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Journal of Human Nutrition & Food Science

Cite this article: Stoltenburg A, Kemmer TM, Lauseng M, Gidvani VK, Lynch J, et al. (2016) Mapping of Anemia Prevalence in Rural Honduran Children Ages 6 to 60 Months. J Hum Nutr Food Sci 4(3): 1087.

*Corresponding authorTeresa M. Kemmer, International Nutrition Research Consultant, Wentworth, 195 Lake Ridge Dr., Wentworth, SD, 57075, USA, Tel: 301-633-3844: Email:

Submitted: 28 April 2016

Accepted: 07 June 2016

Published: 09 June 2016

ISSN: 2333-6706

Copyright© 2016 Kemmer et al.

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Research Article

Mapping of Anemia Prevalence in Rural Honduran Children Ages 6 to 60 MonthsAshley Stoltenburg1, Teresa M. Kemmer2*, Megan Lauseng3, Vinod K. Gidvani4, Julia Lynch5, Douglas Lougee6, Miguel Coello7, Wilmer E. Amador7, Ricardo Aviles7, Rosaura Velasquez Arriaga8, and Pravara Thanapura9

1Johnson and Wales University, USA2International Nutrition Research Consultant, USA3Watertown Veterans Affairs Outpatient Clinic and Prairie Lakes Healthcare System/Sodexo, USA 4San Antonio Military Medical Center, USA5Armed Forces Research Institute of Medical Sciences, Thailand6USSouthern Command, USA7JTF-Bravo, Soto Cano Air Base - Medical Element, Honduras8Health Region Nº 12 La Paz, Ministry of Health, Honduras9Engineering Resource Center, South Dakota State University, USA

Abstract

Within Honduras, anemia is a nationwide issue with a previously reported anemia prevalence of 39% in children age 6-59 months. Those living within the lowest quintile of wealth are at highest risk. The purpose of the study was to determine the prevalence of anemia in children aged 6-60 months living in rural Honduras, map the data collection points and classification of anemia severity by study area, and identify risk factors associated with anemia. Whole blood for analysis of hemoglobin level was obtained from 841 children living within four health regions including 16 health centers. Altitude, latitude, and longitude were obtained at each household using a handheld global positioning system. Age range of the children evaluated was 6.12-59.93 months. Overall prevalence of anemia in children was 29.8%. Based on health region, the prevalence of anemia was 29.5% in Santiago de Puringla, 33.1% in Lepaterique, 25.9% in Chinacla, and 26.5% in Santa Maria. Anemia classified by public health severity was mild in one health center, moderate in 13 health centers, and severe in two health centers. Based on World Health Organization standards, 56.5% of the children were stunted, 20.5% underweight, and 1.5% wasted. The child’s anemia status was positively associated with the mother’s having anemia (p=0.004). Other risk factors associated with anemia included altitude (p=0.012), child’s age (p<0.001), underweight (p=0.049), clinic distance > 1 hour walking from home (p=0.006), consumed meat < once per week (p=0.049), house constructed from material other than brick (p=0.049), no electricity in the household (p=0.049) and child breastfed > 24 months (p<0.001). Regression analysis was also utilized to determine significant predictors of anemia: mother’s literacy (p=0.032), father’s literacy (p=0.044), mother was anemic (p=0.014), child’s age (p<0.001), and walking distance from the clinic is > 1 hour (p=0.004).By targeting health centers at highest risk for anemia the Honduran Ministry of Heath can use this data to implement prevention measures as a means of reducing childhood morbidity.

Keywords•Anemia•Hemoglobin•Altitude•Global positioning system

ABBREVIATIONSGPS: Global Positioning System; DALYs: Disability-Adjusted

Life-Years; Hb: Hemoglobin; WHO: World Health Organization; HAZ: Height for Age Z-score, WAZ: Weight for Age Z-score; WHZ: Weight for Height Z-score; VAD: Vitamin A Deficiency; SPSS: Statistical Package for the Social Sciences; ESRI: Environmental Systems Research Institute; CDHAM: Center for Disaster and Humanitarian Assistance Medicine; USUHS: Uniformed Services University of the Health Sciences

INTRODUCTIONWithin Honduras, anemia is a nationwide issue and infants

belonging to the lowest quintile of wealth are particularly affected, as compared to those in the upper quintile [1]. It is estimated that

anemia affects 43% of children globally corresponding to 273 million children [2].

The true toll of anemia is hidden in the statistics of overall death rates, maternal hemorrhage, reduced school performance and lowered productivity [3]. Within the 36 focus countries evaluated, iron deficiency anemia was estimated to cause 1.6 million disability-adjusted life-years (DALYs) in children under the age of 5 years [4]. Anemia has a negative effect on child cognition and has been quantified as 1.73 lower IQ points per 10g/L decrease in hemoglobin [5]. Infants with iron deficiency anemia are developmentally at risk and providing iron-supplements earlier in development or before iron deficiency becomes severe or chronic, can be prevent and/or reverse adverse effects [6].

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Honduras is one of the poorest countries in Latin America with more than half of the population living in poverty [7]. Within Honduras, 39% of the population of children age 6-59 months is afflicted by anemia putting the country at moderate risk according to the World Health Organization (WHO) [2]. The infant mortality rate is 18.18 per every 1,000 live births in Honduras [7]. Within Honduras, major health care inequities exist and negatively impact the health conditions of the population [1]. The benefits to combating iron deficiency and anemia are substantial and treatment can raise national productivity levels by 20% [3].

The current study incorporates global positioning system (GPS) data and anemia mapping identifying regions most in need of nutrition and public health intervention. Mapping anemia provides information to make better evidence based decisions for interventions [8].The purpose of the study was to 1) determine the prevalence of anemia in children aged 6-60 months living in rural Honduras, 2) map the data collection points and classification of anemia severity by study area and 3) identify demographic, socioeconomic, and nutrition risk factors associated with anemia.

MATERIALS AND METHODSStudy participants, location and survey

Cross-sectional data was obtained from randomly selected households. The assessments were coordinated through the national and local Ministry of Health offices. Study participants were children, 6 to 60 months of age, living in the Santa Maria, Chinacla, Santiago de Puringla, and Lapaterique health municipalities of rural Honduras. Random sampling of children within the appropriate age range was completed using local health center records. One randomly selected child was assessed per household. A primary care provider provided written consent prior to assessment and data collection. Teams traveled to the households to obtain anthropometric measurements, blood samples, and survey information. Dietary intake was obtained via food frequency, food availability, food assistance and breastfeeding status and duration questions. Health information was obtained from immunization records and recorded or verbalized history of diagnosis or treatment for malnutrition, vitamin and or mineral supplementation, deworming medication and frequency of diarrheal illness. Demographic data was also obtained during the survey. Since surveys were conducted at the household level, construction materials and other specific household questions were obtained via visual inspection of the facility. Trained translators administered the survey.

Anthropometrics

Electronic Scale 890 (Seca, Vogel & Halke, Hammer Steindamm 9-25, Hamburg, Germany) was used to obtain weights to the nearest 0.10 of a kg. For children that were not able to stand on their own, the tare weight function was used. Stature (for children from 2 to 5 years) and recumbent infant length (for children < 2 years) were measured to the nearest 0.1 cm using the Infant/Child Shorrboard (Schorr Productions, Olney, MD). World Health Organization references were used to calculate height for age Z-score (HAZ), weight for age Z-score (WAZ), and weight for height Z-score (WHZ) [9]. Stunting (height for age),

wasting (weight for height), and underweight (weight for age) were defined using < -2 Z-scores [9].

Anemia

Hemoglobin (Hb) level was obtained using the HemoCue Blood Hemoglobin Photometer (HemoCue, Angelholm, Sweden) and was diagnosed in the field using the WHO age-specific cutoff Hb values of <11.0 g/dL (altitude adjusted) [10]. Anemia prevalence was classified by public health severity: severe was a prevalence of ≥ 40%, moderate was 20-39.9%, mild was 5-19.9%, and normal was ≤ 4.9% [10]. Children diagnosed with anemia were provided iron supplementation per local Ministry of Health guidelines, deworming medication, and nutrition education to promote improved iron intake and absorption. Anemic children were referred to their local health care facilities and the local clinics were provided a list of the anemic children for follow-up based on Ministry of Health standard guidelines.

Data Mapping

The latitude, longitude and altitude of each household were determined using the Garmin eTrex Vista CX (hiking companion) Global Positioning System. The GPS unit’s horizontal accuracy was approximately 0.01 kilometer (33 feet) and a systematic maximum distance error of 1.6 kilometers was applied to those collected GPS points with missing decimal information. The points on the maps represent the study children based upon their anemia status. Health center boundaries within each region were estimated by including all clustered points designated to obtain care within the health center. Inaccurate or missing latitudes and longitudes were not considered in health center boundary determination, but data was still included in all statistical analysis. Geographic Information Systems--ArcGIS® 9.2 software was used to create the series of maps. The data, used in the mapping process, was based on Media Kit—Environmental Systems Research Institute, Inc. (ESRI) Data & Maps of 2005 (i.e. country boundaries, political boundaries) and a set of GPS data in decimal degrees (i.e. randomly selected participant locations by health centers) collected specifically for this study. The ESRI data was used as a reference to integrate all data sets into the same geographic coordinate system—the World Geodetic System of 84 (WGS 84).

Statistical Analysis

The Statistical Package for the Social Sciences (SPSS, Chicago) version 22 and WHO Anthro Version 3.2.2 (2011) were utilized for data analysis. Participant data was analysed and then stratified into dichotomous groups for analysis using Chi-square statistics. Regression analysis was used to determine the relationships between anemia and variables of interest. Data analysis was completed at the 95% confidence level to determine significance.

Institutional Review Board approval

This study was conducted according to the Declaration of Helsinki guidelines and the University Human Subjects Internal Review Board approved the protocol.

RESULTS Of the 851 children evaluated, 50.6% were male. Age range of

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the children evaluated was 6.12-59.93 months and mean age was 32.0 ± 14.months. The mean ± SD HAZ was -2.20 ± 1.22, WAZ was -1.15 ± 1.05, and WHZ was 0.15 ± 0.94. Based on World Health Organization standards, 56.5% of the children were stunted, 20.5% underweight, and 1.5% wasted. The average number of individuals living within the household was 6.66. Child, parent, health, household demographics and socioeconomic indicators are provided in Table 1.

Hemoglobin was available for 841 of the children and the mean hemoglobin was 11.9 ± 1.3 g/dL. Overall prevalence of anemia in children was 29.8%. Hemoglobin was available for 757 of the mothers; 14% were anemic. Risk factors associated with anemia are displayed in Table 1. Table 2 presents the prevalence of anemia by region and health center. Regression analysis

was utilized to determine significant predictors of anemia in Honduran children age 6-60 months: mother’s literacy (p=0.032), father’s literacy (p=0.044), mother was anemic (p=0.014), child’s age (p<0.001), and walking distance from the clinic is > 1 hour (p=0.004).

Anemia mapping of participants by health center, study area and public health severity is shown in (Figure 1). Anemia prevalence for children less than 24 months of age was 46.4%. There was a statistical difference in the prevalence of anemia by age category in the health regions of Lepaterique, Chinacle, and Santa Maria (Figure 2). There was no significant difference in anemia prevalence by health region or by gender within the health regions.

DISCUSSION

Anemia prevalence

Anemia is identified as a significant health problem in less developed countries [2] and the current study further substantiates this with 29.8% of the children anemic.

Nestel et al. found 30% of children aged 12-71 months were anemic in Honduras [11]. The Pan American Health Organization estimates anemia prevalence at 40.2% in Honduran children aged 12 to 59 months [1]. Within rural Honduran children aged 6-36 months, the prevalence of anemia was reported at 39.8% [12].

Early prevention, discovery, and treatment of iron deficiency anemia in infancy are important to prevent its devastating long-term effects [11]. The most common form of anemia is caused by low levels of iron (or iron-deficiency anemia) [13]. Prevalence estimates for anemia are used to assess the severity of iron deficiency or iron deficiency anemia, recognizing that anemia can reflect both nutritional deficiencies and non-nutritional

Table 2: Prevalence of anemia by region and health center.

Region and Health Center Prevalence of AnemiaSantiago de Puringla Region 29.5

Santiago de Puringla 32.3El Ocotal 31.0Hornitos 28.2Cedritos 23.1

Lepaterique Region 33.1Mateo 50.0

Culguaque 41.2Las Tablas 38.7La Estancia 37.9Lepaterique 31.1

Mulhuaca 11.1Chinacla Region 24.8

Chinacla 24.8Santa Maria Region 26.5

San Jose 33.3Santa Maria 28.6

Planes 28.1Arenalitos 23.1Miratoro 20.0

Table 1: Child, parent, health, household demographics and socioeconomic indicators of Honduran children aged 6-60 months and the association with anemia.

Indicator Variable Percentage(mean ± SD) P-value

ChildGender femaleAge of the child Age < 2 yearsHeight for age z-score < -2Weight for age z-score< -2Weight for height z-score < -2Breastfed < 12 monthsBreastfed > 24 months Consumed meat < once per week

ParentsMother was anemicLiteracyMotherFather

Father attended <3 years of school Mother attended < 3 years of school

49.4 (32.06 ± 14.57)

33.356.520.51.5

20.3 19.7

88.4

14.0

71.079.957.055.0

0.437<0.001*<0.001* 0.734 0.049* 0.198 0.616 <0.001* 0.049*

0.004*

0.0720.1310.8840.833

Child’s HealthMore than 2 episodes of diarrhea in the

last 3 monthsTreated for malnutrition in the past

yearReceived Vitamin A supplement in the

last 12 monthsReceived vaccinations in the last 12

monthsDid not receive parasite medication in

the last 12 monthsDemographics and Socioeconomics

AltitudeHealth regionNo electricity in the householdHousehold had a radioLived in a one room householdHad piped water on the propertyHousehold had a latrineDistance from the clinic was greater

than one hour walking timeThe family had a child less than 5 years

of age dieReceived food assistanceRoof constructed of tileHouse constructed of adobe, sticks or

wood (not brick)

32.57.1

92.692.760.1

4,641.3 ± 789.2

16.583.225.772.968.049.118.94.6

56.6 91.2

0.5140.6800.8320.367

0.040*

0.012*0.310

0.049*0.4330.4630.1030.431

0.006*0.2980.6180.251

0.049*

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Figure 1 Anemia mapping of individual participants and public health severity classification by study area in Honduran children aged 6-60 months.

Figure 2 Prevalence of anemia in Honduran children aged 6-60 months based on health region and age category. *Indicates statistical significance (P <.05) in prevalence of anemia by age category by region)

factors, such as infections, inflammation, and thalassemia or hemoglobinopathy [14]. In non-malaria settings it is estimated that 60% of anemia is due to iron deficiency and 50% in malaria endemic areas [14,15]. Since Honduras is considered a malaria endemic area at altitudes < 3281 feet, within this study, it is estimated that 14.9 % of the anemia is due to iron deficiency.

Risk factors and underlying causes of anemia

This study revealed several risk factors associated with anemia. Socioeconomic status indicators including household construction material and the availability of electricity in the household were found to be associated with anemia. Low socio-

economic status as a risk factor for anemia reinforces previous findings [11,16-18]. Cordosa et al., reported that children liv-ing with families in higher income quartiles were less likely to have anemia than children living in lower income quartiles [17]. et al., reported that the type of floor in the house (an economic indicator) and being underweight were significantly associated with anemia [11]. Within this study parental literacy was associ-ated with anemia. Other studies have also revealed that parent’s level of education was associated with anemia [11,16]. Nine out of ten anemia sufferers live in developing countries and the most vulnerable, the poorest and the least educated are disproportion-ately affected by iron deficiency and anemia [3].

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The current study also found a significant association between underweight children and anemia. Impaired growth is a result of limited nutrient availability or utilization at the cellular level and these include negative consequences associated with inadequate protein-energy intake as well as micronutrient deficiencies [19]. Undernutrition, which includes both anemia and underweight, imposes costs: human costs of premature death which also implies economic costs, economic costs due to lost productivity and output, and the costs to the household and the health service of treating ill health associated with undernutrition [20]. Magalhaes and Clements reported that rural households versus urban households were at a significantly increased risk for anemia [18]. This study also revealed that the location of the home was a significant risk factor for anemia. In addition, children with long distances to the clinic or those living at higher elevations had a higher prevalence of anemia. The human body experiences physiological changes in order to compensate for the low partial pressure of oxygen at altitude and an increase in the concentration of circulating hemoglobin is one of the vital components in the process[21,22]. The physiological changes which allow this to occur are grouped together under the term “acclimatization”, while change that occurs over many generations in high altitude populations is known as “adaptation”. In order to cope with hypoxia, the body attempts to maximize the delivery of oxygen to the tissues [21,22].

Exclusive breast-feeding beyond 6 months is associated with developing iron deficiency as breast milk is no longer able to meet all of the infant’s requirements [23]. The present study found that children breastfed for > 2 years had an increased prevalence of anemia. In addition, children that consumed meat < once per week were also at significant risk for anemia. The majority of anemias result from lack of nutrients required for normal erythrocyte synthesis, principally iron, vitamin B12 and folic acid [24]. Nutritional anemias result from inadequate intake of iron, protein, vitamin B12, folic acid, pyridozine, ascorbic acid, copper and other heavy medals; therefore inadequate meat consumption can be a contributing factor of anemia [24].The quantity of iron absorbed from the diet is highly dependent on the dietary intake of iron enhancers or inhibitors. Heme containing foods, consisting predominately of red meats, contain highly bioavailable iron and promote the absorption of iron in less bioavailable food sources [25]. Research conducted by Moshe et al., determined that the high prevalence of anemia and iron deficiency, primarily in children 1.5 to 3 years old, was related to low red meat consumption [26]. Siegel et al., found that the introduction of complimentary foods after 6 months was associated with the prevalence of anemia and explained that the content of iron in the complimentary foods could be inadequate or that the complimentary foods are fed infrequently resulting in breast milk remaining the main source of food [27]. Iron supplementation from 4-9 months or 6-9 months significantly reduced iron deficiency anemia in a Honduran study [28]. A study from Engelmann et al., found that infants that received 27 g/day of meat versus 10 g/day had significantly higher hemoglobin values [29].

Within the current study, children < 24 month of age had a significantly higher prevalence of anemia than older children. Other studies have also reported similar findings. Late infancy

and early childhood are high risk timeframes for anemia due to iron requirements for rapid growth combined with low dietary intake of bioavailable iron [25,30,31]. ALmusaylim found that Honduran children < 24 months of age were more likely to have anemia than children aged 30 to 36 months [12]. Another study completed in Honduras found that children 12-23 months of age were more likely to be anemic than children 24-36 months of age, children 24-36 months of age were more likely to be anemic than children 36-47 months of age, and children 36-47 months of age were more likely to be anemic than children 48-71 months of age [11]. Other studies also support the age of the child as a risk factor for anemia [17,32-35].

Identifying contributing factors or underlying causes of anemia within these locations is essential for determining the appropriate intervention strategy. Children within the current study had a significantly higher prevalence of anemia if they had not received parasite medication in the last 12 months. Helminth infections are a significant contributing factor for anemia due to the malabsorption that ensues [8,16,18,36]. The mechanism that helminth infections lead to anemia includes blood loss, sequestration of red blood cells by the spleen, hemolysis by antibodies, and anemia of inflammation [37,38]. With parasite infections, synergistic effects that exacerbate anemia include multiple species infections and a high parasite burden [39,40]. Honduras has a high prevalence of helminth infections with greater than 20% of the population being affected [8]. Within the current study, 61% of the population reported receiving treatment for helminth infections over the past year.

Data mapping

This is the first anemia mapping study completed using actual data collection points within health regions of Honduras. Muthayya et al., utilized global mapping to present an estimate of the 1) population-adjusted hidden hunger associated DALYs and 2) total population-unadjusted disability adjusted life years attributed to micronutrient deficiencies [14]. They used two separate datasets to compile the hidden hunger indices and maps: 1) a database of the most up-to-date national prevalence estimates of anemia, stunting, vitamin A deficiency (VAD) in pre-school aged children, and iodine deficiency in school-aged children, for 190 countries for the years 1999-2009; and 2) data of the recent DALY estimates attributed to deficiencies of iron, zinc, vitamin A, and iodine for 192 countries. Using these datasets, hidden hunger maps and indices were created by 1) combining national prevalence estimates of anemia, stunting, and VAD for preschool-age, children, together with separately added estimates of iodine deficiency for school-age children; and 2) combining country-wide DALY estimates attributed to deficiencies of iron, zinc, and vitamin A for the population [14]. Estimates of anemia prevalence were obtained from two main sources: 1) the WHO Global Database on Anemia, a part of the Vitamin and Mineral Nutrition Information System; and 2) Demographic and Health Surveys. Only nationally representative prevalence data for preschool-age children (0-4.99 years) were included. For countries without national survey data, regression-based estimates developed by the WHO were used in their analyses [14].

The mean prevalence of anemia and the predictive

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geographical variation of number of children aged 1 to 4 years of age with anemia for 2011 were mapped by Magalhães and Clements [18]. They also completed a predictive geographical risk of anemia in children aged 1 to 4 years of age, based on a model-based geostatistical Bernoulli model and a predictive geographical variation of mean hemoglobin concentration model-based geostatistical Gaussian model [18]. They utilized national cross-sectional household-based demographic health surveys from 7,147 children aged 1–4 y in Burkina Faso, Ghana, and Mali in West Africa. They developed Bayesian geostatistical models to predict the geographical distribution of mean Hb and anemia risk, adjusting for the nutritional status of preschool children, the location of their residence, predicted parasite rate, and predicted prevalence of helminth infections [18].

Global estimates of the prevalence of anemia in infants and children aged 6–59 months have been mapped by country and it is estimated that 39% of Honduran children are afflicted by anemia [2]. The methods for mapping within this WHO study included: 1) identifying data sources for blood hemoglobin concentration and anemia through a systematic review, accessing and extracting data, and systematically assessing the population representativeness of data; 2) adjusting blood hemoglobin concentrations for altitude and smoking; and 3) utilizing a Bayesian hierarchical mixture model to estimate trends in the distribution of blood hemoglobin concentrations for children and for women of reproductive age by pregnancy status [2].

The worldwide public health significance for the prevalence of anemia in preschool age children for the years of 1993 to 2005 was also mapped and Honduras with an estimated prevalence of 29.9% was moderate [41]. Their estimates were based on data from the WHO Global Database on Anemia and data were collected from the scientific literature and through collaborators, including WHO regional and country offices, United Nations organizations, ministries of health, research and academic institutions, and non-governmental organizations [41].

Researchers mapped Demographic and Health Survey locations from West Africa using cluster coordinates in a geographic information system to predict the geographical risk of anemia in children aged 1–4 y based on a model-based geostatistical Bernoulli model [2]. Using this technique they were able to estimate the prevalence of mild, moderate and severe anemia in Burkina Faso, Ghana, and Mali [18]. Magalhaes and Clements successfully used a predictive mapping model to target specific regions with increased prevalence of anemia [18].

CONCLUSION The results of this study reflect the high prevalence of anemia

and associated risk factors within rural Honduran children aged 6-60 months and have been presented using geographical mapping by data collection points and health region. Child’s age, dietary intake, underweight, parasite treatment, mother’s anemia status, parental literacy, geographic location and socioeconomic indicators were all predictors of anemia. The information reported can aid in the identification of communities where anemia is likely to be found and will allow for monitoring and evaluation of the regions following interventions. The Honduran Ministry of Health will be able to use this information

and target the Santa de Puringla, Lepaterique, Chinacla, and Santa Maria regions to implement prevention measures as a means of reducing childhood morbidity.

ACKNOWLEDGEMENTSThis assessment project is a collaboration of the Honduran

Ministry of Health, Nutrition Department; San Antonio Military Medical Center; Joint Task Force Bravo, Honduras; The Center for Disaster and Humanitarian Assistance Medicine (CDHAM), Uniformed Services University of the Health Sciences (USUHS); and South Dakota State University. Funding was provided by the CDHAM, USUHS, Bethesda, MD; the Henry M. Jackson Foundation for the Advancement of Military Medicine; and United States Department of Agriculture, Agricultural Experiment Station HATCH Grant SD00H249-08. The contents of this article do not necessarily represent the views of the U.S. Military or the U. S. Government.

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