Author: Nyamai Francis
Contact: 0711984848 | francisnyamai65@yahoo.com
Institution: Great Lakes University of Kisumu
ABSTRACT
Vitamin A is important for growth and development especially for young children who are under five years. If these children are not given Vitamin A then they stand high chances of their immunity being weak and this can lead to high morbidity and mortality. Kitui has low uptake of vitamin A and this leaves many children in this County not given this Vitamins which again can interfere with their health status. For proper health monitoring for these children, it means that they should be given vitamin A at the right time. Therefore, this study is determining factors associated with uptake of vitamin A among children below five years at Kitui County Referral Hospital. The study adopted cross-sectional analytic study design. It used both qualitative and quantitative data. The data was collected using a questionnaire. In this study, Systematic random sampling which is a type of probability sampling technique was used. Data was analyzed using percentages, chi-square and logistic regression. Results were presented using tables and figures. The study found out that demographic factors, Knowledge of mother about vitamin A and mothers perception on vitamin A have a significant association with vitamin A uptake at p-value<0.05. Thus the study concluded that there is likely hood for complete uptake of vitamin A was higher among children born of older mothers compared to children born of young and adolescent mothers. These differences could have occurred due to the fact that adolescent mothers did not have experience in child care and the Vitamin A schedule and thus their children were more vulnerable. Hence it also recommends that Health workers should have system and structures of ensuring that young mothers get health related information for their children from prenatal clinic and during delivery as this will reduce the number of children who have not completed vitamin A schedule in this category.
Vitamin A, Children, Under Five, Factors
Introduction
Vitamin A is essential for numerous intrinsic processes. The most well-known and understood process is that of vision. The retinal form of vitamin A is essential for the neural transmission of light into vision. Epithelial cells are highly dependent on retinoic acid and are commonly used to treat a variety of skin diseases. A developing fetus is also highly dependent on retinoic acid, as it is essential to the growth of the eyes, lungs, ears and heart. The retinoids are not only the most active form of vitamin A, but also a current area of interest to many scientists (WHO., 2017).
Vitamin A deficiency is estimated to affect approximately one third of children under the age of five around the world. It is estimated to claim the lives of 670,000 children under five annually. Approximately 250,000–500,000 children in developing countries become blind each year owing to vitamin A deficiency, with the highest prevalence in South East Asia and Africa (WHO., 2017).
Vitamin A deficiency can occur as either a primary or a secondary deficiency (WHO., 2017). A primary vitamin A deficiency occurs among children and adults who do not consume an adequate intake of pro-vitamin A carotenoid from fruits and vegetables or preformed vitamin A form animal and dairy products. Early weaning from breast milk can also increase the risk of vitamin A deficiency (WHO., 2017).
Secondary vitamin A deficiency is associated with chronic mal-absorption of lipids, impaired bile production and release, and chronic exposure to oxidants, such as cigarette smoke, and chronic alcoholism (WHO., 2017). Vitamin A is a fat soluble vitamin and depends on micellar solubilization for dispersion into the small intestine, which results in poor use of vitamin A from low-fat diets. Zinc deficiency can also impair absorption, transport, and metabolism of vitamin A because it is essential for the synthesis of the vitamin A transport proteins and as the cofactor in conversion of retinol to retinal (Gibbs., 2014). In malnourished populations, common low intakes of vitamin A and zinc increase the severity of vitamin A deficiency and lead physiological signs and symptoms of deficiency. A study in Burkina Faso showed major reduction of malaria morbidity with combined vitamin A and zinc supplementation in young children (Giaquinto et al., 2010).
In Kenya vitamin A consumption among children is about 10.5% hence 89.8% do not take or consume food high in vitamin A. In rural areas due to poor infrastructure lack of access to medical facilities and breastfed infants since most of breast milk is deficient in retinol further heightening the risk of vitamin A deficiency (Bull., 2014).
Vitamin A intake as per research done in fourteen Counties in Kenya, shows between 6-60 months, 7% of children have poor intake of vitamin A. 32.9% had marginal vitamin A deficiency. Age group 6-11 months ,40.7% had very poor intake. Main problems research shows are in Mombasa Kwale, Kitui, Baringo,Kisumu,Kisii, Garissa ,Mandera and Bungoma (Goodman.,2016).
Uptake of vitamin A in developing countries Kenya included is still low as compared to Western countries. Studies have been done on uptake of vitamin A, however none has been done on the same in Kitui County. There has been reduced donor support especially from USAID resulting in low supplies of Vitamin A in Kenyan health facilities and this study is greatly important to identify the gaps and increase body of knowledge
2.4.1 Vitamin A uptake
Several studies have been conducted to determine vitamin A uptake. In analytical home based quantitative study conducted in Flanders Belgium by Braekman., (2013) with a sample size of 600 children from 380 families the results showed that Belgium coverage rate for two doses of vitamin A uptake was high at 86%. In another analytical quantitative study done by Moonlight (2015) which consisted of 12,065children, which aimed at assessing the integration of vitamin A in the immunization schedule, correlating vitamin A uptake with trends in age in the immunized group, Vitamin A uptake was considered high at 90%. In another study conducted in Brazil by Adams., (2014) on uptake of vitamin A and timeliness of routine schedules, the results showed that the administrative uptake with the two-dose series of vitamin A ranged from 85% to 88%.
Some studies has shown low uptake of vitamin A. These include a study done in South Africa by Bricks (2015) that showed that 40% of the children aged less than one year had received a complete one dose series of vitamin A, considered very low compared to the national target of 90% coverage. These findings are similar with the analytical hospital based study conducted in USA study by Gibbs., (2014) targeting 12,040 children whose results showed that vitamin A uptake was 24% and one year later doubled to 48%. The percentage of children receiving vitamin A continued to grow steadily, reaching 60% by April 2015 and reaching 70% beginning November 2015. Between 2013 and 2015 81% of eligible children were given at least one dose of vitamin A.
In a study conducted in USA by Judy., (2016) whose objective was estimating the uptake of vitamin A among children aged one year, the uptake was 57%. Similarly studies conducted in Asia and Pacific countries by Santosham et al., (2015) on vitamin A uptake indicated that the uptake was approximately 50%. In Singapore, 30% in Korea and Taiwan, and lower than 10% in other countries. In another analytical study done in Canada by Dube., (2016) vitamin A uptake was 42%. These results are also similar with findings of a study conducted in Germany by Vizule (2014) which showed that the uptake of vitamin A was slightly above 50% in children aged between 6 and 60 months in five eastern federal states and it was slightly above 30% in the 11 western states.
Compliance and completion of Vitamin A
On compliance Wag et al (2015) indicated that the purpose of the recommended vitamin A schedule is to protect every child as soon as possible and to minimize the period in which they are prone to infections. Any delay can have a major impact, especially for disease associated with immune system and eye problems. The findings are in agreement with those of Giaquinto et al., (2010) who indicated that individual children are recognized as “compliant” if he/she received all doses in accordance with the recommended schedule. Completion is defined as receipt of all doses of vitamin A. Despite benefits of vitamin A completion CDC (2016) estimated that only 67% of the eligible children 19 to 35 months in the USA had completed a vitamin A series . These findings were similar with results of a study conducted in Belgium by Braeckmam., et al (2016) who found out that despite the fact that all doses of vitamin A uptake was 90% only 30% and 10% of the children had received their first and second dose respectively at the recommended age. This means that 60% did not adhere to recommended age to get the first dose and the others doses. This is in line with a study by Hodge et al., (2013) which showed that majority of the children received their second dose too late. Following the national recommendations for the first dose of vitamin A should be administered at six months of age.
Daskalaki et al., (2014) in USA also in his study also found that after the first six months of vitamin A uptake, 20% of children received their second late. Catherine et al., (2014) in her study also assessed timeliness as per the 2009 ACIP recommendation and patterns of vitamin A uptake. The results showed that 18% of infants receive a second dose of vitamin A more than 10 weeks after their first dose, 7% of infants received their second dose of vitamin A more than 12 months after their first dose. Across all years, approximately 8% of infants received their first dose of vitamin A at ages older than the maximum recommended age for the first dose. However, on completion Catherine et al., in (2014) results indicated that 87% of children completed the schedule. For all the studies it was evident that compliance was not achieved.
Maternal Age
Most studies have shown that as most maternal age increases vitamin A uptake increased. In a study conducted in USA by Salmon et al., (2015) results showed that uptake among children with 17 years old mothers was 64%; whereas uptake among children of mothers aged 17-26 years old increased by 16.3% making it 80.3% overall. In a cross sectional community-based study conducted in 8 rural and 2 urban villages by Balachew et al., (2015) in Ambo Woreda, in central Ethiopia, the researchers were looking for factors associated with complete vitamin A uptake in children aged 12-23 months. Vitamin A uptake in children born of mothers aged 15-20 years was 4.3% whereas those above 21 years had 31.4%. Similarly a hospital based analytical study done in USA by Catherine., (2014) to assess patterns of vitamin A uptake and in privately –insured US children, the results revealed 69% of children who completed doses series were born to mothers who were 25-39 years of age whereas 31% were born by younger mothers. In another study conducted in similarly these observations agreed with those of study done in India by Yadlapalli (2014) (AOR=95% CI;4.47(1.47-14.15), who found than increasing mothers age increased the likelihood of a child to complete all vitamin A doses. The researchers concluded that children born to younger mothers are less likely to complete the vitamin A doses, and the trend remained consistent.
2.4.4 Maternal Education
Most studies have shown that formal education can improve vitamin A uptake. In a study conducted by Wisyonge et al., (2013) on factors associated with low childhood vitamin A uptake which had a sample size of 27,094 children aged 12-23 months, within 8,56 communities from 24 countries in sub-Sahara Africa. The results of the multi-level logistic regression analysis showed that children born to mothers with no formal education were more likely not to complete vitamin A doses than those born to parents with secondary or higher education. It was also noted that children from communities with high illiteracy rates were also more likely not to complete vitamin A doses. In cross sectional household survey that utilized multistage sampling technique conducted in Nigeria by Brown et al.,(2015) in which 400 mothers s of children aged 12-24 months from four communities were randomly selected and interviewed, the results showed that children of mothers with secondary education or more, are more likely to complete vitamin A doses.
These findings are almost similar with those conducted in Papua new guinea by Tina et al., (2014) and with those of a study conducted in Ambo Woreda,central Ethiopia by Balachew (2014) who had bivariate analysis showing that literate mother was significantly associated with complete vitamin A status of children.
Maternal knowledge /awareness on importance of vitamin A uptake
Majority of studies have showed that there was very low knowledge about vitamin A uptake and deficiency. In a hospital based quantitative analytical study conducted in Uganda by Nakawesi etal., (2015 prevalence and factors associated with vitamin A uptake among children admitted with acute Pneumonia, all 390 mothers had very low information about vitamin A. Similarly in a qualitative study done in USA by Patel et al., (2015) the researchers gave printed informational material describing vitamin A uptake and deficiency of vitamin A to all the mothers they had recruited in Sunnyvale and Kansas city because they wanted them to rate the cases. The results indicated that only 49% had heard about vitamin A prior to the study and most mothers reported that they were not aware of its public health impact or its potential for causing severe disease and death. They did not rate the disease to be a high priority health issue for children. These findings tally with those of a study conducted in five countries namely: India, Indonesia, Thai land, Nicaragua and Ukraine by Evan et al., (2013). The results of that descriptive qualitative study indicated that out of 546 mothers who were involved in all of the countries, except for Nicaragua, awareness and knowledge about vitamin A was extremely low. In a study conducted by Dube et al., (2015) were mothers were asked in an open ended questioners on sources of information about vitamin A uptake, 95% of parents whose children had received dose of vitamin A said they got information from Doctor, 19% said they got information from their families and friends. 10% said they got information from (Books, newspapers and magazines. The conclusion was that health education in hospitals, the simple fact of answering questions about vitamin A and providing the information pamphlet might act as educational intervention and increase vitamin A uptake. These results are in agreement with St-Amour et al., (2016) who indicated that when good interaction is offered giving written information to parents, could increase their decision to take their children to hospital for vitamin A uptake.
Informational material
In a qualitative assessment of factors influencing acceptance of vitamin A among 100 mothers conducted in USA by Patel et al., (2015) mothers identified the internet as a primary source where they obtained health information, others cited health workers and others mass media.
Mothers perception towards vitamin A
In a qualitative study conducted in USA by Manish et al (2013) found out that most mothers considered vitamin A uptake by children to be very important and serious matter for well-being. Based on scale of 1 (“not at all serious”) to 7 (“very serious “), 59% considered the vitamin A uptake to be very serious matter in children health status (rage 5to 7), while 36% considered vitamin A uptake to be serious matter (range =3 to 4) and only 5% considered it to be not at all serious (rage =1 to 2). Similarly results of a survey conducted in France by Hash et al (2014) indicated that among the 1002 mothers of at least one child below two years 43% considered infection as a severe whereas 51% very severe pathology for young children. In Nigeria Tagbo (2013) results showed that about one third,27.5% considered vitamin A uptake very serious, moderate 59.4% and not serious at all 6.6%.
2.4.8 Perceived benefits
Several studies done on vitamin A uptake benefits indicate that majority of mothers perceived it as beneficial to the health of children. In a study done in Tasba pri,Nicaragua by Treleaven Emily et al (2015), 98% of mothers rated vitamin A as important or very important in preventing their children from the diseases. Similarly a study in Nigeria by Tagbo (2013) had close results of 70.3% in USA Manish (2014) asked the mothers to rate their likelihood of their children using vitamin A on a scale of one to seven, with one being “absolutely not” and seven being “absolutely yes,” the mean score was 5(range=3 to 6). However, when asked to rank the likelihood of having their children get vitamin A from 1 (“definitely not get”) to 7(“definitely get”), 29% ranked between 1to 2, 36% between 3 to 4 ,and 35% between 5 to 7.
2.4.9 Perceived barriers
Studies conducted showed variation in types of barriers to vitamin A uptake. In a population based cross-sectional study was conducted in Nicaragua by Emily et al (2015) in which 189 women of reproductive age (15-49) were respondents,44% of mothers reported that they were unable to take their children for vitamin A on time or at all. Some of the reasons they gave were: 29% said clinic was too far away, 10% said clinic was closed when they arrived while 10%, clinic was stocked out of vitamin A. 42%, others reported that child was too sick to receive a vitamin A while 13% were concerned about the side effects.
2.4.10 Accessibility (distance to health care facility)
Several studies done on accessibility to healthcare have shown that improving access to vitamin A increases uptake. In a study conducted in Uganda by Kiwanuka et al (2013) noted that a key factor in the reduction of child mortality and the promotion of child health is universal accessibility of health-care services which is determined by many different factors including distance. Similarly in a cross sectional study conducted in Ethiopia by Okwaraji et al (2014) among children aged between 12 and 59 months, travel time to health facilities appeared to be a barrier to the delivery of primary health care services to children in a remote community.
Findings from a study conducted in 2016 in East Harlem and the Bronx in New York City by Bryant et al (2016) showed that children who were isolated from the health care services were less likely to have been given vitamin A in the past. Emily et al (2014) on study conducted in Nikaragua on barriers to vitamin A, 29% of parents reported that the clinic or health post was too far away and thus the children could not accesses services. These findings also agree with Feikin., (2015) who found out that distance to health facilities significantly reduced the use of health services by the population.
MATERIALS AND METHODS
3.1 Introduction
This chapter describes study population, study site, sampling method and sample size determination. It also clarifies criteria of inclusion and exclusion in the study. It further describes the process of data collection, instruments to be used, data quality control, data analysis and presentation. More so it also states out plan for data collection, data analysis and ethical consideration.
3.2 Study design
The study design was analytical cross-sectional study using quantitative methods of data collection. The analytical design was to establish relationship between maternal age, maternal education, mother’s knowledge, mother’s perception and Vitamin A uptake. The descriptive approach enables description of the characteristics of the study population in terms of age, sex, place of delivery, distance to facility, age at receiving first dose in Six months and age at receiving subsequent doses.
3.3 The study population and unit of analysis
The study population comprised of children below five years who are getting services at facility at the time of the study. The children represented the unit of analysis while the mothers were the respondents.
3.4 Inclusion criteria
- Adult (above 18 years) mothers.
- Children between the age of 6 months to 5 years old
- Mothers are willing to participate
- Mother willing to give informed consent.
Exclusion criteria
Those who were not willing
3.5 The study site
The study area is in Kitui County Referral hospital, located in Kitui central sub- County of Kitui County. This is the only County Referral Hospital with catchment population of 250,000 people. The catchment area has a total of 3514 households served by 175 community health extension workers (CHEWs) with a total of 100 community health workers (CHW) linked to the facility. Mostly the facility serves people from nearby region and others come from neighboring sub counties, as well as referrals from other county regions. The study covered both pediatric, casualty and MCH clinic. These are areas where children get their services. Pediatric, casualty offer curative services and screening of Vitamin A compliance and completion. If a child has missed any or has not received vitamin A they are sent to MCH clinic. Services offered at the MCH are: Vitamin A supplementation, growth monitoring, family planning, Antenatal clinic, postnatal and prevention of mother to child transmission of HIV, Cervical cancer screaming and gynecological clinic. All routine immunization and vitamin A are offered free of charge. Paediatric, casualty operates 24 hours whereas MCH clinic operates five days a week from 8am to 5 p.m excluding public holidays.
3.6 Study population and Sample size determination
A sample is a smaller group obtained for accessible population with the same characteristic to represent the whole population and sample size is smaller group obtained from the sample to represent the whole population. Sample size is number of observation in a sample (Evans et al., 2000) where time and research allow a researcher should take as big a sample as possible.
The study population targeted the 1805 mothers with 5540 children of Kitui township. This which explicitly mean that 1805 mother’s participated
The sample size was determined the using formula suggested by Fishers et al., 1998
n = z2pq
d2
Where:
n= the desired sample size (if the target population is greater than 10,000)
z= the standard normal deviate at the required confidence level
p= the proportion in the target population estimated to have characteristic being measured
q=1-p
d=the level of statistical significance set
If there is level no estimate available of the proportion in the target population assumed to have characteristic of interest, 50% should be used as recommended by Fisher et al (1998)
For example if the proportion of a target population with a certain characteristic is, 50, the z-statistic is 1-96 and we desire accuracy at the OS level then the sample size is
N=(1.96)2(0.5) (.5)
(0.5)2
= 3.8416*2500
25
=384.16
n=384
Since the target population is less than 10,000, the sample size was adjusted using nf=n/(1+(n/N) as suggested by Mugenda and Mugenda(2003).
Where n is the calculated sample size using fishers etal.,(1998)=384
N is the targeted population =1805
nf=384/(1+384/1805)
=316.6
=317 participants
3.7 Sampling Technique
In this study, systematic sampling which is a type of probability sampling technique was used. This is to ensure that there was fairness in selecting participate in the study and participants are selected after a given interval. This size of interval is determined by Kth partcipants.Every kth participant or child was selected from a list of all children below five years of age who were treated given Vitamin A in Kitui County Hospital. The register which served as a sample frame had a column for vitamin A uptake. According to Ken (2012) sampling formula, states that the sampling should starts by selecting an element from the list at random and then every kth element in the frame is selected, where k, the sampling interval (sometimes known as the skip): this was calculated as
k =N/n
Where n is the sample size, and N is the population size.
Using this procedure each element in the population has a known and equal probability of selection and participation.
Therefore:
k = 1805
317
k = 5
Thus every fifth child was selected.
3.8. Data collection methods
3.8.3. Training
The researcher recruited two enumerators to assist in data collection. Both were health workers so as to handle any psychological harm which may occur during the interview. The training took one day and included understanding the questionnaires, how to fill the responses, how to get the consent from the mothers and ethical considerations.
3.8.4. Pretesting and piloting
In 2013 Cohen & Crabtree stated that pre-testing and piloting of data collection tool by the interviewers are used to minimize bias and strengthen the validity and reliability of the results. This is done to check whether the tool is giving consistent results during the pre-test and the piloting and whether it is covering all the specific objectives. It also helps in checking how long the enumerators took to fill one questionnaire. The pilot was done at Katulani subcounty hospital. 10% of the sample size was used which is 31 questionnaires. At the end of tool pretesting, errors, difficult questions, sensitive questions were identified and corrected before the actual study is conducted.
3.9 Data collection
Structured questionnaires with closed ended questions and Likert scale statements were used to collect the quantitative data. The questionnaire were divided as per the specific objectives which are: demographic factors, knowledge, source of information, education level, Maternal age and mother’s perception to find out whether there is a relationship between them and vitamin A uptake among children aged below five years in Kitui County Referral Hospital.
The information on vitamin A uptake was obtained in hospital records: from mother and child health booklets (MCHB), road to health clinic cards (RTHC) and from mother’s verbal reports. All mothers were requested to show the interviewer MCHB or RTHC used to record child’s report. If the booklet is available, the interviewer checked the dates vitamin A was given and compare it with the age of the child then. If the mother does not have a card she was further asked to recall whether the child had received vitamin A.
3.10. Data Analysis
After the questionnaires were completed, errors in responses, omissions, exaggerations, inconsistencies, missing values, outliers and biases were checked. This is data cleaning.
For anonymity purposes all questionnaires were given a code. Data was entered and verified after effective coding. For easy management data was captured in Ms – Excel 2012 windows and the analysis was done using statistical package for the social Science (SPSS). Results were presented using tables and figures in order to compare differences in proportions and also to describe baseline characteristics of study participants. Since the dependent variable is categorical (dichotomous variable), Pearson chi square was applied to sets of categorical data to evaluate how likely it is that any observed difference between the sets can arise by chance. Logistic regression was also used to measure the relationship between the categorical dependent variable (complete or incomplete vitamin A uptake) and independent variables namely; maternal age, maternal education, mother’s knowledge and mother’s perception..
3.11 Ethical Considerations
Study permission and approval was obtained from Great Lakes University of Kisumu and
from Kitui county referral Hospital administration. The Kitui sub county commissioner was informed since approval is required in his/her area of jurisdiction. The enumerators were ask permission from the respondents before they interview them. Respondents were also be assured that the information shared was confidential and the study is for learning purposes only,
Participation in the study was voluntary and informed consent was obtained. Participants were v also be assured that their responses were not be attributed to them. Names were not recorded.
3.11.1 Informed Consent
Participation in the study was purely voluntary, and the participants are free to withdraw at any time during the interview. Verbal and written consent was sought from the respondents as a requirement to participate in the study. An explanation on the nature of the study and ethical
Considerations prior to being interviewed was done.
3.11.2 Risks
3.11.2.1Psychological Harms
Participation in research may result in undesired changes in thought processes and emotions (e.g. episodes of depression, feelings of tress, guilt, and loss of self esteem). Most psychological risks are minimal or transitory, but some research has the potential for causing serious psychological harm. Stress and feelings of guilt or embarrassment may arise simply from thinking or talking about one’s own behavior or attitudes. These feelings may also be aroused when the respondent is being interviewed. (Example, when asking about vitamin A, a mother may remember a child who died due to malnutrition or lack of vitamin A. To address this, the enumerators were health workers who are trusted by community so as to handle any risk that may occur as a result of this study.
3.10. Data Analysis
After the questionnaires were completed, errors in responses, omissions, exaggerations, inconsistencies, missing values, outliers and biases were checked. This is data cleaning.
For anonymity purposes all questionnaires were given a code. Data was entered and verified after effective coding. For easy management data was captured in Ms – Excel 2012 windows and the analysis was done using statistical package for the social Science (SPSS). Results were presented using tables and figures in order to compare differences in proportions and also to describe baseline characteristics of study participants. Since the dependent variable is categorical (dichotomous variable), Pearson chi square was applied to sets of categorical data to evaluate how likely it is that any observed difference between the sets can arise by chance. Logistic regression was also used to measure the relationship between the categorical dependent variable (complete or incomplete vitamin A uptake) and independent variables namely; maternal age, maternal education, mother’s knowledge and mother’s perception..
3.11 Ethical Considerations
Study permission and approval was obtained from Great Lakes University of Kisumu and
from Kitui county referral Hospital administration. The Kitui sub county commissioner was informed since approval is required in his/her area of jurisdiction. The enumerators were ask permission from the respondents before they interview them. Respondents were also be assured that the information shared was confidential and the study is for learning purposes only,
Participation in the study was voluntary and informed consent was obtained. Participants were v also be assured that their responses were not be attributed to them. Names were not recorded.
3.11.1 Informed Consent
Participation in the study was purely voluntary, and the participants are free to withdraw at any time during the interview. Verbal and written consent was sought from the respondents as a requirement to participate in the study. An explanation on the nature of the study and ethical
Considerations prior to being interviewed was done.
3.11.2 Risks
3.11.2.1Psychological Harms
Participation in research may result in undesired changes in thought processes and emotions (e.g. episodes of depression, feelings of tress, guilt, and loss of self esteem). Most psychological risks are minimal or transitory, but some research has the potential for causing serious psychological harm. Stress and feelings of guilt or embarrassment may arise simply from thinking or talking about one’s own behavior or attitudes. These feelings may also be aroused when the respondent is being interviewed. (Example, when asking about vitamin A, a mother may remember a child who died due to malnutrition or lack of vitamin A. To address this, the enumerators were health workers who are trusted by community so as to handle any risk that may occur as a result of this study.
3.11.2. 2 Economic Risks
Participation in research can result in additional actual cost to individuals like time wasting. The enumerators were not to waste respondent’s time. The respondents were also informed before giving consent that they were not required to pay anything to participate in the study and neither were there be any monetary compensation or pay for participating.
3.11.2.3 Confidentiality
Confidentiality pertains to the treatment of information that an individual has disclosed in a relationship of trust and with the expectation that it was not be divulged to others without permission in ways that are inconsistent with the understanding of the original disclosure. During the informed consent process, respondents were informed of the precautions that was taken to protect the confidentiality of the data and was also be informed of the parties who was or may have access to the information. The respondents name was not recorded but was coded so as to ensure confidentiality. The interview was to take place in a secluded place where there was no interruptions to ensure privacy rights are adhered to. All questionnaires were kept under lock and key to safeguard them. The information collected was not be given to people who are not stakeholders.
3.12. Dissemination plan
After the study, feedback was given to all stakeholders among them Great Lakes University of Kisumu, Kitui county referral hospital administration, Sub-county commissioner and health department of Kitui County.
Later the results can be disseminated in other forums including seminars, presentations and scientific conferences.
RESULTS
4.1 Introduction
This chapter presents the analysis of the data which was collected using a structured questionnaire. Data was collected from a total 317 children. The data was analyzed using percentages, means, frequencies, correlation, regression and chi-square was used to generalize findings. The data was presented using tables and figures. The chapter was guided be the sections below.
4.2 Response rate.
The data was collected from the all targeted sample of children through the consent and acceptance by their primary care givers. All 317 children were involved in this study hence achieving 100% response rate. This was so because the study was conducted within the health facility where the children were being attended to hence it was convenient.
4.2 Social demographic factors
The respondents were requested to indicate their socio-demographic factors and they responded as shown in the sub sections below.
4.2.1 Parental background
The mothers of children involved in this study were requested to indicate their marternal age ,education ,marital status, religion, and distance they cover when going to the health facillitiy . They responded as shown in the table 4.1 below..
Table 4.1 Ddemographic Ccharacteristics of the Mothers
From table 4.1, majority of mothers were below 30 years old (80.9%) with young and adolescent mothers (25 years and below) comprising of 42.5% of total respondent. Majority of respondents had formal education. Only 1.4% reported to have no formal education .Over ¾ (76.3%) of the mothers were married. Almost half of the respondents were protestants were protestant (49.6%). Majority (64.3%) of respondents came from the area neighboring the facility with a distance of less than five kilometers
4.2.2 Characteristics of the children
The mothers of children involved in this study were requested to indicate the demographic characteristics of their children based on the gender, children age in months, place of delivery, MCHB or CWC or RTH and if they recall MCHB or CWC. They respondent as shown in the table below.
From table 4.2, the e total number of children studied was 317.The proportion of males and females were almost the same (49.7%) and (50.3%) respectively. Most children (93% were delivered at the health facility and the rest at home. Majority (97.4%) had mother and child health booklet (MCHB) or child welfare card (CWC) seen at the time of study. About 1/3rd (37.1%) of the children were between 6-9 months old. Most (88.9%) of the children completed the doses of vitamin A , 6.3% received one dose and 4.9% did not get any dose at all.
4.3 Association between demographic characteristics and Vitamin A uptake
This association was analyzed and the results were displayed and interpreted as shown in the subsections below.
4.3.1 Association between children gender and Vitamin A uptake
The association of children gender on vitamins A uptake was tested using odd ratios. The results were analyzed and displayed as shown in the table below.
From table 4.3, the male had an odd ratio of 1.6573 which indicates that they had more times by 0.6573 to get the uptake of vitamins A compared to the female children. The uptake of Vitamin A for male and female was significant at p-value<0.05.The chi-square was also significant at p<0.05 which indicates that gender had a significant association with the uptake of vitamins A in kitui County. This implies that gender determines the level of uptake for vitamin a among children in Kitui County. It implies that male had higher uptake of Vitamin a compared to female.
4.4 Associations between maternal age and Vitamin uptake
The maternal age was categorically associated by the uptake of vitamins A was analyzed using chi-square and odd ratios and the results were displayed as shown in the table below 👇
From table 4.4, the age of women between 21-25 were found to be 2.349 time to than their counterpart who were older which means that the younger the woman the uptake of vitamins A to their children increases . These odd ratios for the ages of women were significant at p<0.05 except the older mothers of the age between 31-35 and above 36 years of age. The chi-square was also significant at p<0.05 which indicates that age of the mother had a significant association with the uptake of vitamins A in kitui county.From these results respondents who were from the age of 21-25 had more times to give their children vitam A compared to under respondents from the stated age brackets.
Table 4.5 Association between maternal age and vitamin A uptake
This association was further described by the logistic regression which tried to find the association between marital age and uptake of vitamins A and the results were shown in the table 4.5 below 👇
