Constraints Militating Against Wellness Seeking Behaviour among Adults in Abia and Imo States Nigeria

Uka-Kalu Chioma Ezinne; E.T. Oparaocha; Joakim Nwaokoro; U.W. Dozie

Department of Public Health, School of Health Technology, Federal University of Technology Owerri, Imo State, Nigeria.

DOI: https://doi.org/10.51244/IJRSI.2023.10903

Received: 17 July 2023; Revised: 11 August 2023; Accepted: 23 August 2023; Published: 26 September 2023

ABSTRACT

This study assessed the constraints that militate against the wellness seeking behavior among adults in Abia and Imo States, Nigeria. The study employed a descriptive survey design using a quantitative approach, targeted at adults who were recruited through multistage and simple random sampling across Abia and Imo States in Nigeria. A semi-structured questionnaire was used to collect data. Descriptive statistics were used, and linear regression model was used to test for associated factors while t-test and z-test were used to test for significant differences between the two states. All data analysis were done at 5% level of significance. The study revealed that the main constraints to wellness seeking behavior were financial problems, dislike of modern medicine, large family size; belief of not getting sick, being too young, and wellness activities are unnecessary. Hence, it was concluded that there is a need for targeted public health interventions. These interventions should focus on improving access to health facilities and resources and addressing the competing demands that limit engagement in wellness activities in Nigeria.

Keywords: Wellness, Wellness Seeking Behavior, Constraints, Militating factors.

INTRODUCTION

The wellness seeking behavior (WSB) of a people determines how health services are used and in turn the health outcomes of populations (Shaikh and Hatcher, 2005). Factors that determine wellness seeking behavior may be physical, socio-economic, cultural, or political. Indeed, the utilisation of a health care system may depend on educational levels, economic factors, cultural beliefs, and practices. Other factors include environmental conditions, socio-demographic factors, knowledge about the facilities, gender issues, political environment, and the health care system itself (Ogunlesi and Olanrewaju, 2010).

A key determinant for wellness seeking behavior is the organisation of the health care system (Shaikh and Hatcher, 2005). In many health systems, particularly in developing countries such as Nigeria, illiteracy, and poverty, under funding of the health sector, inadequate water and poor sanitation facilities have a big impact on health indicators. In addition, cost of services, limited knowledge on illness and wellbeing, and cultural prescriptions are a barrier to the provision of health services. These challenges, which are significant in Nigeria’s health system, affect the wellness seeking practices of the people. Inappropriate wellness seeking behavior has been linked to worse health outcomes, increased morbidity and mortality and poorer health statistics (Mwase, 2015). Studying wellness seeking behavior in a community is an important tool in understanding how healthcare facilities are utilized and identifying the determinants of poor utilization of available health-care facilities (Shaikh, 2008). Abia and Imo states make up a good part of the population in the Southeast part of the country. Research on the adults in these states will help give an idea of their wellness seeking behaviour and factors that influence it. Overall, a better understanding of wellness seeking behavior in the Southeast part of Nigeria is essential to developing effective interventions and strategies to promote health and wellbeing in the region and the country as a whole. Research in this area can help healthcare providers and policymakers to design culturally appropriate interventions that are tailored to the unique needs of the population in the Southeast region and other parts of the country. Thus, this study was conducted to identify constraints that militate against wellness seeking behavior among adults in Abia and Imo States.

METHODOLOGY

The study used the descriptive survey design approach. According to Orodho (2012), the descriptive survey design is effective, and easy to conduct, and it also ensures ease in accessing information. The descriptive survey design allows the researcher to gather information, summarize and interpret data for purposes of clarification. The descriptive survey design is useful in collecting information about people’s attitudes, opinions, habits, or perceptions about issues under investigation.

The target population for this study comprised adults in Imo and Abia States, Nigeria. For this study, the adults are taken to be people above 18 years of age. Based on the 2006 National Population Census and an annual estimated growth rate of 2.8% for this age group (18 years and above), the estimated population for 2021 is 4,978,758 in Imo State and 4,112,230 in Abia State. Therefore, the study target population is a total of 9,090,988 people.

The sample size in this study is determined using Taro Yamane’s statistical method. This method for sample size population was formulated by the statistician Taro Yamane in 1967 to determine the sample size from a given population using a confidence level of 95% and 5% margin error (Yamane, 1973). The formula presented mathematically is thus;

where;

n = sample size

N = population size

e = marginal error (0.05)

With a target population size of 9,090,988 according to the 2006 National Population Census, the sample size is calculated as below:

Therefore, 400 people is the minimum sample size in this study. Multi-stage and simple random sampling techniques was used in collecting data. Each state was statutorily divided into 3 senatorial zones and has 27 Local Government Areas (LGAs) in Imo state and 17 LGAs in Abia state. The LGAs in each state is stratified by senatorial zone and locality. In the first stage, a representative urban and rural LGA was selected by simple random sampling (by balloting without replacement) from each senatorial zone. LGAs in Abia and Imo states are further stratified into Districts/Area organized by postal codes. In the second stage, one District was selected by simple random sampling by balloting without replacement from each selected LGA. Districts within the LGAs are further stratified into villages. In the third stage, one village was selected by simple random sampling by balloting without replacement from each selected District.

From a notable landmark in a selected village, households were identified, and eligible respondents were selected moving in a clockwise direction. Two eligible participants (of opposite sex) were selected per household. this study used questionnaire to obtain adequate and reliable information for this study. The questionnaire was both structured and semi-structured nature, using a modified Health Behavior Lifestyle Profile II and Wellness Behaviors Inventory (WBI) questionnaires. The questionnaire was divided into five (5) sections. Section A collected demographic data from the respondents, Section B collected the socioeconomic characteristics of respondents, Section C collected health service-based factors, Section D and E collected data on respondents’ knowledge and practice of wellness seeking behavior respectively. Each part contained the item statements to be responded to. To justify the validity of this study, several steps were taken. First, the use of multistage and simple random sampling provided the study with rich information that enabled to an extent the generalization of findings to wider populations. Second, the data collection methods using modified Health Behavior Lifestyle Profile II and Wellness Behaviors Inventory (WBI) questionnaire ensured excellent results.

In this study, reliability was achieved by measuring consistent results from the respondents. Reliability of data was assured through information collected from relevant respondents with specific attention to proper wording of instructions, logical arrangement of questions that were asked and key issues related to wellness seeking behavior among adults in the study area. In addition, to establish the reliability of the instrument, the split-half method was used. In the split-half method, the total number of items was divided into two halves (odd and even), and a correlation taken between the two halves using a correlation coefficient. A correlation co-efficient of about 0.52 was judged high enough for the instrument to be assumed reliable.

Data from the answered questionnaires in this study were analyzed qualitatively using percentages. All questionnaires were coded before analysis. Data was coded by identifying themes that are related to the research questions and analyzed using descriptive statistics to obtain frequencies and percentages. 50% and above was accepted while below was rejected. The results were presented in tables and chart form. The software used for analysis of the findings was IBM-Statistical Package for Social Sciences (SPSS) Version 21.

RESULTS AND DISCUSSIONS

Results

The study showed that many (64.10%) of the respondents resides in urban than those at rural (35.90%) areas in Abia State while many (57.30%) resides in rural than in urban (42.70%) area in Imo State.

Figure 1: Location of Residence of the Respondents of the study.

Table 1: Varimax-Rotated Factors Militating against Wellness Seeking Behavior among Adults in Abia State

Source: SPSS Results

Note: Factor loading of 0.40 is used at 10% overlapping variance. Variables with factor loadings of less than 0.40 were not used.  **Variables that load in more than one factor were discarded.

Factor 1 = Financial/Cost Related Factor, Factor 2 = Human/ Household Related factors, Factor 3 = Institutional/ Knowledge Related Factors.

Table 2: Varimax-Rotated Factors Militating against Wellness Seeking Behavior among Adults in Imo State

Source: SPSS Results

Note: Factor loading of 0.40 is used at 10% overlapping variance. Variables with factor loadings of less than 0.40 were not used.  **Variables that load in more than one factor were discarded.

Factor 1 = Financial/Cost Related Factor, Factor 2 = Human/ Household Related factors, Factor 3 = Institutional/ Knowledge Related Factors

Table 3: Pooled Results on Varimax-Rotated Factors Militating against Wellness Seeking Behavior among Adults in the Study Area

Source: SPSS Results

Note: Factor loading of 0.40 is used at 10% overlapping variance. Variables with factor loadings of less than 0.40 were not used.  **Variables that load in more than one factor were discarded.

Factor 1 = Financial/Cost Related Factor, Factor 2 = Human/ Household Related factors, Factor 3 = Institutional/ Knowledge Related Factors.

Factors Militating Against Wellness Seeking Behavior among Adults in Abia State

Table 1 presents the varimax-rotated factors militating against wellness seeking behavior among adults in Abia State. Three (3) factors from the results were extracted based on the response of the respondents. Only variables with factor loading of 0.40 and above at 10% overlapping variance were used in naming the factors. Variables that loaded more than one factor as in the case of variables 7, 10, 11, 14 and 17 were discarded while variables that have factor loadings of less than 0.40 were not used for the study. In naming the factors, Okoye et al.(2012) stated that each factor is given a denomination based on the set of variables or characteristics it is composed of. This procedure was adopted in grouping the variables into three major factors as: Factor 1 = Financial/Cost Related, Factor 2 = Human/ Household Related, Factor 3 = Institutional/ Knowledge Related.

For factor 1, the results found financial problem (0.4078) as only financial /cost related factors in the State (Abia), responses on; don’t like modern medicine (0.4830), large family (0.8031), don’t get sick (0.6105), don’t think is necessary (0.4254) and still young (0.6472) were human/household related factors; while insecurity in the country (0.4804), distance to hospital/health facility is far (0.5429), and unaware about wellness seeking behavior (0.6090) were institutional/knowledge related factors militating against wellness seeking behavior among adults in Abia State.

Factors Militating Against Wellness Seeking Behavior among Adults in Imo State

Table 2 presents the varimax-rotated factors militating against wellness seeking behavior among adults in Imo State. Three (3) factors from the results were extracted based on the response of the respondents. Only variables with factor loading of 0.40 and above at 10% overlapping variance as indicated by Ashley et al.(2010) were used in naming the factors. Variables that loaded more than one factor as in the case of variables 4, 9 and 16 were discarded while variables that have factor loadings of less than 0.40 were not used in the study. In naming the factors, Okoye et al., (2012) stated that each factor is given a denomination based on the set of variables or characteristics it is composed of.

For factor 1, the results found financial problem (0.4078) and unavailability of foods/fruits when needed as financial /cost related factors, the human/household related factors found significant were; large family (0.8031), don’t get sick (0.4573) and time constraints for exercise (0.4595) while insecurity in the country (0.4452), bad attitude of the health workers (0.60104) and don’t know what to do (0.7528) were institutional/knowledge related factors militating against wellness seeking behavior among adults in Imo State.

Factors Militating Against Wellness Seeking Behavior among Adults in the Study Area (Pooled Results)

Table 3 presented the pooled results on varimax-rotated factors militating against wellness seeking behavior among adults in the study area.The study showed that generally financial problem (0.6006) was the only factor 1 constraints, don’t like modern medicine (0.7064), large family number (0.7965) and time constraint for exercises (0.4663) were human/household related factors while bad attitude of the health workers (0.4161), distance to hospital/health facility is far (1.4165), don’t think is necessary (0.4071) and don’t know what to do (0.4945) were institutional/knowledge related factors militating against wellness seeking behavior among adults in the study area.

Discussions

The study identified and discussed three factors militating against wellness seeking behavior in the study area as factor 1 = financial/cost related, factor 2 = human/ household related, factor 3 = institutional/ knowledge related.

Financial Related Constraints

The finding of the study reported financial problems (0.4078) as the financial /cost related factors militating against wellness seeking behavior in both States. However, unavailability of foods/fruits when needed was found as a financial/cost related factor only in Imo State. This pointed out the importance and effect of funds on wellness seeking behavior in the study area. A point that was also indicated with the unavailability of foods/fruits when needed in Imo State. Economic resources (such as income and wealth) enable access to material goods and services, including health-care services.

Fund is extremely useful in health seeking behavior as it provides a means of shifting the focus from better to best ways of providing WSB. In relation to the health of individuals there is growing evidence that high levels of fund may have a positive effect on health and WSB. There is also evidence to suggest that participation in WSB practice is fund driven, engendering more active wellness seeking behavior in other contexts. Inappropriate health-seeking behavior was observed among participants from inadequate funding which prevented them from visiting appropriate healthcare facilities for treatment when sick and other WSB resources. Poor attendance to WSB may be a result of poor financial status, quality of care given or taken, health providers attitude and behavior, poor cooperation, and involvement in the treatment process. This finding is also consistent with findings in a study in Nigeria (Ogunlesi and Olanrewaju, 2010), where family socioeconomic status is a predictor of appropriate healthcare-seeking behavior.

Human/household related factors

Not liking modern medicine (0.4830), large family size (0.8031), the belief of not getting sick (0.6105), the thought that WSB is not necessary (0.4254) and the idea of still being young (0.6472) constituted the human/household related factors that militated against WSB in Abia State while large family size (0.8031), the belief of not getting sick (0.4573) and time constraints for exercise (0.4595) were the human and household related constraints militating against WSB in Imo State.  The common factors of large household size and the belief of not getting sick with high mean loads found among the two States under study was an indication of the severity of the constraints against WSB. Other measurements on human/household factors that militated against WSB found in the study such as not liking modern medicine, the thought that WSB is not necessary, the idea of still being young and time constraints for exercise were indications that the respondents did not fully understand the concept and meaning of WSB.For example,the thought that WSB is not necessary can be associated with the belief that taking care of one’s physical, mental, and emotional health is not important or not worth the time and effort. This may lead to less engagement in activities that promote their well-being, such as exercising and eating healthily, which may ultimately lead to negative health outcomes over time.

The study has pointed out clearly that educational programmes are needed to enlighten adults about WSB and what it entails – concepts, benefits, and practice. The link between education and health has different potential explanations. Education as a long-term investment provides an incentive to individuals to stay healthy and reap the benefits of such investment.

Institutional/knowledge related constraints

The study also highlighted the institutional/knowledge related constraints in the study areas as:  insecurity in the country (0.4804), long distance to hospital/health facility (0.5429), and lack of awareness about wellness seeking behavior (0.6090) in Abia State; and insecurity in the country (0.4452), bad attitude of the health workers (0.60104) and not knowing what to do (0.7528) in Imo State with a mean score of 2.50.  In line with the findings on institutional factors, Ambebila et al.(2020) observed that there was limited accessibility to health facilities and low utilization of services provided, even though some of these services may be free or subsidized by the state or its partners. The study found cost of transportation, poor knowledge, and lack of awareness of the services provided and workers related poor attitude because of low accessibility.

This study has demonstrated that the insecurity in the study areas is affecting the utilization of health care services, thereby affecting wellness seeking behavior among adults in the study. When people feel unsafe or threatened, they may prioritize their immediate survival needs over long-term wellness goals, leading to changes in their behavior. Adults may feel insecure to go out to health facilities to seek for treatment even when ill. In addition, hospitals and clinics may be targeted by violence, making it difficult for people to access medical care when they need it. Insecurity in the country may also lead to chronic stress and anxiety among adults in the study which may have been linked to not knowing what to do regarding wellness seeking behavior found as one of the institutional/knowledge related constraint militating against WSB. Chronic stress and anxiety can have negative effects on both mental and physical health as people may be more likely to engage in unhealthy behaviors such as smoking, overeating, or using drugs or alcohol to cope with stress (Ambebila et al., 2020). There is therefore the need to not only provide populations with better education and living standards but also to provide community security to ensure people feel safe to go to health facilities to seek health services when they get ill or need to go for routine check-ups to enhance WSB.

CONCLUSION

This study identified the constraints that militate against wellness seeking behavior among adults in Abia and Imo States Nigeria. The financial constraints that militate against wellness seeking behavior in the study were inadequate fund (for both States); and unavailability of foods/fruits when needed for adults in Imo State only. However, responses such as dislike of modern medicine, large family size, the belief of not getting sick, the thought that WSB is unnecessary and still young to observe WSB were human/household related factors; and insecurity in the country, distance to hospital/health facility and lack of awareness about WSB were the institutional/knowledge constraints commonly militating against wellness seeking behavior among adults in both States. Probably, due to location proximity, the study showed a significant difference between constraints, but no significant difference in the health service-based factors provided by both States on wellness seeking behavior among the adults.

In conclusion, the study established that the client-based factors, provider ¬based factors, caretaker perceptions; social and demographic factors, cost, and social networks work synergistically to produce a pattern of wellness seeking behavior. Hence, though optimal health care is believed to be a priority, many adults in Abia and Imo States preferred not to visit hospital when sick, therefore opting for selfcare practices, translating that high level of knowledge may not implied practices to an extent.  The study areas need to optimize recognition of wellness seeking behaviors, and, via public health initiatives with gender and location inclusiveness, promote health education, prevention, and acceptance of health responsibility to individuals to tackle the growing burden of disease because of neglect of wellness seeking behavior practices.

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