Comparative Analysis of Fresh and Dried Fish Consumption in Ondo State, Nigeria

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1 Comparative Analysis of Fresh and Dried Fish Consumption in Ondo State, Nigeria Mafimisebi, T.E. (Ph.D) Department of Agricultural Business Management School of Agriculture & Natural Resources Mulungushi University Kabwe, Zambia

2 Introduction There is an on-going campaign for increased protein intake in Nigeria to combat widespread protein calorie malnutrition. One way this can be achieved is increased consumption of various fish forms. No empirical research findings to support common assertions in Nigeria that the dried fish form is more widely consumed than the fresh or that urban populace consume more fish than the rural populace. Giving empirical backing to these assertions was the motivation for this study which compared the consumption of fresh and dried fish.

3 Methodology Data, Sampling and Data Collection Primary data were used for this study. Data used were collected from 90 households selected through multi-stage sampling technique. In the first stage, two Local Government Areas (LGAs) Akure North (urban) and Ifedore (rural), were purposively selected.

4 Methodology Data, Sampling and Data Collection In stage two, 2 fish markets were purposively selected in the LGA capital, where respondents, buying fish for household consumption, were sampled. Fifty (50) respondents (25 for dried fish and 25 for fresh fish) per LGA, were targeted for interview by convenience sampling at the purchase point. Of the targeted 100 respondents, 90 (47 from Akure North LGA and 43 from Ifedore LGA) responded to all the questions asked.

5 Analytical Tools Descriptive, Z-test, Chi-square statistics and regression model were used to analyze the data collected. Z-test was used to compare fresh and dried fish consumption in the two LGAs (locations). Chi-square statistics was used to test whether or not there is a significant relationship between the quantities of fish consumed and the households income. Multiple regression analysis was used to determine the effects of postulated independent variables on the dependent variable. Y= f( X 1, X 2,X 3 X 4,X 5, X 6,X 7,, U t )

6 Analytical Tools Where Y = Estimated quantity of fresh/dried fish consumed per household per year X 1 = Household size X 2 = Number of years of formal education of household head/contact person X 3 = Household income (N) X 4 = Age (yrs) of household head/contact person X 5 = Square of the ages of the household head/contact person X 6 = Price (N) per unit of fish form X 7 = Number of children below the age of 15 years U t = Error term

7 Results and Discussion Socio-economic Characteristics of Respondents and Households In the two locations, about 53.0% of the respondents were females while about 47.0% were males. The mean household size was 7 in both households. The average age of household head or major income earner was 47 years in urban and 42 years in rural households. Table 1 reveals this information

8 Results and Discussion TABLE 1: Socio-economic Characteristics of Respondents and Households (Urban & Rural) Age of Respondents Frequency % n=47 Frequency % n= Above

9 Results and Discussion TABLE 1: Socio-economic Characteristics of Respondents and Households (contd) Variable Frequency % n=47 Frequency % n=43 Sex Male Female Marital Status Married Single Divorced Household size Above

10 Results and Discussion TABLE 1: Socio-economic Characteristics of Respondents and Households (contd) Variable Frequency % n=47 Frequency % n=43 Educational Status None Primary Secondary Tertiary Adult education Age of HH/Major Income Earner

11 Results and Discussion TABLE 1: Socio-economic Characteristics of Respondents and Households (contd) Variable Frequency % n=47 Frequency % n=43 Major Occupation of HH/Major Income Earner Trading Civil service Artisanship Farming

12 The average annual household income was N471, ($2,908.6) in urban households and N326, ($2,015.2) in rural households. Table 2: Distribution of Households by Income ANNUAL INCOME URBAN AREA RURAL AREA (N) Number % Number % <100, , , , , , , , , , , , , , , Total

13 Consumption Frequency of Fresh and Dried Fish in Urban and Rural Areas Also, 30.0%, 25.5% and 5.5% of the respondents claimed to be consuming fresh fish once, twice and three times per week, respectively. 41% claimed not consuming fresh fish at all owing mainly to cost and availability. Dried fish consumption was claimed at >3times, 3times and once per week by 56.7%, 33.3% and 10.0% of the respondents.

14 TABLE 3: Consumption Frequency of Fresh and Dried Fish in Urban and Rural Areas Variable n=47 n=43 Fish Form Number of Times Consumed per Week URBAN AREA Number % RURAL AREA Number % Fresh fish None Once twice thrice Total Dried fish Once twice thrice >thrice Total

15 Estimated Quantities of Fresh and Dried Fish Consumed in Urban and Rural Areas Estimated quantity of fresh fish consumed per annum by the households in urban area varied from 7.14kg and 19.71kg while in the rural households, the corresponding value was 6.26kg and 17.18kg. For dried fish, the annual quantity consumed by the urban households ranged from 25.47kg to 68.73kg. The corresponding value for the rural households was 21.69kg and 54.83kg per annum.

16 Test of Significance of Fish Consumption There was no significant difference between dried and fresh fish consumption in the two locations. Variables Mean Value Z-value P-value Akure North LGA (Urban) Ifedore LGA (Rural) Quantity of fresh fish consumed (kg) (ns) Quantity of dried fish consumed (kg) (ns) Expenditure on fresh fish (N) 31,835 26, (ns) Expenditure on dried fish (N) 75,747 62, (ns)

17 The Chi-square results showed that there was significant relationship between the quantities of fresh fish ( , p < 0.05) and dried fish ( , p < 0.05) consumed and household income. Table 5: Result of Chi-Square Analysis Variable Degree of Freedom χ 2 P-value Income (N) and fresh fish consumed (kg) - ---urban Income (N) and fresh fish consumed (kg)-- -rural Income (N) and dried fish consumed (kg)-- urban Income (N) and fresh fish consumed (kg)-- rural ** ** ** **

18 Pooled Regression Result Fresh Fish Age of the household head, square of household heads ages and number of children below 15 years of age were not significant in explaining fish consumption. Household size, income and price of fish were significantly negatively or positively related to the quantity of fresh and dried fish consumed (p < 0.05). The education variable showed a strongly positive influence on the quantity of fresh fish consumed.

19 Table 6: Regression Result of Consumption of Fresh Fish Variable b0 Standard error P- value Constant Household size *** Education *** Household income ** Age Age Price *** Children < 15 years

20 Table 7: Regression Result of Dried Fish Consumption Variable B Standard error Significance Constant Household size ** Education Household income ** Age Age Dried fish price ** Children < 15 years of age

21 Pooled Regression Result--Dried Fish Age of the household head, square of household heads ages and number of children below 15 years of age were not significant in explaining fish consumption. Household size, income and price of fish were significantly negatively or positively related to the quantity of fresh and dried fish consumed (p < 0.05). The education variable, which was significant in fresh fish consumption was not significant here.

22 TABLE 8: Problems Encountered in Fresh Fish Consumption Fish Form Constraints Number of Times Ranked First Percentage Fresh fish Disintegration Affordability Availability Storage/handling Bones Household size Total

23 TABLE 8: Problems Encountered in Dried Fish Consumption Fish Form Constraints Number of Times Ranked First Percentage Dried fish Faulty drying process Putrefaction Affordability Scales on dried fish Seasonality of some species Total

24 Problems Encountered in Fresh and Dried Fish Consumption About 84% of households agreed that there is the need to consume more fish in their households. Also, 67% of households indicated preference for fresh fish over dried fish but rated affordability (50%) and accessibility (27%) as the two strongest factors inhibiting consumption. The two main factors hindering consumption of more dried fish were faulty drying process (37%) and affordability (22.0%). Other factors identified to be negatively affecting fresh and dried fish consumption are shown in Table 8.

25 Conclusion and Recommendations It is concluded that respondents consume more dried than fresh fish in the study area and that there is no significant difference in fish consumption by residents of rural and urban areas in Ondo State It is recommended that demand and or supply-side policies be used to tackle the problem of the high cost of fresh fish to achieve reduced price and make it more affordable. Also, more emphasis on fresh fish in the enlightenment programmes on the importance of fish consumption, needed.