{"paper_id":"5d7ba76f-d08c-4175-afd5-f40284b0738e","body_text":"Contribution of community health workers in the prevention of disease caused by malnutrition in Rwanda | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Contribution of community health workers in the prevention of disease caused by malnutrition in Rwanda Roger Muremyi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-41252/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Malnutrition affects physical growth, morbidity, mortality, cognitive development, reproduction, and physical work capacity, and it consequently impacts on human performance, health and survival. It is underlying factor in many diseases for both children and adults, and is particularly prevalent in developing countries, where it affects one out of every 3 preschool-age children. A well-nourished child is one whose weight and height measurements compare very well with standard normal distribution of heights and weights of healthy children of the same age and sex. Factors that contribute to malnutrition are many and varied. Objective The objective of the present study is to evaluate the contribution of community health workers in the prevention of diseases caused by malnutrition in Rwanda. Factors included: community health workers, place of residence (urban, rural), sex of child, marital status, antenatal care, breastfeeding, wealth index and education level. Methodology: We used data from NISR(DHS2014.2015) collected on child that covered 1137 Households. The results show that the level of wasting, stunting, and underweight in children under five years of age was 51.89%, 58.4% and 36.24% respectively. Findings: Malnutrition was significantly (p < 0.01) higher among boys than among girls. The prevalence of wasting and stunting decreased significantly by community health workers and antenatal care. The higher the level of parent’s education, the lower the level of child underweight observed. Breastfeeding was found to reduce the occurrence of underweight among children. Conclusion The study findings imply that efforts for redressing child under nutrition in Rwanda should focus on factors associated with development outcomes such as, community health worker’s improvements, parent’s education, and the creation of employment or economic engagements that do not comprise important child care practices such as breastfeeding and antenatal care. Health Economics & Outcomes Research Health Policy community health workers prevention of disease malnutrition in Rwanda 1. Introduction Over the last three centuries following the 1978 Alma Ata Declaration on Primary Health Care (PHC), community health workers (CHWs) have been encouraged to become component of the health structures of many emerging nations. CHW programs were implemented in many of these nations in a top-down manner with comparatively restricted capability construction and scheduling. instead of being the leading edge of changed strategy to health care, CHWs often wound up becoming a badly resourced and undervalued expansion of the current health service- “just another couple of finger”(MINISTRY OF HEALTH, 2013). Worldwide, CHWs are used as a strategy to addressthe shortage of health workers, and render certainbasic health services to their communities (e.g. USA,China, Brazil, and South Africa)(Rwanda Governance Board, 2017). Depending on the specific needsof countries and communities, CHWs’ profiles vary interms of activities, scope; training among others. According to WHO (World Health Organization) definition of CHWs is that they should be: “members of the communities where they work; selected by the communities; answerable to the communities for their activities; supported by the health system but not necessarily a part of its organization; and, have shorter training than professional workers(Rwanda Governance Board, 2017). The Rwanda CHW Program was established in 1995 after Genocide, aiming at increasing uptake of essential maternal and child clinical services through education of pregnant women, promotion of healthy behaviors, and follow-up and linkages to health services. An estimated 45,000 CHWs operating at the village level provide the first line of health service delivery. There are three CHWs in each village: a male-female CHW pair providing basic care and integrated community case management (CCM) of childhood illness, and a CHW in charge of maternal health, called an ASM (Agent de Santé Maternelle). There are four main objectives of the program (1) strengthen the capacity of decentralized structures to allow community health service delivery; (2) strengthen the participation of community members in community health activities; (3) strengthen CHW motivation through CPBF to improve health service delivery; and (4) strengthen coordination of community health services at the central district, health center, and community levels. The program has since grown to include an integrated service package that include malnutrition screening, treatment of TB patient of DOT, prevention of NCDs, community-based provision of contraceptives, and promotion of healthy behaviors and practices including hygiene, sanitation, and family gardens(Lauren Crigler, 2014). From 2005, after the decentralization policy was introduced countrywide, there was sustained capacity building of the CHWs through training and supply of materials. By 2011, the number of CHWs had grown to 60,000. In May 2012, the Ministry of Health and Ministry of Local Government decided to remove the CHWs in –charge of Social Affairs in all the Villages. The number of community health workers was therefore reduced from 60,000 to approximately 45000. Each village is meant to have 3 CHWs. The range of services offered at community level by CHWs has evolved over time and so has its underlying policy, plans and implementation strategies (Luigi D’Aquino, 2016). Based on experience of the community initiatives for the past several years, the Government of Rwanda through the Ministry of Health consolidated the most promising strategies I the 2008 National Community Health Policy. In each village (Umudugudu), the binomes (pairs of CHW) are trained in ICCM and they are responsible for administering appropriate first aid as quickly as possible and the refer severe cases to health facilities. The training is accompanied by supportive supervision to strengthen their knowledge and skills to provide quality services to their communities. It is for this purpose that this training manual was developed. The ICCM is strategy that ensures comprehensive and continuous care to under 5 years’ sick child focusing on the most common disease: malaria, diarrhea, pneumonia and malnutrition. These interventions are curative, preventive and promote with participation of families and communities. This program comprises also growth monitoring and the promotion of child development. Community Health Workers (CHWs) play an important role that complements the health care provided by health center workers(Dr. BINAGWAHO Agnes, 2014). According to World Health Organization(WHO), Malnutrition refers to deficiencies, excesses or imbalances in a person’s intake of energy and nutrients. The term malnutrition covers 2 broad groups of conditions. One is ‘undernutrition’- which include stunting (low height for age), wasting (low weight for height), underweight (low weight for age), and micronutrient deficiencies or insufficiencies (a lack of important vitamins and minerals). The other is overweight, obesity and diet-related non communicable diseases (such as heart disease, stroke diabetes and cancer). The term malnutrition generally refers both to under nutrition and over nutrition, many factors can cause malnutrition, most of which relate to poor diet or severe and repeated infections, particularly in underprivileged populations. Inadequate diet and diseases, in turn, are closely linked to the general standard of living, the environmental conditions, and whether a population is able to meet its basic needs such as food, housing and health care. Malnutrition is thus a health outcome as well as the risk factor for diseases and exacerbated malnutrition, and it can increase the risk both morbidity and mortality(Monika Blössner & Mercedes de Onis, 2005). Malnutrition continues to be a major public health problem throughout the developing world, particularly in southern Asia and sub-Saharan Africa. The high prevalence of bacterial and parasitic diseases in developing countries contributes greatly to malnutrition there. Similarly, malnutrition increases one’s susceptibility to and severity of infections, and is thus a major component of illness and death from disease. Malnutrition is consequently the most important risk factor for the burden of disease in developing countries. It is the direct cause of about 300000 deaths per year and indirectly responsible for about half of all deaths in young children. The risk of death is directly correlated with the degree of malnutrition(Olaf Müller & Michael Krawinkel, 2005). Malnutrition, with its two constituents of protein-energy malnutrition and micronutrient deficiencies, continues to be a major health burden in developing countries. However, it is globally the most important risk factor for illness and death, with hundreds of millions of pregnant women and young children particularly affected(Olaf Müller & Michael Krawinkel, 2005).Over three million deaths occur from protein-energy malnutrition (PEM) in children under five worldwide annually. The burden of malnutrition in the developing world accounts for a large majority of these deaths, where one in four children under five are underweight. In Rwanda, an estimated 38% of children under five suffer from chronic malnutrition(MINISTRY OF HEALTH, 2018). The substantial burden of infectious disease contributes to the high rate of malnutrition among children, leading to negative effects on growth, as well as increased vulnerability to future occurrences of infection(Dr. Agnes Binagwaho et al., 2011). Improved nutrition can reduce child morbidity and mortality related to infectious disease, as adequately nourished children are more likely to fight and recover from an infection, and that is why Rwanda as the country which want to achieve MDGs has developed some of strategic policies to keep fighting against this problem of malnutrition in under five years children, the community health workers program has played an important role in expanding coverage of basic services, especially community based FP services and treatment of childhood malnutrition reduction. According to RDHS (Rwanda Demographic Health Survey) data, it shows that there has been a vast improvement in the nutritional status of children: between 2005 and 2010, the percentage of children who were underweight declined from 18% to 11% and the percentage of children who were stunted declined from 51% to 44%. And also between 2010 and 2015 the underweight has declined from 11% to 8.8%, while stunted declined from 44% to 38%. Though there is an improvement but the percentage is still high (NISR,2015). However, in Rwanda there are community health workers, Rwanda is still having problem of malnutrition diseases. One of the biggest problem is stunting where the statistics shows that there is a big rate number of 38% are stunted. This analysis uses the most recent DHS data from NISR (National Institute of statistics of Rwanda) to understand how the nutritional status of children varies with the educational achievement of mothers in the country. The main purpose of this paper is to evaluate how the community health workers is contributing in the prevention of diseases caused by malnutrition. Specifically, to identify diseases caused by malnutrition, to find out the challenges faced by community health workers, to examine the contribution of community health workers in the prevention of diseases caused by malnutrition in Rwanda, to suggest some possible solutions to overcome malnutrition. These will help the policy makers to get true and reliable information on malnutrition in Rwanda. 2. Literature Review The program of CHW Program was established in 1995, having an aim of increasing uptake of essential maternal and child clinical services through maternal education who is pregnant, promotion of health behaviors and follow up and linkages to health services. An estimated 45000 CHWs operating at the level of village: male-female CHWs pair providing basic and integrated community cases management of childhood illness a CHWs in charge of maternal health called an ASM(Rwanda Ministry of Health., 2018). Moreover, the core of level 1 health service provision rest on the key household practices. In this view CHWs who were described as gate keeper of health in community were found to be effective in dialoging with the households on actions for health since they shared a common situation and experience. In all the district visited, the CHWs had been selected by the community using the MOH guidelines with a strong emphasis on the willingness and ability to work as volunteers(Ministry of health, 2007). Basing on the community strategy (Ministry of health, 2007), Community health workers are expected to be, mature, respected and responsible members of the community the community choose men or women by the community to provide basic health care. Community health workers are coming from the village in which they live. They are between ages 20 and 50 they must know write and to read. They must volunteer willing and they are considered to be honest, trustworthy and reliable(Rwanda Ministry of Health., 2018). They to be selected by the members of village. On the last Saturday of the month (Umudugudu, or community service day) the villagers and volunteers are gathered together and voting “with their feet “in a literal sense. The process has been described as one that includes community members lining up the person they support. The individual with high number of community members is recruited. Binomes are trained in community based IMCI in each of the villages (umudugudu) by preparing them as first responders to a number of common childhood illness, including diarrhea, malaria and pneumonia. The CHWs are also trained on when and how to refer the installation to serious instance. IMC refresher training is given by a supporting supervisory model which the supervisor performs training to enhance the understanding and abilities of the CHWs in offering quality case management services in their communities(Rwanda Ministry of Health., 2011). Another example of program specific training is the ten day training for community based provision of FP service(Rwanda Ministry of Health., 2011a). A total of 3061 CHWs in three districts have received their training, which uses parcipatory methods, having CHWs brainstorm ideas and practice exercises such as role plays and perform a rapid diagnosis tests for malaria(Rwanda Ministry of Health., 2011a). 3. Findings From Other Researchers On Community Health Workers Freddy Perez et al. ( 2009 ) made a study on the role of health community health workers in improving child health program in Mali using a community based cross-sectional survey that was undertaken using multi-stage cluster sampling of wards and village. The data was collected using questionnaires among 401 child caregivers and registers of 72 CHWs. their findings showed that, among 401 households supposed to receive a visit by a CHWs, 219 had received at least one visit in the last three months before the survey, through the results mother is the most important caregiver (97%), high percentage being illiterate. Caregivers treat fever and diarrhea with the correct regimen in 40% and 11% of cases respectively. Comparative analysis between households with and without CHWs visits showed a positive influence of CHWs on family health practice like: knowledge on the management of child fever, non-utilization of antibiotics in home treatment of diarrhea, presence and bed net, all these have been statistically significant. A total of 27(38%) CHWs had not received supervision at all against 45(63%) who followed the regularly each month during the last six month, therefore they concluded saying that continuous training, transport means, adequate supervision and motivation of CHWs through the introduction of financial incentives and remuneration are among key factors to improve the CHWs work in rural communities(Freddy Perez, Hamady Ba, Sayed G Dastagire1, & Mathias Altmann, 2009). Brynne and Eilissh McAuliffe (2013) investigated on effect of community health workers delivering preventive interventions for maternal and child health in low and middle income countries. They worked on the evidence for policy and practical information and coordinating centre’s (EPPI-Centre) guidelines and systematic searching of the database occurred between June 8-11th, 2012: CINAHL, Embase, ovid Nursing Database, PubMed, Scopus, Web Science and POPLINE. Their study characteristics of included studies were extracted using a data sheet and peer tested quality assessment. A narrative synthesis of included studies was compiled with articles being coded descriptively to synthesize and draw conclusion. A total of 10281 studies were initially identified and through the screening process a total of 17 articles detailing 19 studies were included in review. With cross-sectional studies five preventive intervention categories like malaria prevention, health education, breastfeeding promotion, essential newborn care and psychological support. Therefore, all these categories showed the evidence for effectiveness of community health worker. They concluded that community health workers were shown to provide a range of preventive interventions for maternal and child health in low-and middle-income countries(Brynne Gilmore & Eilish McAuliffe, 2013). Zaeem and Assad Hhafeez (2009) made a study on knowledge and communication needs assessment of community health workers in developing country. They focused on group discussions which were held with health workers and their supervisors belonging to all the four province of the country and the Azad Jammu & Kashmir region. Self-response questionnaire was also used to obtain information on questions regarding their continued education. About four fifths of the respondents described their communication skills as moderately sufficient and wanted improvement. Knowledge on emerging health issues was insufficient and the respondents showed willingness to participate in their continued education. Media campaigns were successful in building the image of health workers are as credible source of health information. They concluded saying that a continued process should be insured to provide opportunities to health workers to update their knowledge sharpen communication skills and bring credibility to their personal as health educators(Zaeem Haq & Assad Hafeez, 2009). Andy Haines, et al., ( 2007 ) made a study on achieving child survival goals: potential contribution of community health workers, they find that there is renewed interest in the potential contribution of community health workers to child survival. Community health workers play a big role in undertaking different tasks like case management of childhood illnesses and delivery of preventive interventions including immunization, promotion of healthy through case management of childhood illness these interventions of community. Though, community health workers are not a panacea for weak health systems and will need task to be focused, training, supervision, and the active involvement of the communities in which the work. They also announced that the introduction of large scale programs for community health workers needs evaluation to look on the impact on child survival and effectiveness cost(Andy Haines, et al., 2007 ). 4. Conceptual Framework This part summarizes how dependent variable is influenced by explanatory variables. the researcher has based also on socio-demographic variables (access to information, wealth, health facility, place of residence, place, child, sex, household size ) Independent variable Dependent variables Community health worker ¬ Community health workers facility Socio-demographic factors ¬ Access to information ¬ Wealth workers ¬ Health facility ¬ Place of residence ¬ Province ¬ Child sex ¬ Household size Child nutrition status ¬ Stunting ¬ Wasting ¬ Underweight Source: researchers own ‘construct 5. Data And Methods Data and Methods This study extracted necessary information from Rwanda Demographic Health Survey (RDHS) 2014-15, which was conducted through a joint effort of the National Institute of Statistics of Rwanda (NISR). Under this chapter the researcher present and define the variables as well as the methods that will be used to analyze the data. For achieving the objective of the study, multivariate regression model will be used to analyze the relationship between community health workers and malnutrition reduction and how the community health workers contribute to reduce malnutrition in Rwanda. Define the methodology as the set of methods and principles that are used when studying a particular kind of work. A method composes all intellectual process an orderly system or arrangements that enable a researcher to reach an aspect of knowledge by using various techniques (Bailey, Kenneth D, 1978). 5.1 Data description The RDHS is a standardized and nationally representative survey that, inter alia, collects detailed level information on housing and household characteristics, maternal and child health, gender, domestic violence, family planning, nutrition, knowledge, and behaviors related to malaria and HIV/AIDS. For the 2014-15 RDHS, the fieldwork took place from July 7 to September 6 2014 and data editing were complete on April 26, 2015. Data cleaning and finalization were completed on May 15, 2015. 5.2 Target population, data filtering The RDHS is standardized and nationally representative survey that collects detailed level information on housing and household’s characteristics, maternal and child health, gender, domestic violence, family planning, nutrition, knowledge and behaviors related to malaria and HIV/AIDS. For the 2014-15 RDHS, the field work took place from July 7 to September 6 2014 and data editing were complete on April 26,2015. The sample size is 1137, though it was used the total household was 3615 before data cleaning. Then some cases were dropped during data cleaning we remain with 1137 cases. The study targeted on all families who have children malnutrition problem in their families. The research will focus on those children; the data set contains more variables and observations as it will be presented in conceptual framework. For the researcher was filtered the variables and observations that are relevant to the recent study design. 5.3 Methods of analysis and model specification 5.3.1 Methods of analysis The researcher used two types of methodology namely: Descriptive statistics (frequency statistics and bivariate analysis) and multivariate analysis, which will have used to identify the direction of effect for each independent variable. 5.3.2 Descriptive statistics The descriptive statistics for variables is important for summarizing the characteristics of respondents. Bivariate analysis using chi-square test will be used to identify the relationshipbetween the community health workers and diseases caused by malnutrition diseases. Chi-square formula is shown below: 5.3.3 Multivariate analysis Multivariable binary logistic regression analysis extends the technique of multiple regression analysis to research situation in which the outcome variable is categorical (Dayton 1992). Generally, logistics is well suited for describing and testing the hypothesis about relationship between a categorical outcome variable and more predictors. In order to obtain a more comprehensive picture of the contribution of the community health workers on malnutrition disease, we will consider several interlinked aspects running through from sickness and socio demographic factors treatment and prevention to finally health outcomes. When sick then all these be linked on malnutrition disease. The logistic regression analysis will be used to assess contribution of CHWs on Malnutrition disease and other factors that influence malnutrition disease and was reported as odds ratio (OR) with 95% confidence interval (CI). The univariate logistic regression was performed using one variable in the model at a time in order to find the association between age at death and each independent variable. Then, multivariate logistic regression will be performed using all the independent variables at a time. The fitness of the final logistic model was tested using Hosmer and Lemeshow goodness of fit test. Logistic regression analysis studies the association between a categorical dependent variable and a set of independent (explanatory) variables. The name logistic regression is used when the dependent variable has only two values, such as 0 and 1 or yes and No. The name multinomial logistic regression is usually reserved for the case when the dependent variable has three or more unique. The binary logistic regression model is shown like: 6. Results of the Analysis This section contains the presentation, analysis and the discussion of the findings of the study. These are presented according to the main research questions raised to guide the study conducted by NISR on RDHS 2014.2015. First part of this chapter included the background information of the respondents. Second part focused on the main findings of the study about the contribution of community health workers in the prevention of the diseases caused by malnutrition. 6.1 Respondents Characteristics This section dealt with the information collected on female population respondents in Rwanda. The characteristics of respondents discussed mainly include sex of respondents, female age group at first birth, place of residence, women marital status, place of residence and their highest education attainment. 6.2 Univariate analysis This part presents the description of child characteristics: health workers care, wealth index, mother education level, place of residence, province, antenatal care, age, sex, breast feeding, for the purpose of ascertaining the percentage and frequency distributions. Diseases caused by malnutrition and child characteristics Stunting | Freq. Percent ------------+------------------------ Non-stunted | 473 41.60 stunted | 664 58.40 ------------+------------------------ Total | 1,137 100.00 wasting ------------+------------------------ Non-wasted | 547 48.11 wasted | 590 51.89 ------------+------------------------ Total | 1,137 100.00 weight ----------------+-------------------- non_ underweight | 725 63.76 underweight | 412 36.24 ----------------+-------------------- Total | 1,137 100.00 Health workers ------------+------------------------- no | 338 29.73 yes | 799 70.27 ------------+------------------------- Total | 1,137 100.00 Education level -------------------------------------- Noeducation| 114 10.03 primary | 798 70.18 secondary | 170 14.95 higher | 55 4.84 -------------------------------------- Total | 1,137 100.00 wealth index ------------+------------------------- poor | 428 37.64 middle | 200 17.59 rich | 509 44.77 ------------+------------------------- Total | 1,137 100.00 Breastfeeding ------------+------------------------- no | 142 12.49 yes | 995 87.51 ------------+------------------------- Total | 1,137 100.00 Marital | status | ------------+------------------------- single | 38 3.34 married | 1,078 94.81 widowed | 1 0.09 divorced | 20 1.76 ------------+------------------------- Total | 1,137 100.00 sex of | child | ------------+------------------------- female | 591 51.98 male | 546 48.02 ------------+------------------------- Total | 1,137 100.00 Antenatal | care | ------------+------------------------- no | 1,026 90.24 yes | 111 9.76 ------------+------------------------- Total | 1,137 100.00 Source: DHS2014-15 According to all total respondent 58% had the problem stunting 51.89% were wasted and 36. 24% of the total population were under-weight. The majority met the health worker (70.27%) while other 29.63% did not. And most of them had primary level education with 70.18% followed by with those in secondary level with 14.95%, 44.77% are rich and 37.64% are poor. Here high number of children have had a breastfeeding while low number did not, 87.51% and 1.49% respectively. According to respondent’s marital status, most of them were married with 94.81% of the whole surveyed population and 51.98% were female and 49.02% were male. Above 90% did not get antenatal care 6.3 Bivariate This section presents the results of bivariate analysis on diseases caused by malnutrition. As earlier mentioned, it establishes the strength of association between diseases caused by malnutrition and each explanatory variables by using cross tabulations and chi-square statistics. Tables below show the details of death patterns by each of the selected independent variables. Factors that influence stunting | stunting status province total non-stunt (%) stunted (%) p value ---------------------------------------------------------------------- kigali city|168 104(61.90) 64(38.10) south |301 108(35.88) 193(64.12) west |239 84(35.15) 155(64.85) north |164 54(32.93) 110(67.07) east |265 123(46.42) 142(53.58) 0.000 ---------------------------------------------------------------------- Health | workers | ---------------------------------------------------------------------- no |338 79(23.37) 259(76.63) yes |799 394(49.31) 405(50.69) 0.000 ---------------------------------------------------------------------- type of | place of | residence | ---------------------------------------------------------------------- rural |836 295(35.29) 541(64.71) urban |301 178(59.14) 123(40.86) | 0.000 ---------------------------------------------------------------------- education | level | ---------------------------------------------------------------------- Noeducation|114 30(26.32) 84(73.68) primary |798 308(38.60) 490(61.40) | secondary |170 96(56.47) 74(43.53) | higher |55 39(70.91) 16(29.09) | 0.000 ------------+----------------------+------------------------------- wealth | index | ---------------------------------------------------------------------- poor |428 134(31.31) 294(68.69) | middle |200 62(31.00) 138(69.00) | rich | 509 277(54.42) 232(45.58) | 0.000 ---------------------------------------------------------------------- breastfeeding | ---------------------------------------------------------------------- no |142 104(73.24) 38(26.76) | yes |995 369(37.09) 626(62.91) | 0.000 ---------------------------------------------------------------------- Marital | status | ---------------------------------------------------------------------- single | 38 16(42.11) 22(57.89) | married |1,078 448(41.56) 630(58.44) | widowed |1 1(100.00) 0(0.00) | divorced | 20 8(40.00) 12(60.00) | 0.699 -------------------------------------------------------------------- sex of | child | ---------------------------------------------------------------------- female |591 262(44.33) 329(55.67) | male |546 211(38.64) 335(61.36) | 0.052 ------------------------------------------------------------------- Antenatal | care | ---------------------------------------------------------------------- no |1026 381(37.13) 645(62.87) | yes |111 92 (82.88) 19(17.12) | 0.000 ---------------------------------------------------------------------- Source: RDHS2014-15 The results of bivariate analysis are shown in the table above. And it shows that, province, health worker, place of residence, breastfeeding, wealth index and antenatal care are statistically significant because their p-value are less than 0.05 (p value <0.05). Means that the all mentioned variables have an influence on stunting status. Basing on findings indicated in table above, it shows that the problem of stunting among Rwandan children is still high. According the surveyed household distributed by province north, west and south provinces are at high level of stunting with 67.07%, 64.85% and 64.07% respectively and the province which has the small number of stunting is Kigali with 38.1% of the total population. Among the total surveyed children 76.63% of the total children who didn’t get help from health workers were stunted while 50.69% of the total children who met with health worker were also stunted. From our findings it is indicated that large number of children who were stunted, their mother had low educational level, for those with no education 73.68% were stunted while with those of primary level 61.4% also were stunted. As the level of education increase number of children with stunting decreases. And large number stunting was from rural distributed children with 64.71% while urban is 40.86%. And male children are more likely to meet stunting problem compared to female. Also 62.87% of the total children who didn’t get antenatal care were stunted while for those who did, only 17.12% were stunted. Factors that influence wasting wasting status province | Total non-waste (%) wasted (%) P value ------------+----------------------+--------------------------------- kigali city | 168 100(59.52) 68(40.48) south | 301 146(48.50) 155(51.50) west | 239 90(37.66) 149(62.34) north| 164 76(46.34) 88(53.66) east | 265 135(50.94) 130(49.06) 0.000 ------------+----------------------+------------------------------- Health | workers | -----------+--------------------------------------------------------- no | 338 143(42.31) 195(57.69) yes | 799 404(50.56) 395(49.44) 0.000 ------------+----------------------+---------------------------------- place of | residence | -----------+--------------------------------------------------------- rural | 836 360(43.06) 476(56.94) urban | 301 187(62.13) 114(37.87) 0.000 ------------+----------------------+--------------------------------- education | level | -----------+--------------------------------------------------------- no education | 114 40(35.09) 74(64.91) primary | 798 370(46.37) 428(53.63) secondary | 170 99(58.24) 71(41.76) higher | 55 38(69.09) 17(30.91) 0.000 -----------+----------------------+----------------------------------- wealth | index | -----------+--------------------------------------------------------- poor | 428 162(37.85) 266(62.15) middle | 200 88(44.00) 112(56.00) rich | 509 297(58.35) 212(41.65) 0.000 -----------+--------------------------------------------------------- breastfeeding -----------+--------------------------------------------------------- no | 142 85(59.86) 57(40.14) yes | 995 462(46.43) 533(53.57) 0.003 -----------+----------------------+----------------------------------- Marital | status | -----------+--------------------------------------------------------- single | 38 17(44.74) 21(55.26) married| 1,078 523(48.52) 555(51.48) widowed | 1 0 (0.00) 1(100.00) divorced | 20 7(35.00) 13(65.00) 0.467 -----------+----------------------+----------------------------------- sex of | child | -----------+--------------------------------------------------------- female | 591 307(51.95) 284(48.05) Male | 546 240(43.96) 306(56.04) 0.007 -----------+----------------------+----------------------------------- Antenatal care -----------+--------------------------------------------------------- no | 1,026 470(45.81) 556(54.19) yes | 111 77(69.37) 34(30.63) 0.000 source: RDHS 2014-15 The results of bivariate analysis are shown in the table above. And it shows that, province, health worker, place of residence, breastfeeding, wealth index and antenatal care are statistically significant because their p-value are less than 0.05 (p value <0.05) except maternal marital status. Means that the all mentioned variables have an influence on wasting status. Among the total children who didn’t get facility from the health workers 57.69% were wasted while 49.44% only were wasted for those who got facility from health workers which means that health workers have a role in reducing the number of wasted children. The result shows that western province is heading other province in having high number of children leaving with the problem of wasting, with 62.34% of the total surveyed children are wasted and is followed by north province which has 62.34% and the province which has low number of wasted children is Kigali city with 40.48%. For maternal educational level, the results indicated that children whose mothers has high level of education are more likely not to have this problem of wasting. For those with no education wasting was 64.91% while for those in higher education wasting was at 30.91 % as shown in the table. And higher number of wasting children was in rural areas, with 56.94% of the total surveyed children. Factors that influence underweight | Underweight status Province |Total non-under(%) underweight(%) P-value ------------+----------------------+---------------------------------- kigali city |168 105(62.50) 63(37.50) south |301 207(68.77) 94(31.23) west |239 135(56.49) 104(43.51) north |164 113(68.90) 51(31.10) east |265 165(62.26) 100(37.74) 0.027 --------------------------------------------------------------------- Health | worker s | ------------+----------------------+---------------------------------- no |338 219(64.79) 119(35.21) yes |799 506(63.33) 293(36.67) ------------+----------------------+---------------------------------- type of | place of | residence | ------------+----------------------+---------------------------------- rural |836 522(62.44) 314(37.56) urban |301 203(67.44) 98(32.56) 0.122 -------------------------------------------------------------------- education| level | ------------+----------------------+---------------------------------- no education|114 78(68.42) 36(31.58) primary|798 507(63.53) 291(36.47) secondary|170 102(60.00) 68(40.00) higher|55 38(69.09) 17(30.91) 0.422 ------------+----------------------+---------------------------------- wealth | inde x | ------------+----------------------+---------------------------------- poor |428 272(63.55) 156(36.45) middle |200 123(61.50) 77(38.50) rich |509 330(64.83) 179(35.17) 0.703 ---------------------------------------------------------------------- breastfeeding ------------+----------------------+---------------------------------- no |142 84(59.15) 58(40.85) yes |995 641(64.42) 354(35.58) 0.222 --------------------------------------------------------------------- Marital | status | ------------+----------------------+---------------------------------- single |38 23(60.53) 15(39.47) married |1078 688(63.82) 390(36.18) widowed |1 0(0.00) 1(100.00) divorced |20 14(70.00) 6(30.00) 0.518 ---------------------------------------------------------------------- sex of | child | --------------------------------------------------------------------- female |591 374(63.28) 217(36.72) male |546 351(64.29) 195(35.71) 0.725 ---------------------------------------------------------------------- Antenatal | care | --------------------------------------------------------------------- no |1026 656(63.94) 370(36.06) yes |111 69(62.16) 42(37.84) 0.712 ---------------------------------------------------------------------- SOURCE: RDHS 2014-15 The results of bivariate analysis are shown in the table above. And it shows that, all factors are statistically insignificant except province because their p-values are less than 0.05(p value <0.05). Means that the all mentioned variables have no influence on underweight status. Here the province which is at higher number of underweight, western province and followed by east, and Kigali city with 43.51%, 37.74% and 37.50%. and the majority were male (56.04%). 6.4 Multivariate analysis Binary logit parameter estimates of model 1 -------------------------------------------------------------------------------------- Stunting status| Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+------------------------------------------------------------------------ Health worker | -1.217217 .1636756 -7.44 0.000 -1.538016 -.8964191 province | -.0568698 .0511028 -1.11 0.266 -.1570294 .0432898 place residence| -.571168 .1838945 -3.11 0.002 -.9315946 -.2107414 education level| -.3417421 .1208649 -2.83 0.005 -.5786329 -.1048513 wealth index | -.277401 .0861079 -3.22 0.001 -.4461695 -.1086326 breast feeding | 1.178479 .219007 5.38 0.000 .7492327 1.607724 antenatal care | -1.59828 .2778857 -5.75 0.000 -2.142926 -1.053634 _cons | 1.626605 .3673184 4.43 0.000 .9066738 2.346536 -------------------------------------------------------------------------------------- LR chi2(9) = 250.08 Prob > chi2 =0.0000 Pseudo R2= 0.1620 Log likelihood = -646.94952 Source: DHS2015-15 The model is: log(p)=1.626605-1.217217 health worker-.0568698 province-.571168 place residence -.3417421 education level-.277401 wealth index +1.178479 breast feeding -1.59828 antenatal care. The likelihood of the model is the probability that you would observe the dichotomous (actually multichotomous) outcomes of the sample, given the coefficient estimates. The logit algorithms maximize the logarithm of this likelihood, and since the probabilities is between 0 and 1, then the log likelihood is always negative. Our maximum log likelihood of obtaining outcomes of health insurance coverage from the sample is -646.94952 and the test chi-square is 250.08. As the calculated chi-square statistics is highly significant at 5%, then the null hypothesis that the constrained model is correct is rejected. This means that the probability in the upper tail beyond the calculated statistic is smaller than the significance level chosen for test. Hence our explanatory variables are important covariates to the model. According to the finding shown in the table above all factors are statistically significant except province which is not because the p-value (0.266) is greater than 0.05. Holding other factors constant, factors constant health worker reduces the odds of stunting status by 1.21 percent which indicate that health workers have a large contribution in reducing this disease caused by malnutrition after antenatal care which has 1.6. Other factors like distribution by province also reduce the stunting status by 0.056 ceteric purbus, and place of residence has a contribution in reducing stunting status by 0.57. When holding other factor constant level of education reduce the odds of stunting status by 0.34 while breast feeding increase the odds by 1.17 here is also another factor called wealth index which reduces the odds of stunting status by 0.277 when other factors are hold constant. Binary logit parameter estimates of model 2 ------------------------------------------------------------------------------------ wasting | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------------- Health worker | -.3689097 .1396012 -2.64 0.008 -.642523 -.0952964 province | -.0440565 .046641 -0.94 0.345 -.1354712 .0473582 place residence | -.4262017 .1686871 -2.53 0.012 -.7568224 -.0955811 education level | -.1954709 .108764 -1.80 0.072 -.4086444 .0177026 wealth index | -.2587137 .0792108 -3.27 0.001 -.4139641 -.1034633 breast feeding | .2289394 .1946632 1.18 0.240 -.1525935 .6104723 child sex | .3073024 .1234634 2.49 0.013 .0653185 .5492863 antenatal care | -.6047335 .229367 -2.64 0.008 -1.054285 -.1551824 _cons | .9052192 .3919809 2.31 0.021 .1369506 1.673488 -------------+---------------------------------------------------------------- ------ LR chi2(8)= 82.22 Prob > chi2=0.0000 Pseudo R2=0.0522 Log likelihood = -746.18373 Source DHS2014-15 The model is: log(p)= .9052192-.3689097 Health worker -.0440565 province -.4262017 place residence -.1954709 education level -.2587137 wealth index +.2289394 breast feeding +.3073024 child sex -.6047335 antenatal care The likelihood of the model is the probability that you would observe the dichotomous (actually multichotomous) outcomes of the sample, given the coefficient estimates. The logit algorithms maximize the logarithm of this likelihood, and since the probabilities is between 0 and 1, then the log likelihood is always negative. Our maximum log likelihood of obtaining outcomes of health insurance coverage from the sample is -746.18373 and the test chi-square is 82.22. As the calculated chi-square statistics is highly significant at 5%, then the null hypothesis that the constrained model is correct is rejected. This means that the probability in the upper tail beyond the calculated statistic is smaller than the significance level chosen for test. Hence our explanatory variables are important covariates to the model. According to the finding shown in the table above all factors are statistically significant except province, level of education and breast feeding which are not because the p-value is greater than 0.05. Holding other factors constant, factors constant health worker reduces the odds of stunting status by 0.36 which indicate that health workers have a large contribution in reducing this disease caused by malnutrition after antenatal care which has 0.90 when other factors remains constant. Holding other factors constant, place of residence has a contribution in reducing the odds of wasting status by 0.42, here is also another factor called wealth index which reduces the odds of wasting status by 0.26 when other factors are hold constant. Ceteric paribus also sex of child has a contribution 0.30 in increasing odds of wasting status. Binary logit parameter estimates of model 3 ------------------------------------------------------------------------------------ Underweight Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+--------------------------------------------------------province| .0204013 .0444034 0.46 0.646 -.0666278 .1074305 _cons | -.6274855 .1492666 -4.20 0.000 -.9200427 -.3349283 ---------------------------------------------------------------------- Source DHS2014-15 Model is log(p)= -.6274855+.0204013 province And because the p value of province is greater than 0.05 hence it is not statistically significant. 7. Discussion Of results As expected the social economic factors like, health workers, maternal education, breast feeding, wealth, health care (antenatal care) index have influence on child stunting similar to the world health organization in 2018. Also in 2010 the world health organization find that poor schooling has an influence on child stunting and wasting which is the same as our findings. Wealth index and breast feeding have an expected sign and they are statistically significant. The findings show that breastfeeding reduce child stunting status. The result is similar to Rwanda ministry of health 2013 and 2018. Community health workers and breast feeding are statistically significant and according to the results both community health workers and breastfeeding have an influence on the child reduction of stunting and wasting which has been also investigated by USAID 2016 in Haiti. Community health workers contribute a larger role in improving children health, and according to the result of Freddy Perez et al. (2009) in Mali also find that these CHWs have large role which is looks the same as findings of Brynne and Eilissh McAuliffe (2013). Andy Haines, et al. (2007) find that there is renewed interest in the potential contribution of community health workers to child survival, which is similar to our result that CHWs contributes to child health. Conclusion and Recommendation From the result, we found that community health workers have positive influence on malnutrition disease since we reject null hypothesis and confirm that community health workers have influence in the reduction of malnutrition disease in Rwanda. But there are other factors that make the malnutrition still high, this is rural areas where their education still low because most people has almost complete primary only or have no education where we found that as the level of education increase the number of children with stunting decrease and also the results indicates that children whose mothers has high level of education are more not to have problem of malnutrition. Other factors that contribute to malnutrition disease in Rwanda are place of residence where we found that the big number of children who are not malnourished are from rural areas, wealth index where the poorest family still have the problem according the result indicate that wealth index have a big role in the reduction of malnutrition. Those that are contribute to malnutrition level in RWANDA. Basing on the findings, the community health workers has great impact to reduce malnutrition disease in Rwanda. That is why I recommend the local people who are the main concern and implementers of government policies, this will be helpful to fight against malnutrition in different areas and also the improvement of nutrition. I recommend again community health workers to participate in different trainings provided by the government or Ministry of Health, because they will find some advices related to health and it will help them again to manage some different case of this problem. The real assets government has, is its citizens. This is where the welfare of the population comes from and with the positive leadership. The government does not force people to join the strategies but if it is a beneficial one, everyone comes to enjoy it. Citizens especially women should work hard and awareness understanding of government strategies for a support to avoid malnutrition in their families. Abbreviations AIDS Acquired Immune Deficiency Syndrome ASM Agent de Santé Maternelle CBN Community Based Nutrition CCM Community Case Management CHC Center for Health Care CHEW Community Health Extension workers CHW Community Health Worker FP Family Planning MDGs Millennium Development Goals MOH Ministry of Health NCDs Non Communicable Diseases NGOs Non-Governmental Organizations NISR National Institute of Statistics of Rwanda PEM Protein Energy Malnutrition PHC Primary Health Care RBC Rwanda Biomédical Center RDH S Rwanda Demographic Health Survey RGB Rwanda Governance Board TB Tuberculosis UNICEF United Nation International Children Emergency Funds WHO World Health Organization References Haines A, Sanders D, Lehmann U, Rowe AK, Lawn JE, Jan S, Damian G, Walker. & Zulfi qar Bhutta. (2007). Achieving child survival goals: potential contribution of community health workers . Brynne G. & Eilish McAuliffe. (2013). Effectiveness of community health workers delivering preventive interventions for maternal and child health in low- and middle-income countries: a systematic review . Freddy Perez H, Ba, Sayed G, Dastagire1. & Mathias Altmann. (2009). The role of community health workers in improving child health programmes in Mali . Ministry of health. (2007). Community strategy implementation guidelines . Rwanda Ministry of Health. (2011a). Introducing Community-Based Provision of Family Planning Services in Rwanda: A Process Evaluation of the First Six Months of Implementation. Department of Maternal and Child Health, Community Health Desk . Rwanda Ministry of Health. (2011b). Trainer’s Guide: “Integrated Management of Child Illness,” “Community Case Management.\" . Rwanda Ministry of Health. (2018). National Community Health Strategic Plan July 2013– . Zaeem H. & Assad Hafeez. (2009). Knowledge and communication needs assessment of community health workers in a developing country: a qualitative study . Binagwaho DAgnès, Agbonyitor M, Rukundo A, Ratnayake N, Kayumba J, Ngabo F. … Mary C Smith Fawzi. (2011). Under diagnosis of malnutrition in infants and young children in Rwanda: implications for attainment of the Millennium Development Goal to end poverty and hunger. International Journal for Equity in Health . Dr BINAGWAHO, Agnes. (2014). INTEGRATED COMMUNITY CASE MANAGEMENT OF CHILDHOOD ILLNESS. Minister of Health . Lauren Crigler. (2014). RWANDA’S COMMUNITY HEALTH WORKER PROGRAMr. MINISTRY OF HEALTH. (2018). Rwanda: Nutrition Profile. MINISTRY OF HEALTH MOH. (2013). NATIONAL COMMUNITY HEALTH STRATEGIC PLAN July 2013 - June 2018. MINISTRY OF HEALTH . Mercedes de Onis Monika B. & Mercedes de Onis. (2005). Malnutrition: Quantifying the health impact at national and local levels. World Health Organization . Olaf, Müller. & Michael Krawinkel. (2005). Malnutrition and health in developing countries. Rwanda Governance Board. (2017). Rwanda Community Health Workers Program: 1995–2015 . Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-41252\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research\",\"associatedPublications\":[],\"authors\":[{\"id\":805967,\"identity\":\"0de709dd-d2b7-46d9-b107-f5813856a5f6\",\"order_by\":0,\"name\":\"Roger Muremyi\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYPACCQj1gYEhAUoTqYVxBkQLiCYSMPMQo0V3Ru7DRzfbLPL5+Rcf+2zbZpfHz97A2FyBR4vZjXRj49w2CcuZM54lz85tSy6W7DnA2HgGr5Y0NmmgFgODG2eMmXPbmBM33Ehgf9iAXwv7b4iW85+ZLdvqQVoYGwloYWMGaznfw8zM2HaYCC1nnjFL55yTMJCcwWbM2HPueOLMnoON+LUcT2P8nFNWZ8DPf/gxw4+y6sR+9uaDeLWAASMbkJBIgDIYGAlqAII/QMx/AMoYBaNgFIyCUYAGAPm1UJJHxr+5AAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":true,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Roger\",\"middleName\":\"\",\"lastName\":\"Muremyi\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2020-07-12 14:32:22\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-41252/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-41252/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":13551264,\"identity\":\"bc04e606-9df4-4a87-bc8b-d34764cf02ad\",\"added_by\":\"auto\",\"created_at\":\"2021-09-17 02:28:05\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":944771,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-41252/v1/e32f86f0-3ebb-418a-b783-475e9c531a2a.pdf\"}],\"financialInterests\":\"\",\"formattedTitle\":\"Contribution of community health workers in the prevention of disease caused by malnutrition in Rwanda\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eOver the last three centuries following the 1978 Alma Ata Declaration on Primary Health Care (PHC), community health workers (CHWs) have been encouraged to become component of the health structures of many emerging nations. CHW programs were implemented in many of these nations in a top-down manner with comparatively restricted capability construction and scheduling. instead of being the leading edge of changed strategy to health care, CHWs often wound up becoming a badly resourced and undervalued expansion of the current health service- \\u0026ldquo;just another couple of finger\\u0026rdquo;(MINISTRY OF HEALTH, 2013).\\u003c/p\\u003e\\n\\u003cp\\u003eWorldwide, CHWs are used as a strategy to addressthe shortage of health workers, and render certainbasic health services to their communities (e.g. USA,China, Brazil, and South Africa)(Rwanda Governance Board, 2017). Depending on the specific needsof countries and communities, CHWs\\u0026rsquo; profiles vary interms of activities, scope; training among others. According to WHO (World Health Organization) definition of CHWs is that they should be: \\u0026ldquo;members of the communities where they work; selected by the communities; answerable to the communities for their activities; supported by the health system but not necessarily a part of its organization; and, have shorter training than professional workers(Rwanda Governance Board, 2017).\\u003c/p\\u003e\\n\\u003cp\\u003eThe Rwanda CHW Program was established in 1995 after Genocide, aiming at increasing uptake of essential maternal and child clinical services through education of pregnant women, promotion of healthy behaviors, and follow-up and linkages to health services. An estimated 45,000 CHWs operating at the village level provide the first line of health service delivery. There are three CHWs in each village: a male-female CHW pair providing basic care and integrated community case management (CCM) of childhood illness, and a CHW in charge of maternal health, called an ASM (Agent de Sant\\u0026eacute; Maternelle). There are four main objectives of the program (1) strengthen the capacity of decentralized structures to allow community health service delivery; (2) strengthen the participation of community members in community health activities; (3) strengthen CHW motivation through CPBF to improve health service delivery; and (4) strengthen coordination of community health services at the central district, health center, and community levels. The program has since grown to include an integrated service package that include malnutrition screening, treatment of TB patient of DOT, prevention of NCDs, community-based provision of contraceptives, and promotion of healthy behaviors and practices including hygiene, sanitation, and family gardens(Lauren Crigler, 2014).\\u003c/p\\u003e\\n\\u003cp\\u003eFrom 2005, after the decentralization policy was introduced countrywide, there was sustained capacity building of the CHWs through training and supply of materials. By 2011, the number of CHWs had grown to 60,000. In May 2012, the Ministry of Health and Ministry of Local Government decided to remove the CHWs in \\u0026ndash;charge of Social Affairs in all the Villages. The number of community health workers was therefore reduced from 60,000 to approximately 45000. Each village is meant to have 3 CHWs. The range of services offered at community level by CHWs has evolved over time and so has its underlying policy, plans and implementation strategies\\u0026nbsp;(Luigi D\\u0026rsquo;Aquino, 2016).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eBased on experience of the community initiatives for the past several years, the Government of Rwanda through the Ministry of Health consolidated the most promising strategies I the 2008 National Community Health Policy. In each village (Umudugudu), the binomes (pairs of CHW) are trained in ICCM and they are responsible for administering appropriate first aid as quickly as possible and the refer severe cases to health facilities. The training is accompanied by supportive supervision to strengthen their knowledge and skills to provide quality services to their communities. It is for this purpose that this training manual was developed. The ICCM is strategy that ensures comprehensive and continuous care to under 5 years\\u0026rsquo; sick child focusing on the most common disease: malaria, diarrhea, pneumonia and malnutrition. These interventions are curative, preventive and promote with participation of families and communities. This program comprises also growth monitoring and the promotion of child development. Community Health Workers (CHWs) play an important role that complements the health care provided by health center workers(Dr. BINAGWAHO Agnes, 2014).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAccording to World Health Organization(WHO), Malnutrition refers to deficiencies, excesses or imbalances in a person\\u0026rsquo;s intake of energy and nutrients. The term malnutrition covers 2 broad groups of conditions. One is \\u0026lsquo;undernutrition\\u0026rsquo;-\\u0026nbsp;\\u0026nbsp; which include stunting (low height for age), wasting (low weight for height), underweight (low weight for age), and micronutrient deficiencies or insufficiencies (a lack of important vitamins and minerals). The other is overweight, obesity and diet-related non communicable diseases (such as heart disease, stroke diabetes and cancer).\\u003c/p\\u003e\\n\\u003cp\\u003eThe term malnutrition generally refers both to under nutrition and over nutrition, many factors can cause malnutrition, most of which relate to poor diet or severe and repeated infections, particularly in underprivileged populations. Inadequate diet and diseases, in turn, are closely linked to the general standard of living, the environmental conditions, and whether a population is able to meet its basic needs such as food, housing and health care. Malnutrition is thus a health outcome as well as the risk factor for diseases and exacerbated malnutrition, and it can increase the risk both morbidity and mortality(Monika Bl\\u0026ouml;ssner \\u0026amp; Mercedes de Onis, 2005).\\u003c/p\\u003e\\n\\u003cp\\u003eMalnutrition continues to be a major public health problem throughout the developing world, particularly in southern Asia and sub-Saharan Africa. The high prevalence of bacterial and parasitic diseases in developing countries contributes greatly to malnutrition there. Similarly, malnutrition increases one\\u0026rsquo;s susceptibility to and severity of infections, and is thus a major component of illness and death from disease. Malnutrition is consequently the most important risk factor for the burden of disease in developing countries. It is the direct cause of about 300000 deaths per year and indirectly responsible for about half of all deaths in young children. The risk of death is directly correlated with the degree of malnutrition(Olaf M\\u0026uuml;ller \\u0026amp; Michael Krawinkel, 2005).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eMalnutrition, with its two constituents of protein-energy malnutrition and micronutrient deficiencies, continues to be a major health burden in developing countries. However, it is globally the most important risk factor for illness and death, with hundreds of millions of pregnant women and young children particularly affected(Olaf M\\u0026uuml;ller \\u0026amp; Michael Krawinkel, 2005).Over three million deaths occur from protein-energy malnutrition (PEM) in children under five worldwide annually. The burden of malnutrition in the developing world accounts for a large majority of these deaths, where one in four children under five are underweight. In Rwanda, an estimated 38% of children under five suffer from chronic malnutrition(MINISTRY OF HEALTH, 2018). The substantial burden of infectious disease contributes to the high rate of malnutrition among children, leading to negative effects on growth, as well as increased vulnerability to future occurrences of infection(Dr. Agnes Binagwaho et al., 2011). Improved nutrition can reduce child morbidity and mortality related to infectious disease, as adequately nourished children are more likely to fight and recover from an infection, and that is why Rwanda as the country which want to achieve MDGs has developed some of strategic policies to keep fighting against this problem of malnutrition in under five years children, the community health workers program\\u0026nbsp; has played an important role in expanding coverage of basic services, especially community based FP services and treatment of childhood malnutrition reduction.\\u003c/p\\u003e\\n\\u003cp\\u003eAccording to RDHS (Rwanda Demographic Health Survey) data, it shows that there has been a vast improvement in the nutritional status of children: between 2005 and 2010, the percentage of children who were underweight declined from 18% to 11% and the percentage of children who were stunted declined from 51% to 44%. And also between 2010 and 2015 the underweight has declined from 11% to 8.8%, while stunted declined from 44% to 38%. Though there is an improvement but the percentage is still high (NISR,2015).\\u003c/p\\u003e\\n\\u003cp\\u003eHowever, in Rwanda there are community health workers, Rwanda is still having problem of malnutrition diseases. One of the biggest problem is stunting where the statistics shows that there is a big rate number of 38% are stunted.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis analysis uses the most recent DHS data from NISR (National Institute of statistics of Rwanda) to understand how the nutritional status of children varies with the educational achievement of mothers in the country. The main purpose of this paper is to evaluate how the community health workers is contributing in the prevention of diseases caused by malnutrition. Specifically, to identify diseases caused by malnutrition, to find out the challenges faced by community health workers, to examine the contribution of community health workers in the prevention of diseases caused by malnutrition in Rwanda, to suggest some possible solutions to overcome malnutrition. These will help the policy makers to get true and reliable information on malnutrition in Rwanda.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\"},{\"header\":\" 2. Literature Review \",\"content\":\"\\u003cp\\u003eThe program of CHW Program was established in 1995, having an aim of increasing uptake of essential maternal and child clinical services through maternal education who is pregnant, promotion of health behaviors and follow up and linkages to health services. An estimated 45000 CHWs operating at the level of village: male-female CHWs pair providing basic and integrated community cases management of childhood illness a CHWs in charge of maternal health called an ASM(Rwanda Ministry of Health., 2018). Moreover, the core of level 1 health service provision rest on the key household practices. In this view CHWs who were described as gate keeper of health in community were found to be effective in dialoging with the households on actions for health since they shared a common situation and experience. In all the district visited, the CHWs had been selected by the community using the MOH guidelines with a strong emphasis on the willingness and ability to work as volunteers(Ministry of health, 2007).\\u003c/p\\u003e\\n\\u003cp\\u003eBasing on the community strategy (Ministry of health, 2007), Community health workers are expected to be, mature, respected and responsible members of the community the community choose men or women by the community to provide basic health care.\\u003c/p\\u003e\\n\\u003cp\\u003eCommunity health workers are coming from the village in which they live. They are between ages 20 and 50 they must know write and to read. They must volunteer willing and they are considered to be honest, trustworthy and reliable(Rwanda Ministry of Health., 2018). They to be selected by the members of village. On the last Saturday of the month (Umudugudu, or community service day) the villagers and volunteers are gathered together and voting \\u0026ldquo;with their feet \\u0026ldquo;in a literal sense. The process has been described as one that includes community members lining up the person they support. The individual with high number of community members is recruited.\\u003c/p\\u003e\\n\\u003cp\\u003eBinomes are trained in community based IMCI in each of the villages (umudugudu) by preparing them as first responders to a number of common childhood illness, including diarrhea, malaria and pneumonia. The CHWs are also trained on when and how to refer the installation to serious instance. IMC refresher training is given by a supporting supervisory model which the supervisor performs training to enhance the understanding and abilities of the CHWs in offering quality case management services in their communities(Rwanda Ministry of Health., 2011).\\u003c/p\\u003e\\n\\u003cp\\u003eAnother example of program specific training is the ten day training for community based provision of FP service(Rwanda Ministry of Health., 2011a). A total of 3061 CHWs in three districts have received their training, which uses parcipatory methods, having CHWs brainstorm ideas and practice exercises such as role plays and perform a rapid diagnosis tests for malaria(Rwanda Ministry of Health., 2011a).\\u003c/p\\u003e\"},{\"header\":\"3. Findings From Other Researchers On Community Health Workers\",\"content\":\" \\u003cp\\u003eFreddy Perez et al. (\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e) made a study on the role of health community health workers in improving child health program in Mali using a community based cross-sectional survey that was undertaken using multi-stage cluster sampling of wards and village. The data was collected using questionnaires among 401 child caregivers and registers of 72 CHWs. their findings showed that, among 401 households supposed to receive a visit by a CHWs, 219 had received at least one visit in the last three months before the survey, through the results mother is the most important caregiver (97%), high percentage being illiterate. Caregivers treat fever and diarrhea with the correct regimen in 40% and 11% of cases respectively. Comparative analysis between households with and without CHWs visits showed a positive influence of CHWs on family health practice like: knowledge on the management of child fever, non-utilization of antibiotics in home treatment of diarrhea, presence and bed net, all these have been statistically significant. A total of 27(38%) CHWs had not received supervision at all against 45(63%) who followed the regularly each month during the last six month, therefore they concluded saying that continuous training, transport means, adequate supervision and motivation of CHWs through the introduction of financial incentives and remuneration are among key factors to improve the CHWs work in rural communities(Freddy Perez, Hamady Ba, Sayed G Dastagire1, \\u0026amp; Mathias Altmann, 2009).\\u003c/p\\u003e \\u003cp\\u003eBrynne and Eilissh McAuliffe (2013) investigated on effect of community health workers delivering preventive interventions for maternal and child health in low and middle income countries. They worked on the evidence for policy and practical information and coordinating centre\\u0026rsquo;s (EPPI-Centre) guidelines and systematic searching of the database occurred between June 8-11th, 2012: CINAHL, Embase, ovid Nursing Database, PubMed, Scopus, Web Science and POPLINE. Their study characteristics of included studies were extracted using a data sheet and peer tested quality assessment. A narrative synthesis of included studies was compiled with articles being coded descriptively to synthesize and draw conclusion. A total of 10281 studies were initially identified and through the screening process a total of 17 articles detailing 19 studies were included in review. With cross-sectional studies five preventive intervention categories like malaria prevention, health education, breastfeeding promotion, essential newborn care and psychological support. Therefore, all these categories showed the evidence for effectiveness of community health worker. They concluded that community health workers were shown to provide a range of preventive interventions for maternal and child health in low-and middle-income countries(Brynne Gilmore \\u0026amp; Eilish McAuliffe, 2013).\\u003c/p\\u003e \\u003cp\\u003eZaeem and Assad Hhafeez (2009) made a study on knowledge and communication needs assessment of community health workers in developing country. They focused on group discussions which were held with health workers and their supervisors belonging to all the four province of the country and the Azad Jammu \\u0026amp; Kashmir region. Self-response questionnaire was also used to obtain information on questions regarding their continued education. About four fifths of the respondents described their communication skills as moderately sufficient and wanted improvement. Knowledge on emerging health issues was insufficient and the respondents showed willingness to participate in their continued education. Media campaigns were successful in building the image of health workers are as credible source of health information. They concluded saying that a continued process should be insured to provide opportunities to health workers to update their knowledge sharpen communication skills and bring credibility to their personal as health educators(Zaeem Haq \\u0026amp; Assad Hafeez, 2009).\\u003c/p\\u003e \\u003cp\\u003eAndy Haines, et al., (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e) made a study on achieving child survival goals: potential contribution of community health workers, they find that there is renewed interest in the potential contribution of community health workers to child survival. Community health workers play a big role in undertaking different tasks like case management of childhood illnesses and delivery of preventive interventions including immunization, promotion of healthy through case management of childhood illness these interventions of community. Though, community health workers are not a panacea for weak health systems and will need task to be focused, training, supervision, and the active involvement of the communities in which the work. They also announced that the introduction of large scale programs for community health workers needs evaluation to look on the impact on child survival and effectiveness cost(Andy Haines, et al., \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e).\\u003c/p\\u003e \"},{\"header\":\"4. Conceptual Framework\",\"content\":\" \\u003cp\\u003eThis part summarizes how dependent variable is influenced by explanatory variables. the researcher has based also on socio-demographic variables (access to information, wealth, health facility, place of residence, place, child, sex, household size\\u003cb\\u003e)\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"No\\\" id=\\\"Taba\\\" border=\\\"1\\\"\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIndependent variable\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eDependent variables\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eCommunity health worker\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Community health workers facility\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSocio-demographic factors\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Access to information\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Wealth workers\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Health facility\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Place of residence\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Province\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Child sex\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Household size\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eChild nutrition status\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Stunting\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Wasting\\u003c/p\\u003e \\u003cp\\u003e\\u0026not; Underweight\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"3\\\"\\u003e\\u003cb\\u003eSource: researchers own \\u0026lsquo;construct\\u003c/b\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \"},{\"header\":\"5. Data And Methods\",\"content\":\"\\u003col start=\\\"5\\\"\\u003e\\n\\u003cli\\u003e\\u003cstrong\\u003e Data and Methods \\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003eThis study extracted necessary information from Rwanda Demographic Health Survey (RDHS)\\u003c/p\\u003e\\n\\u003cp\\u003e2014-15, which was conducted through a joint effort of the National Institute of Statistics of Rwanda (NISR). Under this chapter the researcher present and define the variables as well as the methods that will be used to analyze the data. For achieving the objective of the study, multivariate regression model will be used to analyze the relationship between community health workers and malnutrition reduction and how the community health workers contribute to reduce malnutrition in Rwanda. Define the methodology as the set of methods and principles that are used when studying a particular kind of work. A method composes all intellectual process an orderly system or arrangements that enable a researcher to reach an aspect of knowledge by using various techniques (Bailey, Kenneth D, 1978).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e5.1 Data description \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe RDHS is a standardized and nationally representative survey that, inter alia, collects detailed level information on housing and household characteristics, maternal and child health, gender, domestic violence, family planning, nutrition, knowledge, and behaviors related to malaria and HIV/AIDS. For the 2014-15 RDHS, the fieldwork took place from July 7 to September 6 2014 and data editing were complete on April 26, 2015. Data cleaning and finalization were completed on May 15, 2015.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e5.2 \\u0026nbsp;Target population, data filtering\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe RDHS is standardized and nationally representative survey that collects detailed level information on housing and household\\u0026rsquo;s characteristics, maternal and child health, gender, domestic violence, family planning, nutrition, knowledge and behaviors related to malaria and HIV/AIDS. For the 2014-15 RDHS, the field work took place from July 7 to September 6 2014 and data editing were complete on April 26,2015. The sample size is 1137, though it was used the total household was 3615 before data cleaning. Then some cases were dropped during data cleaning we remain with 1137 cases.\\u003c/p\\u003e\\n\\u003cp\\u003eThe study targeted on all families who have children malnutrition problem in their families. The research will focus on those children; the data set contains more variables and observations as it will be presented in conceptual framework. For the researcher was filtered the variables and observations that are relevant to the recent study design.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e5.3 Methods of analysis and model specification \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e5.3.1 Methods of analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe researcher used two types of methodology namely: Descriptive statistics (frequency statistics and bivariate analysis) and multivariate analysis, which will have used to identify the direction of effect for each independent variable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e5.3.2 Descriptive statistics\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe descriptive statistics for variables is important for summarizing the characteristics of respondents. Bivariate analysis using chi-square test will be used to identify the relationshipbetween the community health workers and diseases caused by malnutrition diseases. Chi-square formula is shown below:\\u003c/p\\u003e\\u003cp\\u003e\\u003cimg src=\\\"data:image/jpeg;base64,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\\u0026nbsp;Multivariate analysis \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eMultivariable binary logistic regression analysis extends the technique of multiple regression analysis to research situation in which the outcome variable is categorical (Dayton 1992). Generally, logistics is well suited for describing and testing the hypothesis about relationship between a categorical outcome variable and more predictors. In order to obtain a more comprehensive picture of the contribution of the community health workers on malnutrition disease, we will consider several interlinked aspects running through from sickness and socio demographic factors treatment and prevention to finally health outcomes. When sick then all these be linked on malnutrition disease.\\u003c/p\\u003e\\n\\u003cp\\u003eThe logistic regression analysis will be used to assess contribution of CHWs on Malnutrition disease and other factors that influence malnutrition disease and was reported as odds ratio (OR) with 95% confidence interval (CI). The univariate logistic regression was performed using one variable in the model at a time in order to find the association between age at death and each independent variable. Then, multivariate logistic regression will be performed using all the independent variables at a time. The fitness of the final logistic model was tested using Hosmer and Lemeshow goodness of fit test.\\u003c/p\\u003e\\n\\u003cp\\u003eLogistic regression analysis studies the association between a categorical dependent variable and a set of independent (explanatory) variables. The name logistic regression is used when the dependent variable has only two values, such as 0 and 1 or yes and No. The name multinomial logistic regression is usually reserved for the case when the dependent variable has three or more unique.\\u003c/p\\u003e\\n\\u003cp\\u003eThe binary logistic regression model is shown like:\\u003c/p\\u003e \\n\\u003cp\\u003e\\u003cimg 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Results of the Analysis\",\"content\":\"\\u003cp\\u003eThis section contains the presentation, analysis and the discussion of the findings of the study. These are presented according to the main research questions raised to guide the study conducted by NISR on RDHS 2014.2015. First part of this chapter included the background information of the respondents. Second part focused on the main findings of the study about the contribution of community health workers in the prevention of the diseases caused by malnutrition.\\u003c/p\\u003e\\n\\u003cp\\u003e6.1 \\u003cstrong\\u003eRespondents Characteristics\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis section dealt with the information collected on female population respondents in Rwanda. The characteristics of respondents discussed mainly include sex of respondents, female age group at first birth, place of residence, women marital status, place of residence and their highest education attainment.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e6.2 Univariate analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis part presents the description of child characteristics: health workers care, wealth index, mother education level, place of residence, province, antenatal care, age, sex, breast feeding, for the purpose of ascertaining the percentage and frequency distributions.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDiseases caused by malnutrition and child characteristics \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003ctable width=\\\"380\\\"\\u003e\\n\\u003ctbody\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eStunting\\u003c/strong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Freq.\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Percent\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003eNon-stunted |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 473\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 41.60\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; stunted |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 664\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 58.40\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Total |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1,137\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"4\\\" width=\\\"335\\\"\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ewasting\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;Non-wasted |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 547\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 48.11\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; wasted |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 590\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 51.89\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Total |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1,137\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"4\\\" width=\\\"335\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eweight\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e----------------+--------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd width=\\\"268\\\"\\u003e\\n\\u003cp\\u003enon_\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003eunderweight |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 725\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 63.76\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003eunderweight |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 412\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 36.24\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e----------------+--------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Total |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1,137\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"3\\\" width=\\\"313\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"4\\\" width=\\\"335\\\"\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eHealth workers\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 338\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 29.73\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 799\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 70.27\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Total |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1,137\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"3\\\" width=\\\"313\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"4\\\" width=\\\"335\\\"\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEducation level\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e--------------------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003eNoeducation|\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 114\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 10.03\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; primary |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 798\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 70.18\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp; secondary |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 170\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 14.95\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; higher |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 55\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 4.84\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e--------------------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Total |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1,137\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"3\\\" width=\\\"313\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"4\\\" width=\\\"335\\\"\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ewealth index\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; poor |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 428\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 37.64\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; middle |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 200\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 17.59\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; rich |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 509\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 44.77\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Total |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1,137\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"4\\\" width=\\\"335\\\"\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eBreastfeeding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 142\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 12.49\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 995\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 87.51\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Total |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1,137\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd width=\\\"268\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"3\\\" width=\\\"313\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Marital |\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"4\\\" width=\\\"335\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; status |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; single |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 38\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 3.34\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; married |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1,078\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 94.81\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; widowed |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.09\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp; divorced |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 20\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1.76\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Total |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1,137\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"3\\\" width=\\\"313\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; sex of |\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"4\\\" width=\\\"335\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; child |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; female |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 591\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 51.98\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; male |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 546\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 48.02\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Total |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003cstrong\\u003e1,137\\u003c/strong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd width=\\\"268\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"3\\\" width=\\\"313\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp; Antenatal |\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"4\\\" width=\\\"335\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; care |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd width=\\\"22\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1,026\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 90.24\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 111\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 9.76\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e------------+-------------------------\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"6\\\" width=\\\"380\\\"\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Total |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003cstrong\\u003e1,137\\u003c/strong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSource: DHS2014-15\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAccording to all total respondent 58% had the problem stunting 51.89% were wasted and 36. 24% of the total population were under-weight. The majority met the health worker (70.27%) while other 29.63% did not. And most of them had primary level education with 70.18% followed by with those in secondary level with 14.95%, 44.77% are rich and 37.64% are poor. Here high number of children have had a breastfeeding while low number did not, 87.51% and 1.49% respectively. According to respondent\\u0026rsquo;s marital status, most of them were married with 94.81% of the whole surveyed population and 51.98% were female and 49.02% were male. Above 90% did not get antenatal care\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e6.3 \\u0026nbsp;Bivariate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis section presents the results of bivariate analysis on diseases caused by malnutrition. As earlier mentioned, it establishes the strength of association between diseases caused by malnutrition and each explanatory variables by using cross tabulations and chi-square statistics. Tables below show the details of death patterns by each of the selected independent variables.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eFactors that influence stunting\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003cstrong\\u003estunting status\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eprovince total non-stunt (%) stunted (%)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; p value\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003ekigali city|168\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 104(61.90)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 64(38.10)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; south |301\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 108(35.88)\\u0026nbsp;\\u0026nbsp; 193(64.12)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; west |239\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 84(35.15)\\u0026nbsp;\\u0026nbsp; 155(64.85)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; north |164\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 54(32.93)\\u0026nbsp;\\u0026nbsp; 110(67.07)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; east |265\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 123(46.42)\\u0026nbsp;\\u0026nbsp; 142(53.58)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;Health |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp; workers\\u003c/strong\\u003e |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no |338\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 79(23.37)\\u0026nbsp;\\u0026nbsp; 259(76.63)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes |799\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 394(49.31)\\u0026nbsp;\\u0026nbsp; 405(50.69)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003etype of |\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp; place of |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;residence\\u003c/strong\\u003e |\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; rural |836\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 295(35.29)\\u0026nbsp;\\u0026nbsp; 541(64.71)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; urban |301\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 178(59.14)\\u0026nbsp;\\u0026nbsp; 123(40.86) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;education |\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; level\\u003c/strong\\u003e |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003eNoeducation|114\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 30(26.32)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 84(73.68)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp; primary |798\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 308(38.60)\\u0026nbsp;\\u0026nbsp; 490(61.40) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;secondary |170\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 96(56.47)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 74(43.53) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; higher |55\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 39(70.91)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 16(29.09) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+-------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; wealth |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; index\\u003c/strong\\u003e |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; poor |428\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 134(31.31)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 294(68.69) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; middle |200\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 62(31.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 138(69.00) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; rich | 509\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 277(54.42)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 232(45.58) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ebreastfeeding |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no |142\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 104(73.24)\\u0026nbsp;\\u0026nbsp; 38(26.76) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes |995\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 369(37.09)\\u0026nbsp; 626(62.91) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u0026nbsp;0.000\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMarital |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; status\\u003c/strong\\u003e |\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; single | 38\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 16(42.11)\\u0026nbsp;\\u0026nbsp; 22(57.89) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp; married |1,078\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 448(41.56)\\u0026nbsp; 630(58.44) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp; widowed |1\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1(100.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0(0.00) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; divorced | 20\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 8(40.00)\\u0026nbsp;\\u0026nbsp; 12(60.00) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.699\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; --------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003esex of |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; child\\u003c/strong\\u003e |\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; female |591\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 262(44.33)\\u0026nbsp; 329(55.67) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; male |546\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 211(38.64)\\u0026nbsp; 335(61.36) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.052\\u003c/p\\u003e\\n\\u003cp\\u003e-------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;Antenatal |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; care\\u003c/strong\\u003e |\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no |1026\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 381(37.13) 645(62.87) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u0026nbsp;yes |111\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 92 (82.88)\\u0026nbsp; 19(17.12) |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSource: RDHS2014-15\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe results of bivariate analysis are shown in the table above. And it shows that, province, health worker, place of residence, breastfeeding, wealth index and antenatal care are statistically significant because their p-value are less than \\u003cstrong\\u003e0.05 \\u003c/strong\\u003e(p value \\u0026lt;0.05). Means that the all mentioned variables have an influence on stunting status.\\u003c/p\\u003e\\n\\u003cp\\u003eBasing on findings indicated in table above, it shows that the problem of stunting among Rwandan children is still high. According the surveyed household distributed by province north, west and south provinces are at high level of stunting with 67.07%, 64.85% and 64.07% respectively and the province which has the small number of stunting is Kigali with 38.1% of the total population. Among the total surveyed children 76.63% of the total children who didn\\u0026rsquo;t get help from health workers were stunted while 50.69% of the total children who met with health worker were also stunted.\\u003c/p\\u003e\\n\\u003cp\\u003eFrom our findings it is indicated that large number of children who were stunted, their mother had low educational level, for those with no education 73.68% were stunted while with those of primary level 61.4% also were stunted. As the level of education increase number of children with stunting decreases. And large number stunting was from rural distributed children with 64.71% while urban is 40.86%. And male children are more likely to meet stunting problem compared to female. Also 62.87% of the total children who didn\\u0026rsquo;t get antenatal care were stunted while for those who did, only 17.12% were stunted.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFactors that influence wasting\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; wasting status\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; province | Total\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; non-waste (%)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; wasted (%)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; P value\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+---------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;kigali city | 168\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100(59.52)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 68(40.48)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; south | 301\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 146(48.50)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 155(51.50)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;west | 239\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 90(37.66)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 149(62.34)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; north| 164\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 76(46.34)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 88(53.66)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; east | 265\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 135(50.94)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 130(49.06)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp; ------------+----------------------+-------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Health |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; workers\\u003c/strong\\u003e |\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+---------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no | 338\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 143(42.31)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 195(57.69)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes | 799\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 404(50.56)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 395(49.44)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+----------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; place of |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp; residence\\u003c/strong\\u003e |\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+---------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; rural | 836\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 360(43.06)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 476(56.94)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; urban | 301\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 187(62.13)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 114(37.87)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+---------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eeducation |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; level\\u003c/strong\\u003e |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+---------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003eno education | 114\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 40(35.09)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 74(64.91)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; primary | 798\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 370(46.37)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 428(53.63)\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp; secondary | 170\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 99(58.24)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 71(41.76)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; higher | 55\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 38(69.09)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 17(30.91)\\u0026nbsp;\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;0.000\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+----------------------+-----------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ewealth |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; index\\u003c/strong\\u003e |\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+---------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; poor | 428\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 162(37.85)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 266(62.15)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; middle | 200\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 88(44.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 112(56.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; rich | 509\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 297(58.35)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 212(41.65)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+---------------------------------------------------------\\u003cstrong\\u003e breastfeeding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+---------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no | 142\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 85(59.86)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 57(40.14)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes | 995\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 462(46.43)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 533(53.57)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.003\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+----------------------+-----------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Marital |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; status\\u003c/strong\\u003e |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+---------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; single | 38\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 17(44.74)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 21(55.26)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; married| 1,078\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 523(48.52)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 555(51.48)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; widowed | 1\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0 (0.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1(100.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp; divorced | 20\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 7(35.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 13(65.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.467\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+----------------------+-----------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003esex of |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; child\\u003c/strong\\u003e |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+---------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; female\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; | 591\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 307(51.95)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 284(48.05)\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; Male\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; | 546\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 240(43.96)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 306(56.04)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.007\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+----------------------+-----------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003cstrong\\u003eAntenatal care\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e-----------+---------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no | 1,026\\u0026nbsp;\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u0026nbsp;470(45.81)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 556(54.19)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes | 111\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 77(69.37)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 34(30.63)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.000\\u003c/p\\u003e\\n\\u003cp\\u003esource: RDHS 2014-15\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe results of bivariate analysis are shown in the table above. And it shows that, province, health worker, place of residence, breastfeeding, wealth index and antenatal care are statistically significant because their p-value are less than \\u003cstrong\\u003e0.05 \\u003c/strong\\u003e(p value \\u0026lt;0.05) except maternal marital status. Means that the all mentioned variables have an influence on wasting status.\\u003c/p\\u003e\\n\\u003cp\\u003eAmong the total children who didn\\u0026rsquo;t get facility from the health workers 57.69% were wasted while 49.44% only were wasted for those who got facility from health workers which means that health workers have a role in reducing the number of wasted children. The result shows that western province is heading other province in having high number of children leaving with the problem of wasting, with 62.34% of the total surveyed children are wasted and is followed by north province which has 62.34% and the province which has low number of wasted children is Kigali city with 40.48%.\\u003c/p\\u003e\\n\\u003cp\\u003eFor maternal educational level, the results indicated that children whose mothers has high level of education are more likely not to have this problem of wasting. For those with no education wasting was 64.91% while for those in higher education wasting was at 30.91 % as shown in the table. And higher number of wasting children was in rural areas, with 56.94% of the total surveyed children.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFactors that influence underweight\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Underweight status\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp; Province\\u0026nbsp; |Total\\u0026nbsp;\\u0026nbsp; non-under(%) underweight(%)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; P-value\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+----------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003ekigali city |168\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 105(62.50)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 63(37.50)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; south |301\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 207(68.77)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 94(31.23)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; west |239\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 135(56.49)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 104(43.51)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; north |164\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 113(68.90)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 51(31.10)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; east |265\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 165(62.26)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 100(37.74)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.027\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;---------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eHealth |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; worker\\u003c/strong\\u003es |\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+----------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no |338\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 219(64.79)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 119(35.21)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes |799\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 506(63.33)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 293(36.67)\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+----------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; type of |\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp; place of |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp; residence\\u003c/strong\\u003e |\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+----------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; rural |836\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 522(62.44)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 314(37.56)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; urban |301\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 203(67.44)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 98(32.56)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.122\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; --------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eeducation|\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; level\\u003c/strong\\u003e|\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+----------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003eno education|114\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 78(68.42)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 36(31.58)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; primary|798\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 507(63.53)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 291(36.47)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp; secondary|170\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 102(60.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 68(40.00)\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; higher|55\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 38(69.09)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 17(30.91)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.422\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+----------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ewealth |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; inde\\u003c/strong\\u003ex |\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+----------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; poor |428\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 272(63.55)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 156(36.45)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; middle |200\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 123(61.50)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 77(38.50)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; rich |509\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 330(64.83)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 179(35.17)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.703\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ebreastfeeding\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+----------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no |142\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 84(59.15)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 58(40.85)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes |995\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 641(64.42)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 354(35.58)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.222\\u003c/p\\u003e\\n\\u003cp\\u003e---------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMarital |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; status\\u003c/strong\\u003e |\\u003c/p\\u003e\\n\\u003cp\\u003e------------+----------------------+----------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; single |38\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 23(60.53)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 15(39.47)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp; married |1078\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 688(63.82)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 390(36.18)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp; widowed |1\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0(0.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1(100.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; divorced |20\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 14(70.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 6(30.00)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.518\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003esex of |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; child\\u003c/strong\\u003e |\\u003c/p\\u003e\\n\\u003cp\\u003e---------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; female |591\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 374(63.28)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 217(36.72)\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; male |546\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 351(64.29)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 195(35.71)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.725\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAntenatal |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; care\\u003c/strong\\u003e |\\u003c/p\\u003e\\n\\u003cp\\u003e---------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; no |1026\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 656(63.94)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 370(36.06)\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; yes |111\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 69(62.16)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 42(37.84)\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.712\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e----------------------------------------------------------------------\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSOURCE: RDHS 2014-15\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe results of bivariate analysis are shown in the table above. And it shows that, all factors are statistically insignificant except province because their p-values are less than 0.05(p value \\u0026lt;0.05). Means that the all mentioned variables have no influence on underweight status.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eHere the province which is at higher number of underweight, western province and followed by east, and Kigali city with 43.51%, 37.74% and 37.50%. and the majority were male (56.04%).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e6.4 Multivariate analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eBinary logit parameter estimates of model 1\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e--------------------------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eStunting status|\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Coef.\\u0026nbsp;\\u0026nbsp; Std. Err.\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; z\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; P\\u0026gt;|z|\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; [95% Conf. Interval]\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e-------------+------------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eHealth worker | -1.217217\\u0026nbsp;\\u0026nbsp; .1636756\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -7.44\\u0026nbsp;\\u0026nbsp; 0.000\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -1.538016\\u0026nbsp;\\u0026nbsp; -.8964191\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;province\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; | \\u003c/strong\\u003e-.0568698\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp; .0511028\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -1.11\\u0026nbsp;\\u0026nbsp; 0.266\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.1570294\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .0432898\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eplace residence|\\u0026nbsp;\\u0026nbsp; -.571168\\u0026nbsp;\\u0026nbsp; .1838945\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -3.11\\u0026nbsp;\\u0026nbsp; 0.002\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.9315946\\u0026nbsp;\\u0026nbsp; -.2107414\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eeducation level| -.3417421\\u0026nbsp;\\u0026nbsp; .1208649\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -2.83\\u0026nbsp;\\u0026nbsp; 0.005\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.5786329\\u0026nbsp;\\u0026nbsp; -.1048513\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ewealth index\\u0026nbsp;\\u0026nbsp; |\\u0026nbsp;\\u0026nbsp; -.277401\\u0026nbsp;\\u0026nbsp; .0861079\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -3.22\\u0026nbsp;\\u0026nbsp; 0.001\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.4461695\\u0026nbsp;\\u0026nbsp; -.1086326\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ebreast feeding |\\u0026nbsp;\\u0026nbsp; 1.178479\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .219007\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 5.38\\u0026nbsp;\\u0026nbsp; 0.000\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .7492327\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1.607724\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eantenatal care |\\u0026nbsp;\\u0026nbsp; -1.59828\\u0026nbsp;\\u0026nbsp; .2778857\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -5.75\\u0026nbsp;\\u0026nbsp; 0.000\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -2.142926\\u0026nbsp;\\u0026nbsp; -1.053634\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; _cons |\\u0026nbsp;\\u0026nbsp; 1.626605\\u0026nbsp;\\u0026nbsp; .3673184\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 4.43\\u0026nbsp;\\u0026nbsp; 0.000\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .9066738\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 2.346536\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e--------------------------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eLR chi2(9) = 250.08 Prob \\u0026gt; chi2 =0.0000 Pseudo R2= \\u003c/strong\\u003e0.1620\\u003cstrong\\u003eLog likelihood = -646.94952\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSource: DHS2015-15\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eThe model is:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003elog(p)=1.626605-1.217217 health worker-.0568698 province-.571168 place residence -.3417421 education level-.277401 wealth index +1.178479 breast feeding -1.59828 antenatal care.\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe likelihood of the model is the probability that you would observe the dichotomous (actually multichotomous) outcomes of the sample, given the coefficient estimates. The logit algorithms maximize the logarithm of this likelihood, and since the probabilities is between 0 and 1, then the log likelihood is always negative. Our maximum log likelihood of obtaining outcomes of health insurance coverage from the sample is -646.94952 and the test chi-square is 250.08.\\u003c/p\\u003e\\n\\u003cp\\u003eAs the calculated chi-square statistics is highly significant at 5%, then the null hypothesis that the constrained model is correct is rejected. This means that the probability in the upper tail beyond the calculated statistic is smaller than the significance level chosen for test. Hence our explanatory variables are important covariates to the model.\\u003c/p\\u003e\\n\\u003cp\\u003eAccording to the finding shown in the table above all factors are statistically significant except province which is not because the p-value (0.266) is greater than 0.05.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eHolding other factors constant, factors constant health worker reduces the odds of stunting status by 1.21 percent which indicate that health workers have a large contribution in reducing this disease caused by malnutrition after antenatal care which has 1.6.\\u003c/p\\u003e\\n\\u003cp\\u003eOther factors like distribution by province also reduce the stunting status by 0.056 ceteric purbus, and place of residence has a contribution in reducing stunting status by 0.57. When holding other factor constant level of education reduce the odds of stunting status by 0.34 while breast feeding increase the odds by 1.17 here is also another factor called wealth index which reduces the odds of stunting status by 0.277 when other factors are hold constant.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eBinary logit parameter estimates of model 2\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e------------------------------------------------------------------------------------\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; wasting |\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Coef.\\u0026nbsp;\\u0026nbsp; Std. Err.\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; z\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; P\\u0026gt;|z|\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; [95% Conf. Interval]\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e-------------+----------------------------------------------------------------------\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eHealth worker |\\u003c/strong\\u003e -.3689097\\u0026nbsp;\\u0026nbsp; .1396012\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -2.64\\u0026nbsp;\\u0026nbsp; 0.008\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.642523\\u0026nbsp;\\u0026nbsp; -.0952964\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eprovince\\u003c/strong\\u003e| -.0440565\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .046641\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -0.94\\u0026nbsp;\\u0026nbsp; 0.345\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.1354712\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .0473582\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eplace residence\\u003c/strong\\u003e| -.4262017\\u0026nbsp;\\u0026nbsp; .1686871\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -2.53\\u0026nbsp;\\u0026nbsp; 0.012\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.7568224\\u0026nbsp;\\u0026nbsp; -.0955811\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eeducation level\\u003c/strong\\u003e| -.1954709\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .108764\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -1.80\\u0026nbsp;\\u0026nbsp; 0.072\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.4086444\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .0177026\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ewealth index |\\u003c/strong\\u003e -.2587137\\u0026nbsp;\\u0026nbsp; .0792108\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -3.27\\u0026nbsp;\\u0026nbsp; 0.001\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.4139641\\u0026nbsp;\\u0026nbsp; -.1034633\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ebreast feeding\\u003c/strong\\u003e|\\u0026nbsp;\\u0026nbsp; .2289394\\u0026nbsp;\\u0026nbsp; .1946632\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1.18\\u0026nbsp;\\u0026nbsp; 0.240\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.1525935\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .6104723\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003echild sex \\u003c/strong\\u003e|\\u0026nbsp;\\u0026nbsp; .3073024\\u0026nbsp;\\u0026nbsp; .1234634\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 2.49\\u0026nbsp;\\u0026nbsp; 0.013\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .0653185\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .5492863\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eantenatal care\\u003c/strong\\u003e| -.6047335\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .229367\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -2.64\\u0026nbsp;\\u0026nbsp; 0.008\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -1.054285\\u0026nbsp;\\u0026nbsp; -.1551824\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; _cons |\\u0026nbsp;\\u0026nbsp; .9052192\\u0026nbsp;\\u0026nbsp; .3919809\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 2.31\\u0026nbsp;\\u0026nbsp; 0.021\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; .1369506\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 1.673488\\u003c/p\\u003e\\n\\u003cp\\u003e-------------+----------------------------------------------------------------\\u003cstrong\\u003e------\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eLR chi2(8)= 82.22 Prob \\u0026gt; chi2=0.0000 Pseudo R2=0.0522 Log likelihood = -746.18373\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSource DHS2014-15\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe model is:\\u003c/p\\u003e\\n\\u003cp\\u003elog(p)= .9052192-.3689097\\u003cstrong\\u003eHealth worker\\u003c/strong\\u003e -.0440565\\u003cstrong\\u003e province\\u003c/strong\\u003e-.4262017\\u003cstrong\\u003eplace residence\\u003c/strong\\u003e-.1954709\\u003cstrong\\u003eeducation level\\u003c/strong\\u003e-.2587137\\u003cstrong\\u003ewealth index\\u003c/strong\\u003e+.2289394\\u003cstrong\\u003ebreast feeding\\u003c/strong\\u003e+.3073024\\u003cstrong\\u003echild sex\\u003c/strong\\u003e-.6047335\\u003cstrong\\u003eantenatal care\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe likelihood of the model is the probability that you would observe the dichotomous (actually multichotomous) outcomes of the sample, given the coefficient estimates. The logit algorithms maximize the logarithm of this likelihood, and since the probabilities is between 0 and 1, then the log likelihood is always negative. Our maximum log likelihood of obtaining outcomes of health insurance coverage from the sample is -746.18373 and the test chi-square is 82.22.\\u003c/p\\u003e\\n\\u003cp\\u003eAs the calculated chi-square statistics is highly significant at 5%, then the null hypothesis that the constrained model is correct is rejected. This means that the probability in the upper tail beyond the calculated statistic is smaller than the significance level chosen for test. Hence our explanatory variables are important covariates to the model.\\u003c/p\\u003e\\n\\u003cp\\u003eAccording to the finding shown in the table above all factors are statistically significant except province, level of education and breast feeding which are not because the p-value is greater than 0.05.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eHolding other factors constant, factors constant health worker reduces the odds of stunting status by 0.36 which indicate that health workers have a large contribution in reducing this disease caused by malnutrition after antenatal care which has 0.90 when other factors remains constant.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eHolding other factors constant, place of residence has a contribution in reducing the odds of wasting status by 0.42, here is also another factor called wealth index which reduces the odds of wasting status by 0.26 when other factors are hold constant. Ceteric paribus also sex of child has a contribution 0.30 in increasing odds of wasting status.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eBinary logit parameter estimates of model 3\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e------------------------------------------------------------------------------------\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eUnderweight\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Coef.\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; Std. Err.\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; z\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; P\\u0026gt;|z|\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; [95% Conf. Interval]\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e-------------+--------------------------------------------------------province| .0204013 .0444034\\u0026nbsp;\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; 0.46\\u0026nbsp;\\u0026nbsp; 0.646\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.0666278\\u0026nbsp;\\u0026nbsp; .1074305\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e_cons\\u0026nbsp;\\u0026nbsp; | -.6274855 .1492666\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -4.20\\u0026nbsp;\\u0026nbsp; 0.000\\u0026nbsp;\\u0026nbsp;\\u0026nbsp; -.9200427 -.3349283\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e----------------------------------------------------------------------\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSource DHS2014-15\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eModel is log(p)= \\u003cstrong\\u003e-.6274855+.0204013 province\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAnd because the p value of province is greater than 0.05 hence it is not statistically significant.\\u003c/p\\u003e\"},{\"header\":\"7. Discussion Of results\",\"content\":\" \\u003cp\\u003e\\u003cstrong\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAs expected the social economic factors like, health workers, maternal education, breast feeding, wealth, health care (antenatal care) index have influence on child stunting similar to the world health organization in 2018. Also in 2010 the world health organization find that poor schooling has an influence on child stunting and wasting which is the same as our findings.\\u003c/p\\u003e\\n\\u003cp\\u003eWealth index and breast feeding have an expected sign and they are statistically significant. The findings show that breastfeeding reduce child stunting status. The result is similar to Rwanda ministry of health 2013 and 2018.\\u003c/p\\u003e\\n\\u003cp\\u003eCommunity health workers and breast feeding are statistically significant and according to the results both community health workers and breastfeeding have an influence on the child reduction of stunting and wasting which has been also investigated by USAID 2016 in Haiti.\\u003c/p\\u003e\\n\\u003cp\\u003eCommunity health workers contribute a larger role in improving children health, and according to the result of Freddy Perez et al. (2009) in Mali also find that these CHWs have large role which is looks the same as findings of Brynne and Eilissh McAuliffe (2013).\\u003c/p\\u003e\\n\\u003cp\\u003eAndy Haines, et al. (2007) find that there is renewed interest in the potential contribution of community health workers to child survival, which is similar to our result that CHWs contributes to child health.\\u003c/p\\u003e\\n\\u003col start=\\\"7\\\"\\u003e\\n\\u003cli\\u003e\\u003cstrong\\u003e Conclusion and Recommendation \\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003eFrom the result, we found that community health workers have positive influence on malnutrition disease since we reject null hypothesis and confirm that community health workers have influence in the reduction of malnutrition disease in Rwanda. But there are other factors that make the malnutrition still high, this is rural areas where their education still low because most people has almost complete primary only or have no education where we found that as the level of education increase the number of children with stunting decrease and also the results indicates that children whose mothers has high level of education are more not to have problem of malnutrition.\\u003c/p\\u003e\\n\\u003cp\\u003eOther factors that contribute to malnutrition disease in Rwanda are place of residence where we found that the big number of children who are not malnourished are from rural areas, wealth index where the poorest family still have the problem according the result indicate that wealth index have a big role in the reduction of malnutrition. Those that are contribute to malnutrition level in RWANDA.\\u003c/p\\u003e\\n\\u003cp\\u003eBasing on the findings, the community health workers has great impact to reduce malnutrition disease in Rwanda. That is why I recommend the local people who are the main concern and implementers of government policies, this will be helpful to fight against malnutrition in different areas and also the improvement of nutrition.\\u003c/p\\u003e\\n\\u003cp\\u003eI recommend again community health workers to participate in different trainings provided by the government or Ministry of Health, because they will find some advices related to health and it will help them again to manage some different case of this problem. The real assets government has, is its citizens. This is where the welfare of the population comes from and with the positive leadership. The government does not force people to join the strategies but if it is a beneficial one, everyone comes to enjoy it. Citizens especially women should work hard and awareness understanding of government strategies for a support to avoid malnutrition in their families.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\" \\u003cdiv class=\\\"DefinitionList\\\"\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eAIDS\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eAcquired Immune Deficiency Syndrome\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eASM\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eAgent de Sant\\u0026eacute; Maternelle\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eCBN\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eCommunity Based Nutrition\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eCCM\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eCommunity Case Management\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eCHC\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eCenter for Health Care\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eCHEW\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eCommunity Health Extension workers\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eCHW\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eCommunity Health Worker\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eFP\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eFamily Planning\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eMDGs\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eMillennium Development Goals\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eMOH\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eMinistry of Health\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eNCDs\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eNon Communicable Diseases\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eNGOs\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eNon-Governmental Organizations\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eNISR\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eNational Institute of Statistics of Rwanda\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003ePEM\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eProtein Energy Malnutrition\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003ePHC\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ePrimary Health Care\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eRBC\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eRwanda Biom\\u0026eacute;dical Center\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eRDH\\u003c/b\\u003eS\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eRwanda Demographic Health Survey\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eRGB\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eRwanda Governance Board\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eTB\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eTuberculosis\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eUNICEF\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eUnited Nation International Children Emergency Funds\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eWHO\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eWorld Health Organization\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e \\u003cspan\\u003eHaines A, Sanders D, Lehmann U, Rowe AK, Lawn JE, Jan S, Damian G, Walker. \\u0026amp; Zulfi qar Bhutta. (2007). \\u003cem\\u003eAchieving child survival goals: potential contribution of community health workers\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eBrynne G. \\u0026amp; Eilish McAuliffe. (2013). \\u003cem\\u003eEffectiveness of community health workers delivering preventive interventions for maternal and child health in low- and middle-income countries: a systematic review\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eFreddy Perez H, Ba, Sayed G, Dastagire1. \\u0026amp; Mathias Altmann. (2009). \\u003cem\\u003eThe role of community health workers in improving child health programmes in Mali\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eMinistry of health. (2007). \\u003cem\\u003eCommunity strategy implementation guidelines\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eRwanda Ministry of Health. (2011a). \\u003cem\\u003eIntroducing Community-Based Provision of Family Planning Services in Rwanda: A Process Evaluation of the First Six Months of Implementation. Department of Maternal and Child Health, Community Health Desk\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eRwanda Ministry of Health. (2011b). \\u003cem\\u003eTrainer\\u0026rsquo;s Guide: \\u0026ldquo;Integrated Management of Child Illness,\\u0026rdquo; \\u0026ldquo;Community Case Management.\\\"\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eRwanda Ministry of Health. (2018). \\u003cem\\u003eNational Community Health Strategic Plan July 2013\\u0026ndash;\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eZaeem H. \\u0026amp; Assad Hafeez. (2009). \\u003cem\\u003eKnowledge and communication needs assessment of community health workers in a developing country: a qualitative study\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eBinagwaho DAgn\\u0026egrave;s, Agbonyitor M, Rukundo A, Ratnayake N, Kayumba J, Ngabo F. \\u0026hellip; Mary C Smith Fawzi. (2011). Under diagnosis of malnutrition in infants and young children in Rwanda: implications for attainment of the Millennium Development Goal to end poverty and hunger. \\u003cem\\u003eInternational Journal for Equity in Health\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eDr BINAGWAHO, Agnes. (2014). INTEGRATED COMMUNITY CASE MANAGEMENT OF CHILDHOOD ILLNESS. \\u003cem\\u003eMinister of Health\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eLauren Crigler. (2014). RWANDA\\u0026rsquo;S COMMUNITY HEALTH WORKER PROGRAMr. MINISTRY OF HEALTH. (2018). Rwanda: Nutrition Profile.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eMINISTRY OF HEALTH MOH. (2013). NATIONAL COMMUNITY HEALTH STRATEGIC PLAN July 2013 - June 2018. \\u003cem\\u003eMINISTRY OF HEALTH\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cdiv class=\\\"InstitutionalAuthorName\\\"\\u003eMercedes de Onis\\u003c/div\\u003e \\u003cspan\\u003eMonika B. \\u0026amp; Mercedes de Onis. (2005). Malnutrition: Quantifying the health impact at national and local levels. \\u003cem\\u003eWorld Health Organization\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eOlaf, M\\u0026uuml;ller. \\u0026amp; Michael Krawinkel. (2005). Malnutrition and health in developing countries.\\u003c/span\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cspan\\u003eRwanda Governance Board. (2017). \\u003cem\\u003eRwanda Community Health Workers Program: 1995\\u0026ndash;2015\\u003c/em\\u003e.\\u003c/span\\u003e \\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\" community health workers, prevention of disease, malnutrition in Rwanda \",\"lastPublishedDoi\":\"10.21203/rs.3.rs-41252/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-41252/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eBackground Malnutrition affects physical growth, morbidity, mortality, cognitive development, reproduction, and physical work capacity, and it consequently impacts on human performance, health and survival. It is underlying factor in many diseases for both children and adults, and is particularly prevalent in developing countries, where it affects one out of every 3 preschool-age children. A well-nourished child is one whose weight and height measurements compare very well with standard normal distribution of heights and weights of healthy children of the same age and sex. Factors that contribute to malnutrition are many and varied.\\u003c/p\\u003e\\u003cp\\u003eObjective The objective of the present study is to evaluate the contribution of community health workers in the prevention of diseases caused by malnutrition in Rwanda. Factors included: community health workers, place of residence (urban, rural), sex of child, marital status, antenatal care, breastfeeding, wealth index and education level.\\u003c/p\\u003e\\u003cp\\u003eMethodology: We used data from NISR(DHS2014.2015) collected on child that covered 1137 Households. The results show that the level of wasting, stunting, and underweight in children under five years of age was 51.89%, 58.4% and 36.24% respectively.\\u003c/p\\u003e\\u003cp\\u003eFindings: Malnutrition was significantly (p \\u0026lt; 0.01) higher among boys than among girls. The prevalence of wasting and stunting decreased significantly by community health workers and antenatal care. The higher the level of parent’s education, the lower the level of child underweight observed. Breastfeeding was found to reduce the occurrence of underweight among children.\\u003c/p\\u003e\\u003cp\\u003eConclusion The study findings imply that efforts for redressing child under nutrition in Rwanda should focus on factors associated with development outcomes such as, community health worker’s improvements, parent’s education, and the creation of employment or economic engagements that do not comprise important child care practices such as breastfeeding and antenatal care.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Contribution of community health workers in the prevention of disease caused by malnutrition in Rwanda\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2020-07-15 15:39:38\",\"doi\":\"10.21203/rs.3.rs-41252/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"0fa6c2b6-c423-45f2-98ec-13df31a1485f\",\"owner\":[],\"postedDate\":\"July 15th, 2020\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":157480,\"name\":\"Health Economics \\u0026 Outcomes Research\"},{\"id\":157481,\"name\":\"Health Policy\"}],\"tags\":[],\"updatedAt\":\"2020-07-15T15:40:29+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2020-07-15 15:39:38\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-41252\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-41252\",\"identity\":\"rs-41252\",\"version\":[\"v1\"]},\"buildId\":\"GqpaHPwrfC8PjnIFayRh5\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}