent pregnancy" to make more clear to the readers.

Comments: Line 227 – In the table title, write WRA in full.

Response: Thank you for pointing out this. We have included the full form WRA with "women of reproductive age" in the revised title of both Table 1 and Table 2.

Comments: Lines 247-248 – “The association of anemia among 15-49 years old women with environmental and individual factors was examined using the binary logistic regression model.” This has already been reported in methods.

Response: Thank you for your suggestion. We have deleted this sentence accordingly.

Comments: Line 249 - Women's having... / women's having...

Response: We have changed the word “Women's” with "women's" accordingly in the line 261.

Comments: Lines 265-266 – “age groups 15-24 years was positively associated with an increased likelihood of anemia compared to age groups of 25-34…” the term positively seems misused. If the variables are categorical (and not ordinal or continuous) and the highest prevalence was in the youngest age group, how was the relationship positive? He's confused. Confirm the adequacy of this term in other parts of the article.

Response: We thank the reviewer for constructive comments. We have corrected the sentence in the line 277-279 within the revised manuscript with "the younger women (15-24 years) were more likely to be anemic compared with women in the age group of 25-34 years"[6].

Comments: Line 296-301 – “The cross-sectional study from the DHS done in 27 Sub-Saharan Africa (SSA) between 2008 and 2014 found that the prevalence of anemia among children was 59.9% [33], which is slightly higher than our findings.” It makes no sense to compare data from children with those from women. If you want to use the information, make some bridge to make sense.

Response: Thank you very much for your insightful comments. We have removed these sentences and added the more relevant evidence from the previous findings in the line 310-313 with “High prevalence of anemia among women from this region is attributed to the social and biological vulnerability within both household and community [7]. In SSEA countries, along with the nutritional anemia poverty and gender inequality also play a significant role in contributing anemia [8]” within the revised manuscript.

Comments: Line 333 – “This study comprises of some limitations. First, due to the cross-sectional nature of data, this study…” Delete the last this study.

Response: Thank you. We have deleted the “last this study" and revised the sentence to make it clearer in line 354-355 within the revised manuscript with track changes.

Comments: Line 335 – “Second, Comparable data. / Second, comparable data…

Response: We revised the word accordingly in line 356.

Line 337 – “Third, dietary intake of mothers and children were not assessed…” the study does not address children.

Response: Thank you very for your constructive comments and feedback. We have revised the sentence with "this study could not consider the assessment of dietary factors among women of reproductive age that might have attributed to the risk of development of anemia" in line 358-359 within the revised manuscript. We removed the word "children" in line 363.

We look forward to hearing a positive response from you soon.

Thank you.

Sincerely

On behalf of all co-authors

Mr. Dev Ram Sunuwar, Dietician/Researcher

Armed Police Force Hospital, Kathmandu, Nepal

Email: devramsunuwar@gmail.com

References

1. Rutstein SO, Johnson K. The DHS wealth index. Calverton, Maryland, USA: ORC Macro,. 2004.

2. Gautam S, Min H, Kim H, Id HJ. Determining factors for the prevalence of anemia in women of reproductive age in Nepal : Evidence from recent national survey data. 2019; 1–17.

3. Laxmi Pandey V, Mahendra Dev S, Jayachandran U. Impact of agricultural interventions on the nutritional status in South Asia: A review. Food Policy. 2016;62: 28–40. doi:10.1016/j.foodpol.2016.05.002

4. Nath P, P.B. Gaddagimath. Horticulture and Livelihood Security - Google Books. [cited 4 Jun 2020]. Available: https://books.google.com.np/books?id=pEJLDwAAQBAJ&pg=PA127&lpg=PA127&dq=iron+rich+food+in+rural+area+of+maldives&source=bl&ots=MTYgRIUWyO&sig=ACfU3U2ouD86JvsAP8ZNcgCb1NwAW8cJZQ&hl=en&sa=X&ved=2ahUKEwjz7oOmqeXpAhUCbisKHTXfAaUQ6AEwAXoECAoQAQ#v=onepage&q=iro

5. Stevens GA, Finucane MM, De-Regil LM, Paciorek CJ, Flaxman SR, Branca F, et al. Global, regional, and national trends in haemoglobin concentration and prevalence of total and severe anaemia in children and pregnant and non-pregnant women for 1995-2011: A systematic analysis of population-representative data. Lancet Glob Heal. 2013;1: e16. doi:10.1016/S2214-109X(13)70001-9

6. Kibret KT, Chojenta C, D’Arcy E, Loxton D. Spatial distribution and determinant factors of anaemia among women of reproductive age in Ethiopia: A multilevel and spatial analysis. BMJ Open. 2019;9: 1–14. doi:10.1136/bmjopen-2018-027276

7. Yang F, Liu X, Zha P. Trends in Socioeconomic Inequalities and Prevalence of Anemia Among Children and Nonpregnant Women in Low- and Middle-Income Countries. JAMA Netw open. 2018;1: e182899. doi:10.1001/jamanetworkopen.2018.2899

8. Kassebaum NJ, Jasrasaria R, Naghavi M, Wulf SK, Johns N, Lozano R, et al. A systematic analysis of global anemia burden from 1990 to 2010. Blood. 2014;123: 615–24. doi:10.1182/blood-2013-06-508325

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PLoS One. doi: 10.1371/journal.pone.0236449.r003

Decision Letter 1

Marly A Cardoso

24 Jun 2020

PONE-D-20-10365R1

Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries: evidence from nationally representative surveys

PLOS ONE

Dear Dr. Sunuwar,

Please address all minor suggestions pointed out by the two reviewers.

Please submit your revised manuscript by Aug 08 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Marly A. Cardoso, Ph.D.

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: No

**********

6. Review Comments to the Author

Reviewer #1: I believe that almost all comments were answered properly, which made the article clearer. Therefore, it can be published.

I suggest that in reference number 14 the name of the journal BMC Women’s Health be included, as this suggestion has not been heeded. However, after this correction, there is no need to return the article to the reviewers for further evaluation.

Reviewer #2: PLOS ONE

Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries: evidence from nationally representative surveys

PONE-D-20-10365R1

The authors responded to most of the suggestions presented in the previous version. However, there are still minor changes to be made before the manuscript is published. Next, I specify what these changes would be.

Line 33: The combined prevalence of anemia among women of reproductive age in the seven selected South and Southeast Asian countries was…

Change to: The combined prevalence of anemia was…

Line 28-30: (Bangladesh DHS 2011, Cambodia DHS 2014, India NFHS 2016, Maldives DHS 2016, Myanmar DHS 2015, Nepal DHS 2016, Timor-Leste 2015)...

Change to: (Bangladesh, Cambodia, India, Maldives, Myanmar, Nepal and Timor-Leste)...

Line 66: …conducted by Balarajan Y., et al (2011) reported that […] urban or rural settings [6].

Change to: …conducted by Balarajan et al. [6] reported that [...] urban or rural settings.

Line 113: Therefore, this study aims to identify […]: Start in a new paragraph.

Line 143: […] anemia was defined […]: Put a comma between g/dL and respectively: (g/dL, respectively)

Line 144: Hemoglobin level was assessed using capillary blood and the HemoCue rapid testing technique […]

Wouldn't that be better? Hemoglobin level in capillary blood was assessed using the HemoCue rapid testing technique […]

Line 173: […] than one year. ANC visits during […]. In Portuguese, does not start sentence with abbreviations or numbers. I am not sure if there is this rule in English (I am not an English speaker).

Line 206: Fig 1. Prevalence of anemia […]: Place after the next paragraph, in which fig. 1 is referred to for the first time.

Line 329: […]. Yang F et al. (2018) also reported […] middle-income countries [38].

Change to: […]. Yang et al. [38] also reported […] middle-income countries.

Other similar cases exist throughout the text and should be corrected.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: HAROLDO DA SILVA FERREIRA

PLoS One. 2020 Aug 13;15(8):e0236449. doi: 10.1371/journal.pone.0236449.r004

Author response to Decision Letter 1

28 Jun 2020

Manuscript ID: PONE-D-20-10365R1

Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian Countries: evidence from nationally representative surveys

Dear Editor,

Thank you very much for giving us an opportunity to submit a revised version of the manuscript entitled "Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian Countries: evidence from nationally representative surveys" to reputed Journal PLOS ONE. We have revised the paper in response to the extensive and insightful reviewers' comments. We appreciate the time and efforts that you and the reviewers have dedicated to providing your constructive feedback on our manuscript. We believe the revisions have substantially improved our manuscript.

We have highlighted the changes within the manuscript where necessary. We hope that the manuscript is now suitable for publication. We look forward to hearing a positive response from you.

Here is a point-by-point response to the academic editor and reviewers' comments and concerns.

Reviewers' comments:

Reviewer #1

Comment: I believe that almost all comments were answered properly, which made the article clearer. Therefore, it can be published.

Response: Thank you very much for your constructive comments and suggestions.

Comments: I suggest that in reference number 14 the name of the journal BMC Women’s Health be included, as this suggestion has not been heeded. However, after this correction, there is no need to return the article to the reviewers for further evaluation.

Response: Thank you very much for your valuable suggestion. We have included the name of the journal "BMC Women's Health" in the reference number 14 in the revised version of the manuscript.

Reviewer #2:

Comments: Line 28-30: (Bangladesh DHS 2011, Cambodia DHS 2014, India NFHS 2016, Maldives DHS 2016, Myanmar DHS 2015, Nepal DHS 2016, Timor-Leste 2015)...

Change to: (Bangladesh, Cambodia, India, Maldives, Myanmar, Nepal and Timor-Leste)...

Response: We thank the reviewer. We have revised the sentence accordingly in the revised version of the manuscript, line 28-29.

Comments: Line 33: The combined prevalence of anemia among women of reproductive age in the seven selected South and Southeast Asian countries was…

Change to: The combined prevalence of anemia was…

Response: Thank you for your suggestion. We have revised the sentence accordingly with "The combined prevalence of anemia was 52.5%, ranged from 22.7% in Timor-Leste to 63.% in the Maldives". in revised manuscript line 32-33.

Comments: Line 66: …conducted by Balarajan Y., et al (2011) reported that […] urban or rural settings [6].

Change to: …conducted by Balarajan et al. [6] reported that [...] urban or rural settings.

Response: Thank you for pointing this out. We have revised the sentence with " A pooled analysis conducted by Balarajan et al [1] reported that the risk of anemia among women living in the lowest wealth quintile, with no education, and also differed by urban or rural settings". in revised manuscript line 65-66

Comments Line 113: Therefore, this study aims to identify […]: Start in a new paragraph.

Response: We have made a new paragraph of the sentence "Therefore, this study aims to identify the prevalence and factors associated with anemia among WRA in seven selected SSEA countries" in the revised manuscript line 112-113.

Comments: Line 143: […] anemia was defined […]: Put a comma between g/dL and respectively: (g/dL, respectively)

Response: Thank you for your comments. We have put a comma between g/dL and respectively with "According to the WHO, for non-pregnant and pregnant women aged 15-49 years, any form of anemia was defined as hemoglobin concentration <12.0 g/dL, and 11 g/dL respectively" in the revised manuscript line 141.

Comments: Line 144: Hemoglobin level was assessed using capillary blood and the HemoCue rapid testing technique […]

Wouldn't that be better? Hemoglobin level in capillary blood was assessed using the HemoCue rapid testing technique […]

Response: Thank you for your valuable suggestions. We have revised the sentences with "Hemoglobin level in capillary blood was assessed using HemoCue rapid testing technique in all seven South and Southeast Asian countries. For further analysis of the outcome variable, the categories of anemia were further dichotomized as anemic and not anemic". in the revised manuscript line 142-143.

Comments: Line 173: […] than one year. ANC visits during […]. In Portuguese, does not start sentence with abbreviations or numbers. I am not sure if there is this rule in English (I am not an English speaker).

Response: Thank you for pointing out this. We agree with you. We have replaced “ANC” with "antenatal checkup" in the revised manuscript line 170.

Comments: Line 206: Fig 1. Prevalence of anemia […]: Place after the next paragraph, in which fig. 1 is referred to for the first time.

Response: Thank you for your suggestion. We have moved the Fig 1 legend after line 211 in the consequent paragraph and text reference of Fig 1 has been also provided in the line 205.

Comments: Line 329: […]. Yang F et al. (2018) also reported […] middle-income countries [38].

Change to: […]. Yang et al. [38] also reported […] middle-income countries.

Response: We have changed the sentence with “Yang et al. [2] also reported that the prevalence of anemia was observed higher among those individuals with low socioeconomic status from low and middle-income countries." accordingly in the revised manuscript, line 317.

Comments: Other similar cases exist throughout the text and should be corrected.

Response: We thank the reviewer for constructive comments. We have corrected it wherever necessary throughout the revised manuscript.

We look forward to hearing a positive response from you soon.

Thank you.

Sincerely

On behalf of all co-authors

Mr. Dev Ram Sunuwar, Dietician/Researcher

Armed Police Force Hospital, Kathmandu, Nepal

Email: devramsunuwar@gmail.com

References

1. Balarajan Y, Ramakrishnan U, Özaltin E, Shankar AH, Subramanian S V. Anaemia in low-income and middle-income countries. Lancet. 2011;378: 2123–2135. doi:10.1016/S0140-6736(10)62304-5

2. Yang F, Liu X, Zha P. Trends in Socioeconomic Inequalities and Prevalence of Anemia Among Children and Nonpregnant Women in Low- and Middle-Income Countries. JAMA Netw open. 2018;1: e182899. doi:10.1001/jamanetworkopen.2018.2899

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PLoS One. doi: 10.1371/journal.pone.0236449.r005

Decision Letter 2

Marly A Cardoso

1 Jul 2020

PONE-D-20-10365R2

Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries: evidence from nationally representative surveys

PLOS ONE

Dear Dr. Sunuwar,

The authors have made all changes requested by the reviewers. However, I have noted the use of the word "multivariable" instead of "multiple" regression models. Thus, please replace "multivariable" by "multiple" in the text and Tables when referring to multiple regression analyses.

Please submit your revised manuscript by Aug 15 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Marly A. Cardoso, Ph.D.

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

PLoS One. 2020 Aug 13;15(8):e0236449. doi: 10.1371/journal.pone.0236449.r006

Author response to Decision Letter 2

2 Jul 2020

Manuscript ID: PONE-D-20-10365R2

Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian Countries: evidence from nationally representative surveys

Dear Editor,

We would like to thank you for allowing us to submit a revised copy of our manuscript entitled "Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian Countries: evidence from nationally representative surveys" to reputed Journal PLOS ONE. We appreciate the time and effort that you and the reviewers have dedicated to providing your valuable feedback on our manuscript. We are grateful to the reviewers for their insightful comments on our papers. We believe the revisions have substantially improved our manuscript.

We have replaced the word "multivariable regression model" with "multiple logistic regression model" in the text and Tables when referring to multiple regression analyses. We hope that the manuscript is now suitable for publication.

We look forward to hearing a positive response from you.

Thank you.

Sincerely

On behalf of all co-authors

Mr. Dev Ram Sunuwar, Dietician/Researcher

Armed Police Force Hospital, Kathmandu, Nepal

Email: devramsunuwar@gmail.com

Here is a response to the academic editor's comments and concerns.

Comment: The authors have made all changes requested by the reviewers. However, I have noted the use of the word "multivariable" instead of "multiple" regression models. Thus, please replace "multivariable" by "multiple" in the text and Tables when referring to multiple regression analyses.

Response: Thank you very much for your constructive comments and suggestions. We have replaced the word "multivariable regression model" with "multiple logistic regression model" in the text and Tables when referring to multiple regression analyses within the revised version of the manuscript.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(13.5KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0236449.r007

Decision Letter 3

Marly A Cardoso

8 Jul 2020

Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries: evidence from nationally representative surveys

PONE-D-20-10365R3

Dear Dr. Sunuwar,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Marly A. Cardoso, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0236449.r008

Acceptance letter

Marly A Cardoso

17 Jul 2020

PONE-D-20-10365R3

Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries: evidence from nationally representative surveys

Dear Dr. Sunuwar:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Marly A. Cardoso

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Data sources and sample size.

(DOCX)

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Data Availability Statement

[pone.0236449.ref001] 1.World Health Organization; Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. Geneva: World Health Organization, 2011. Available: http://www.who.int/vmnis/indicators/haemoglobin.pdf [Google Scholar]

[pone.0236449.ref002] 2.Stevens GA, Finucane MM, De-Regil LM, Paciorek CJ, Flaxman SR, Branca F, et al. Global, regional, and national trends in haemoglobin concentration and prevalence of total and severe anaemia in children and pregnant and non-pregnant women for 1995–2011: A systematic analysis of population-representative data. Lancet Glob Heal. 2013;1: e16 10.1016/S2214-109X(13)70001-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236449.ref003] 3.Kassebaum NJ, Jasrasaria R, Naghavi M, Wulf SK, Johns N, Lozano R, et al. A systematic analysis of global anemia burden from 1990 to 2010. Blood. 2014;123: 615–624. 10.1182/blood-2013-06-508325 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0236449.ref004] 4.McLean E, Cogswell M, Egli I, Wojdyla D, De Benoist B. Worldwide prevalence of anaemia, WHO Vitamin and Mineral Nutrition Information System, 1993–2005. Public Health Nutr. 2009;12: 444–454. 10.1017/S1368980008002401 [DOI] [PubMed] [Google Scholar]

[pone.0236449.ref005] 5.World Health Organization. Global Health Observatory data repository: Prevalence of anaemia in women Estimates by country. In: World Health Organization; [Internet]. 2017. [cited 7 Feb 2020]. Available: http://apps.who.int/gho/data/view.main.GSWCAH28v?lang=en [Google Scholar]

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PERMALINK

Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries: Evidence from nationally representative surveys

Dev Ram Sunuwar

Devendra Raj Singh

Narendra Kumar Chaudhary

Pranil Man Singh Pradhan

Pushpa Rai

Kalpana Tiwari

Roles

Abstract

Background

Methods

Results

Conclusions

Introduction

Methods

Data sources

Analytic sample

Outcome variables

Predictor's variables

Data analysis

Ethical consideration

Results

Table 1. Socio-demographic information with weighted prevalence rates for anemia among women of reproductive age in seven South and Southeast Asian countries.

Prevalence of anemia among women of reproductive age

Fig 1. Map showing the prevalence of anemia among women of reproductive age in seven selected South and Southeast Asian countries.

Fig 2. Prevalence of any form of anemia among women of reproductive age by country.

Factors associated with anemia among women of reproductive age

Table 2. Multiple logistic regression analysis for factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries.

Discussion

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Marly A Cardoso

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Author response to Decision Letter 0

Decision Letter 1

Marly A Cardoso

Roles

Author response to Decision Letter 1

Decision Letter 2

Marly A Cardoso

Roles

Author response to Decision Letter 2

Decision Letter 3

Marly A Cardoso

Roles

Acceptance letter

Marly A Cardoso

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

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