Lifestyles pattern, health-seeking behaviour and body mass index of market traders in Owo, Owo Local Government Area of Ondo State, Nigeria

Bolajoko OO1*, Olanrewaju OI2, Odugbemi BA3
1Nutrition and Dietetics Department, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria.
2Nutrition and Dietetics Department, Rufus Giwa Polytechnic, Owo, Ondo State, Nigeria
3Community Health department, College of Health Technology, Ilese, Ogun State, Nigeria.
*Correspondence: Bolajoko Opeyemi O; +234 703 844 5221; opebolajoko@gmail.com, tunakinshealthcare@gmail.com

Download full article in pdf format

Abstract

Background: Inappropriate health-seeking behaviour (HSB) coupled with a sedentary lifestyle had been shown to complicate health outcomes among market traders in Nigeria. Therefore, this study assessed the lifestyles pattern, HSB and Body Mass Index of market traders in Owo, Owo local government area of Ondo State, Nigeria.
Materials and methods: The study was a descriptive cross-sectional study, which involved 205 traders who were conveniently selected from three major markets in Owo. Information was sourced from participants on medical history, lifestyle patterns, and HSB using a structured, self-administered questionnaire and anthropometric indices. Data were analysed using descriptive statistics and chi-square. In all cases, a probability of P<0.05 was taken to indicates a level of significance.
Results: Findings showed that 44.4% of the traders were males while 55.6% were females, about 28.8% and 24.4% drinks and smoke cigarette, respectively. Similarly, 5.4% and 5.4% were hypertensive and diabetic, respectively. Obesity was found in 12.6% of the study population, of which obese females were statistically (<0.05) higher than their male traders. The prevalent of inappropriate HSB was 36.1%. Self-medication/herbal cure (33.3%) and patent medicine store (33.3%) were the most identified inappropriate health seeking behaviour by the traders.
Conclusion: Appropriate HSB increases with the increase in age of the traders while inappropriate   HSB decreases with an increase in age. A significant difference existed between age (P=0.014), sex (P=0.002), presence of chronic disease (P=0.011), and HSB.

Keywords: Alcohol, Cigarette, Obesity, Inappropriate HSB, Hypertension, Diabetes.
Yen Med J. 2020;2(4):80 – 89.

Cite this article: Bolajoko OO, Olanrewaju OI, Odugbemi BA. Lifestyles pattern, health seeking behaviour and body mass index of market traders in Owo, Owo local government area of Ondo State, Nigeria. Yen Med J. 2020;2(4):80 – 89.

INTRODUCTION

Market traders are a vital part of the agricultural and economic value chain that bridges the gap between farmers or manufacturers and consumers. This occupation involves transacting business from a spot, and traders are either doing their job standing in one position or sitting down all day.1 These habits surely have a significant influence on energy expenditure and may contribute significantly to sedentary lifestyle because some of these traders do not exercise their bodies all day long. Since they work all day, traders have limited to take charge of their health; and the habit of routine medical checks is not common among them. Thus, they indulge in inappropriate HSB, which does not just complicate health but also worsen health outcome.

Health seeking behaviour (HSB) refers to any form of actions or inactions undertaken by people to maintain adequate and prevent ill health, as well as promote a good state of health.2 In other words, HSB is an action taken by individuals with perceived health problems for finding an appropriate solution. For anyone to remedy ill health status a series of remedial actions need to be taken; such an action can either be of help to health or complicate and aggravate the health condition of the individual.

Health is significant for social and economic development; hence, it is seen as a tool for everyday living, and all need it. The relationship between health and human behaviour is a major area of interest in public health. Studies on health-seeking behaviour have shown the numerous influences on an individual’s health behaviour. These influences include past experiences with health services, perception about quality and efficiency of health services, and influences at the community level.3,4 The decision to seek medical help is influenced but not limited to the educational, demographical, gender and economic status of an individual as well as the extent of the symptom of the condition and symptoms duration.5,6

Inappropriate HSB has been found and reported among market traders in Nigeria. For instance, in the south-east part of Nigeria, specifically in Akwa, Anambra state, about 34.2% of the market traders do not seek or patronise the appropriate health services when in need.7 A similar study in Ibarapa central market in Ibadan showed that 43% of the market traders preferred patronising patent medicine shops rather than consulting qualified health workers for medical treatment and about 4% consult herbalist.8 A study conducted in Ile-Ife, Nigeria, on HSB among traders showed that the majority of the respondents relied on self- medication, herbal concoctions, and home rest as their treatment options used during the last illness.9 The consequence of this action has been linked to poor health outcomes in Nigeria.

The market place is an occupational environment that can predispose individuals to obesity, mainly due to the sedentary nature and enhanced access to food.10 Market men and women spend most hours of the day sitting down and are involved in many other sedentary activities, eating foods with mean daily energy intake higher than recommended levels. These conditions increase their risk of developing obesity and other non-communicable diseases.1 Studies have shown that the burden of non-communicable diseases (NCDs) such as hypertension, diabetes, obesity, renal diseases, and cancer is increasing in epidemic proportions in Africa.10,11 World Health Report (2002) revealed that NCDs accounted for 22% of the total deaths in the region in the year 2000; cardiovascular diseases alone accounted for 9.2% of the total deaths, killing even more than malaria. Poor dietary habits and a sedentary lifestyle are some of the predisposing factors to the burden of non-communicable diseases (NCDs), especially in Africa and other regions of the world. Indeed, it has already been projected that up to three-quarters of the world’s hypertensive population will be in economically developing countries by the year 2025.12

A healthy lifestyle is known to include healthy nutritional habits, adequate physical activity, and moderate consumption of alcohol, and avoidance of tobacco abuse. Poor dietary habits and a sedentary lifestyle, excessive weight gain coupled with inappropriate health-seeking behaviour is suicidal.13 The detrimental effect of a sedentary lifestyle and inappropriate HSB has been linked to worsened health outcomes, increased morbidity, and mortality as well as poorer health statistics. Market traders in Nigeria must be assessed and reassessed from time to time to prevent disease and provide public health measures to curbing health emergencies. Therefore, this research aimed to assess the lifestyle pattern, health-seeking behaviour and Body Mass Index (BMI) of Market Traders in Owo, Owo local government Area of Ondo State, Nigeria.

MATERIALS AND METHODS

The study was a descriptive cross-sectional study to investigate the lifestyles pattern, HSB, and BMI of market traders in Owo, Ondo State, Nigeria.

 

The study was carried out in Owo local government area of Ondo State, Nigeria. Owo is one of the first local governments created when Ondo State was created in 1976 from the old western state. The town has six (6) markets within its metropolis. The three markets selected for this study are located one to two kilometres apart from the city centre. The Oba market is an everyday market situated beside the Oba’s palace. In contrast, the Ikoko market is a five (5 days) market located about 500 m away from Oba’s market adjacent to the King palace extension. These two markets are collecting points for food commodities and textile fabrics. Further, the Ijebu market is situated 1 km away from Oba’s palace main gate; it is majorly for the selling and buying of domestic’s animals, birds, and herbal medicine; food commodities can be purchased in the market.

 

The study population consisted of apparently healthy market traders both males and females in Owo Township.

 

The multistage sampling method was used in the selection of markets for the study in Owo Township. Three (3) markets (Ikoko market, Oba’s market, and Ijebu market) were selected using a simple random sampling method. Due to the populations of traders in the markets, the Ikoko market was allotted one hundred and ten (110) questionnaires while the two other markets shared one hundred (100) questionnaires equally. A convenient sampling method was adopted in the selection of participants for the study. One hundred and five (105) questionnaires were retrieved from the participants in the Ikoko market, while the fifty (50) participants were sampled from each Oba’s market and Ijebu market, respectively. In total, 205 participants participated in the study.

 

Inclusion criteria

Healthy males and females market traders in Oba, Ijebu, and Ikoko market in Owo local government who agreed to participate in the study was considered.

Exclusion criteria

Those who did not give consent to the study and those who were ill were excluded from the study

INFORMED CONSENT

Before the survey, permission was obtained from the Nutrition and Dietetics Department of Rufus Giwa Polytechnic, Owo. Verbal consent was sought and obtained for the study from the office of the chairperson, Iyaalaje in Owo local government. Verbal consent from the participant was obtained after the objective of the study was explained to them.

Data Collection

Questionnaire

A structured, self, and interviewer-administered questionnaire was use to obtained data on lifestyle patterns, health-seeking behaviour and demographic characteristics of the market traders. A modified version of Latunji and Akinyemi.11 HSB framework model was used in the design of the questions on HSBs for the study

 

Anthropometric measurements

Weight

The weight of the subjects was measured using a portable bathroom scale (HANSON model), to the nearest 0.1kg with the subjects standing upright on the scale barefooted at shoulder level, arms by the side, and the head straight in line with using standard methods.14,15

 

Height

Standiometer was used to measure the height of the participants with the subject standing erect and barefoot on the height meter with back to the wall and looking straight in a Frankfurt position. The height was taken and recorded to the nearest 0.1 cm.14,15

 

Statistical Analysis

Statistical analysis was performed using the statistical package for social science (SPSS version 20). Descriptive statistics, such as frequencies and percentages were used to analyse demographic characteristics, lifestyle patterns, HSB, and BMI. For the inferential statistics, t-test and Chi-square were employed to determine the relationship. The level of significance was set at p<0.05.

RESULTS

Medical History of the Respondents

Table 1 presents the medical history of the respondents; 205 respondents participated in the study. Female respondents made up more than half (56.6%) of the total population. The result also revealed that roughly one fourth (27.3%) of the market traders were within the age of ≥50 years old. About 30.7% of the respondents have a family history of chronic diseases, of which 38.1% of the respondents have a history of chronic diseases that could be traced to their paternal family and 61.9% traced to their maternal family, and 69.3% do not have a family history of chronic diseases.

 

Table 1: Medical History of the respondents

Variables                                                                           Frequency (205)                 Percentage (%)

Sex

Male                                                                            91                                     44.4

Female                                                                         114                                   55.6

Total                                                                           205                                   100.0

Age (years)

20 –29                                                                         50                                     24.4

30 – 39                                                                          49                                     23.9

40 – 49                                                                          50                                     24.4

>50                                                                              56                                     27.3

Total                                                                            205                                   100.0

Family history of chronic disease

Yes                                                                              63                                     30.7

No                                                                               142                                   69.3

Total                                                                           205                                   100.0

If Yes, Parents with chronic disease

Father/grandfather                                                        24                                      38.1

Mother/grandmother                                                     39                                      61.9

Total                                                                           63                                     100.0

 

 

Lifestyle patterns of the respondents

The majority (71.2%) of the respondent does not take alcohol, while 22.0% engage in alcohol, 75.6% were not smokers, and 15.1% were smokers. Moreover, 80.5% of the respondent does not have any medical condition, about 12.7% have a medical condition at the time of assessment, and 6.8% did not respond to the question. The most prevalent disease condition among the respondent was hypertension and diabetes mellitus, with 5.4% each; 70.2% have time for exercise while 29.3% reported not having time for exercise, and 1.5% did not respond to the question. Walking is the most common type of exercise among respondents with 24.9%, and the least was table tennis (0.5%). Most of the respondents did not respond to the question on time spent during exercise (31.7%), but 30.7% used 1-5hrs during exercise, which was the highest percentage recorded for the time of exercise.

 

 

Table 2a:  Lifestyle patterns of the respondents continued

Variables                                                                       Frequency (205)                            Percentage (%)

Alcohol

Yes                                                                            59                                                28.8

No                                                                             146                                               71.2                

Total                                                                         205                                               100.0

Cigarette

Yes                                                                            50                                                24.4

No                                                                             155                                               75.6                

Total                                                                         205                                              100.0

Medical condition

Yes                                                                           40                                                 19.5

No                                                                                 165                                                   80.5               

Total                                                                        205                                                 100.0 

Disease condition

Hypertension                                                            11                                                 5.4

Diabetes mellitus                                                      11                                                   5.4

Stomach ache                                                           4                                                     2.0

Headache                                                                 5                                                     2.5

Malaria                                                                     5                                                     2.5

Ulcer                                                                        2                                                     1.0

Leg pain                                                                   1                                                     0.5     

Pile                                                                           1                                                     0.5

Absent of disease condition                                       165                                               84.9               

Total                                                                        205                                               100.0

 

Table 2b: Lifestyle of the respondents continued

Variables                                                                     Frequency (205)                               Percentage (%)

Time of exercise

Yes                                                                          144                                                  70.2

No                                                                           58                                                    28.3

No responses                                                           3                                                      1.5

Total                                                                       205                                                  100.0

Kinds of exercise

Dancing                                                                 5                                                     2.4

Sit up                                                                     12                                                   5.4

Jumping                                                                       10                                                   4.9

Running                                                                11                                                   5.4

Walking                                                                 101                                                 49.3

Press up                                                                  6                                                     3.0

No exercise                                                             60                                                   29.3    

Total                                                                      205                                                  100.0

Minutes spent for exercise

< 20mins

30-40mins

40-50mins

1-5hrs 

Not specified   

Total

 

   63

   52

   6

   9

  15

  145

 

          43.4

          35.9

          4.1

          6.2

          10.3

          100.0

 

 

Body mass index of the Respondents

The BMI of the respondents is presented in Table 3. This study found that only (19.6%) of the entire study population were underweight. Nearly half (52.4%) were within the normal BMI range, and nearly one third (27.3%) of the participants were found to be overweight while about (12.7%) were obese.  Female participants were more obese and statistically significant (p<0.05).

 

Table 3: Body mass index of the Respondents

Anthropometrics parameters

Male

Female

Total

X2

P-value

Body Mass Index

 

 

 

 

 

<18.5 (underweight)

13(14.3)

9(7.9)

22(19.6)

16.895

0.031*

18.5 – 24.9 (Normal)

50(54.9)

57(57.0)

107(52.4)

 

 

25-29.9 (Overweight)

21(23.1)

35(30.7)

56(27.3)

 

 

30-34.9 (Obesity class1)

7(6.6)

13(11.4)

26(12.7)

 

 

Total

91 (100.0)

114(100.0)

205(100.0)

 

 

*Significant at P<0.05)

 

Health Seeking Behaviour of the respondents

The table below represents the HSB practiced by the respondents; 63.9% of the respondents practiced appropriate HSB, while 36.1% of the market traders practice inappropriate HSB. Federal Medical Centre, Owo (35.1%), and Pharmacy Shop (30.5%) were the most visited place for seeking health among the market traders. The general hospital and PHC centres were the least visited. Patronage of patient medicine store 33.8%, followed by self-treatment/ herbal cure and a visit to traditional healers with 23.0% and 20.3%, respectively. Faith Healing amount to about 15.6%, of which 22.7% and 10.0% were female and male market traders, respectively.

 

 

Table 4: HSB of the respondents                                                                     

HSB characteristic

Male (%)

Female (%)

Total (%)

Appropriate health seeking  behaviour

(n=61)

(n=70)

(n=131)

Federal Medical Centre, Owo

25(41.0)

21 (30.0)

46 (35.1)

General Hospital, Owo

6(9.8)

4 (5.7)

10 (7.6)

Primary Health Care Centre’s

5(8.2)

5 (7.1)

10 (7.6)

Pharmacy Shop

15(24.5)

25 (35.7)

40 (30.5)

Private Hospital

10(16.4)

15 (21.4)

25 (19.1)

Total

61(100.0)

70(100.0)

131(100.0)

Inappropriate health Seeking  Behaviour

(n=30)

(n=44)

(n=74)

Self-Treatment/ herbal cure

10(33.3)

7 (15.9)

17 (23.0)

Traditional Healer

5(16.7)

10 (22.7)

15 (20.3)

Patient Medicine Store

10(33.3)

15 (34.1)

25 (33.8)

Faith Healing House

3(10.0)

10 (22.7)

13 (15.6)

No Action 

2(6.7)

2 (4.5)

4 (5.4)

Total

30(100.0)

44(100.0)

74(100.0)

*Significant at P<0.05) Latunji and Akinyemi, 2008

 

Relationship between Sex, Age, chronic disease and HSB practice by the respondents

Table 4 below shows that about 46.5% of the male participants adopted appropriate HSB; this was lower than that of their female counterparts with 53.5%. Likewise, inappropriate HSB was higher and statistically significantly (P<0.05) among the female than the male traders. While appropriate HSB increased with age (P<0.05). Further, 19.5% of the market traders were suffering from chronic diseases. Hypertension (27.5%) and diabetes mellitus (27.5%) were the highest chronic diseases observed among the traders. Inappropriate HSB were found among hypertensive (27.8%) and Diabetic (16.7%) respondents.

 

 

Table 5: Relationship between Sex, Age and present of chronic disease and health-seeking behaviour practice by the respondents

HSB characteristic

AHSC (%)

INAHSC (%)

Total (%)

P-value

Sex

Male

Female

Total

 

61(46.5)

70(53.5)

131(100.0)

 

30(40.5)

44(59.5)

74(100.0)

 

91(44.4)

114(55.6)

205(100.0)

 

0.014*

 

Age (years)

20-29

30-39

40-49

50 and above

Total

 

25 (19.1)

29 (22.1)

35 (26.7)

42 (32.1)

131(100.0)

 

25 (33.8)

20 (27.0)

15 (20.2)

14 (18.9)

74(100.0)

 

50 (24.4)

49(23.9)

50 (24.4)

56(27.3)

205(100.0)

 

0.002*

Presence of chronic diseases

Yes

No

Total

 

22 (16.8)

109(83.2)

131(100.0)

 

18(24.3)

56 (75.7)

74 (100.0)

 

19.5

80.5

205(100.0)

 

0.011*

If yes, which condition (n=40)

Hypertension

Diabetes

Stomach ache

Headache

Malaria

Ulcer

Leg Pain

Pile

Total

 

6 (27.2)

8 (36.4)

2 (9.1)

2 (9.1)

3 (13.6)

1 (4.5)

0 (0.0)

0 (0.0)

22 (100.0)

 

5 (27.8)

3 (16.7)

2 (11.1)

3 (16.7)

2 (11.1)

1 (5.6)

1 (5.6)

1 (5.6)

18 (100.0)

 

11(27.5)

11(27.5)

4(10.0)

5(12.5)

5(12.5)

2(5.0)

1(2.5)

1(2.5)

40 (100.0)

 

0.131

*Significant at P<0.05) AHSB- appropriate HSBs, IAHSC– inappropriate HSBs

 

DISCUSSION

Medical History and Lifestyle patterns of the Respondents

A healthy lifestyle is known to include nutrition, adequate physical activity, and avoidance of tobacco abuse. In this study, one-third of the market traders reported a family history of chronic diseases. The value in this report was lower than the value (56.2%) obtained by Olanrewaju et al among health workers in Jos University Teaching Hospital. The high number observed among the health workers may be due to the size of the study.16 More than 300 participants participated in the study, which is higher than the number of participants in this study.  Though, the majority of the study participants (89.7%) did not suffer from chronic disease as at the time the study was conducted. The market activities revealed that the traders woke up quite early to prepare for the market. The early wake-up time of these traders may not be unconnected with the fact that some of them have to prepare their children for school and probably prepare meals for them. Although, some equally reported walking around in the market is a form of exercise for them. Walking is a prominent form of exercise among traders. Again, walking activities of the women may not necessarily be in the form of vigorous physical activity that could lead to weight loss.

The fact that most of the respondents perceived their activity level and market activities to be physically active and very stressful might be linked to either ineffective management of time or lack of sleep during the day (siesta). The result of this study reveals that the majority of the market traders had not used alcohol in the past year, and only about 29.8% were drinkers. The lower rate of alcohol use reported among market traders may have resulted from their knowledge of the negative consequences of alcohol; hence, caution in the use of alcohol. People who abuse alcohol are prone to occupational and other health problems that make them vulnerable to developing psychological distress.17,18

Body mass index of the Respondents

  1. The rates of Overweight/Obesity as determined BMI was 39.9%. Overweight/Obesity is defined as abnormal or excessive fat accumulation that may impair health. It does express not only the degree of excess fat but also fat distribution in the body, which determines the health risk associated with excessive weight gain.19 The rate of obesity reported in this study was lower than 69% reported among a group of market traders in Abeokuta (Mebude AS. Prevalence of obesity among market women in Abeokuta, Unpublished BSc Thesis. University of Agriculture, Abeokuta, 2010) but higher than 16.3% reported among female traders in Ibadan.20 A contributing factor to overweight/Obesity may be attributed to the fact that the study location is an urban centre where there is a high intake of the western diet, and changes in local dietary patterns due to urbanization are common.21,22 Sedentary lifestyle seen among the traders could be responsible for overweight and obesity. Overweight and obesity is a risk for cardio-metabolic diseases.23

 

HSB of the respondents

HSB has been explored in many international studies, and its significant correlates included the physical, demographic, socioeconomic, and cultural factors and the organization of the health care system.24,25 The HSB of market traders in the study was remarkably better than that of the rural dwellers in Ekiti state.26,27 and among pulmonary tuberculosis patients in rural Nigeria.28 In this study, HSB by the respondents shows that more than half (63.9%) of the market traders seek appropriate health. This value was similar to the study conducted by Latunji and Akinyemi among civil servant in Ibadan where 63.1% were found to seek appropriate health care but was lower than the reported (72.3%) among household heads in Dale Woreda, Sidama Zone, Southern Ethiopia.11,29  The total number of respondents who don’t seek appropriate health facility in the study tripled the number (12.3%) who did not seek health service from a modern health facility in Tanzania, similar to the report of Latunji and Akinyemi, but was higher than the 27.7% reported by Fikre et al.11,29 This might not be far-fetched from the differences in the data collection method, study population, and location of study. This study was conducted among market traders with a higher sample size.

 

This study revealed that a patent medicine store, self- treatment/ herbal cure, and a visit to a traditional healer were more sought after than faith healing among the participants. A similar situation was also found among traders in Osun State.2 Patronage of patent medicine store among the market traders was higher than 12.9% found among traders in Osun state has reported by Akintaro.2 A concern about these patent drug dealers is that they are often untrained and perpetuates the vicious circle of counterfeit drugs and death. Lack of dosage for herbal medicine coupled with the unapproved medical diagnosis is also a risk for death and more dangerous than the disease itself.

 

Inappropriate HSB was seen among female traders in this study. This might be because women sometimes shoulder more family responsibilities and experienced severe socioeconomic hardships, which prevented them from visiting appropriate healthcare facilities for their illnesses. This is contrary to the findings by Latunji and Akinyemi in Ibadan, Nigeria, and Manzi et al in Rwanda.7,30 The trending factors in the HSB, as seen in this study, are gender, age, and nature of the illness.

 

This study found a significant difference in HSB between men and women traders. Female traders adopted an appropriate HSB more than their male counterparts, contrary to the study of Latunji and Akinyemi,11 where male respondents take more responsibility for appropriate HSB. Inappropriate HSB was higher among the female than the male traders, and this is statistically significant (P<0.05). This could be linked to the unequal number of male and female traders who participated in the study. The study also showed that older people are significantly more likely to seek appropriate health care than resulting in self-medication, such as a visit to a traditional healer and religious homes. Appropriate HSB increases with the age of the traders; inappropriate HSB decreases with age and is significant (P<0.05).

 

Chronic diseases are diseases that are long-standing in its effects, and there are some of them which can be hereditary, such include cardiovascular and metabolic diseases. Hypertension and diabetes mellitus were the highest chronic diseases identified among the traders. Hypertensive and diabetic respondents practiced inappropriate HSB. This action would not just complicate the management of these diseases but may also lead to an untimely death. Proper medical diagnosis and treatment can only be achieved for people with diabetes and hypertensive individual in an appropriate health facility. Inappropriate HSB could worsen the health situation and increase the number of casualties from these disease conditions.

 

CONCLUSION

This study found a high prevalence of alcohol consumption, cigarette smoking, and lack of exercise was observed among the traders while walking was the dominating exercise among the market traders. Overweight/obesity was also rampant. This was more pronounced among female marketers than their male counterparts. The patronage of inappropriate HSB common as one-third of the study population was found seeking health in the wrong direction. This was more pronounced among female marketers than their male counterparts. The study also confirmed that hypertension and diabetes were the leading chronic diseases among traders.

 

RECOMMENDATION

There is an urgent need to intensify health education particularly about the danger of sedentary lifestyles, self-medication and patronage of patent drug dealers.  Concerted efforts involving all stakeholders should be made to ensure that the activities of patent drug dealers are thoroughly monitored

ACKNOWLEDGMENT

Sincere appreciation goes to the Iyaalaje General of Owo local government area of Ondo state, who coordinated the markets Iyaalajes in each market to give their maximum support for the success of the study 

DECLARATION OF CONFLICT OF INTEREST

The authors declared no conflicts of interest. The authors alone are responsible for the design, data collection, writing, and funding of this research.

REFERENCES

  1. Food and Agriculture Organization of the United Nations and Practical Action Publishing. Smallholder Agriculture and Market Participation, 2017. http://www.fao.org/3/a-i7841e.pdf. Accessed September 4, 2020.
  2. Akintaro O.A. Health Seeking Behaviours as Predictors of Hypertension among Traders in Osun State, Nigeria. Huria J. 2015;20:73-80.
  3. Sule SS, Ijadunola KT, Onayade AA, Fatusi AO, Soetan RO, Connell FA. A study on the utilization of primary health care facilities in a rural community. Niger J. Med. 2008;17(1):98-106.
  4. MacKian S. Complex cultures: rereading the story between health and social capital. Crit Soc Policy. 2002;18(2):215-226.
  5. Amaghionyeodiwe LA. Determinants of the choice of health care provider in Nigeria. Health Care Manag Sci. 2008;11(3):215-227.
  6. Katung PY. Socioeconomic factors responsible for poor utilisation of the primary health care services in a rural community in Nigeria. Niger J Med. 2001;10(1):28-29.
  7. Oguizu AD, Utah-Iheanyichukwu C, Ibejide. Prevalence of Hypertension among Adult Traders in Some Selected Markets in Awka, Awka-South Local Government Area, Anambra State, Nigeria. Acta Sci Nutri Health. 2019;3(6):142-149.
  8. Ige C, Nwachukwu C. Health Care Seeking Behaviour Among Market Traders in Ibarapa Central Local Government, Nigeria. The Inter J Health. 2008;9(2):1-5.
  9. Onwujekwe OE, Uzochukwu BC. Socioeconomic differences and health seeking behaviour for the diagnosis and treatment of malaria. Malaria J. 2008;8(7):5.
  10. Afolabi, W.A. Addo, A. A. and Sonibare, M.A. Activity pattern, energy intake and obesity among Nigerian urban market women. Int. J. Food Sci. Nutr. 2004;55(2):85-90.
  11. Latunji, O.O and Akinyemi, O.O. Factors Influencing Health-seeking behaviour among civil servants in Ibadan, Nigeria. Ann Ib Postgrad Med. 2018;16(1):52-60.
  12. Kearney PM, Whelton M, Reynolds K, Muntner P, Whelton PK, He J. Global burden of hypertension: analysis of worldwide data. Lancet. 2005;365(9455):217-223.
  13. Olanrewaju OI, Oladapo AA, Dele-Olawumi B, Odunuga BA. Lifestyles patterns and Anthropometric indices of staff in Jos University Teaching Hospital, Jos, Nigeria. Adv Med Dent Health Sci. 2020;3(1):7-14.
  14. World Health Organization. Physical status: The use and interpretation of anthropometry. WHO Technical Report Series 854, p. 1995:375-409. Available from: https://apps.who.int/iris/bitstream/handle/10665/37003/WHO_TRS_854.pdf;jsessionid=C4BE53E7E201D863FAA59AAB45DE8A6F?sequence=1. Accessed September 3, 2020.
  15. World Health Organization. Waist Circumference and Waist – Hip Ratio: Report of a WHO Expert Consultation, Geneva, 8-11 December, 2008. p. 1-39. Available from: https://apps.who.int/iris/bitstream/handle/10665/44583/9789241501491_eng.pdf?ua=1. Accessed September 3, 2020.
  1. Olanrewaju OI, Olaitan OO, Alaba JO. Blood Pressure pattern, Nutritional Status and Stress Assessment of health workers in Jos University Teaching Hospital, Jos. Proceedings of the Nutrition Society of Nigeria. 2019:109-111.
  2. Rosta J, Gerber A. Excessive working hours and health complaints among hospital physicians: a study based on a national sample of hospital physicians in Germany. Ger Med Sci. 2007;5:Doc0
  3. Lucas N, Windsor TD, Caldwell TM, Rodgers B. Psychological distress in non-drinkers: Associations with previous heavy drinking and current social relationships. 2010;45:95–102.
  4. Ogunjimi L, Ikorok MM, Olayinka Y. Prevalence of obesity among Nigerian nurses: The Akwa Ibom State experience. Inter NGO J. 2010;5(2):45-9.
  5. Balogun MO, Owoaje ET. Work condition and health problems of female traders in Ibadan, Nigeria. African J Med Sci. 2007;36(1):57-63.
  6. World Health Organization. A global brief on hypertension: silent killer, global public health crises (World Health Day 2013). Geneva: WHO; 2013. Available from: http://apps.who.int/iris/bitstream/10665/79059/1/WHO_DCO_WHD_2013.2_eng.pdf. Accessed September 3, 2020.
  1. Popkin BM. The shift in stages of the nutrition transition in the developing world differs from past experience. Public health Nutr. 2002;5(1A):205-214.
  2. Ellulu SM, Ismail P, Huzwah K, Asmah R, Yehia A. Obesity and inflammation; the linking mechanisms and the complications. Arch Med Sci. 2017;13(4):851-863.
  3. Russell S. Treatment-seeking behaviour in urban Sri Lanka: trusting the state, trusting private providers. Soc Sci Med. 2005;61(7):1396-1407.
  4. Ali F, Sami F, Rehman H, Haider K. Relation of gender education and health seeking behaviour of the general population regarding psychiatric illness. J Pakistan Med Assoc. 2006;56(9):421-422.
  5. Omotoso D. Health seeking behaviour among the rural dwellers in Ekiti State, Nigeria. Afri Res Rev. 2010;4(2):125-138.
  6. Iyalomhe GBS, Iyalomhe SI. Health-Seeking Behavior of Rural Dwellers in Southern Nigeria: Implications for Healthcare Professionals. Int J Trop Dis Health. 2012;2(2):62-71.
  7. Ukwaja KN, Alobu I, Nweke CO, Onyenwe EC. Healthcare-seeking behaviour, treatment delays and its determinants among pulmonary tuberculosis patients in rural Nigeria: a cross-sectional study. BMC Health Serv Res. 2013;13(1):25.
  8. Fikre B, Samuel D, Zinabu D, Fessahaye A, Fasil T (2018). Assessment of Health Care Seeking Behavior among House HoldHeads in Dale Woreda, Sidama Zone, Southern Ethiopia, Ethiopia. Glob J Med Res Dis. 2018;18(1):19-29.
  9. Manzi A, Munyaneza F, Mujawase F. Assessing predictors of delayed antenatal care visits in Rwanda: a secondary analysis of Rwanda demographic and health survey 2010. BMC Pregnancy Childbirth. 2014;14(1):290.
× Chat