Socio-Economic Characteristics of Traditional Fish Processors in Lagos State, Nigeria

Autor: O B Oyewole, H A Oyedele, Adeyeye S.A.O., A M Omemu, S O Adeogun, A O Obadina
Rok vydání: 2016
Předmět:
Zdroj: International Journal of Aquaculture.
ISSN: 1927-5773
Popis: The study examined the socio-economic characteristics, income and expenditure pattern among traditional fish processors in twenty different fish processing centres in Lagos State, Nigeria. Data were collected through field observation and administration of structured questionnaire. A total of 200 questionnaires were administered through purposive sampling method at 10 respondents/processing centre. Analytical technique used was descriptive statistics. Results revealed that using age and educational level of the processors and availability of household amenities as proxies for socio-economic status, it showed that most of the households were relatively poor. 55.5% were old women and 44.5% were young women. 51.5% had primary school education, 38% had post-primary school education while 10.5% had no schooling. The study found that 98.0% of the processors practiced manual operations while 2.0% practiced mechanical operation. Fish processors in fishing communities play a central role in fisheries and in maintaining the social family structure. Despite the fact that fish and fish products provide significant proportion of the supply of animal protein needs, the fish processors experience seasonal food crisis, particularly the poor women. It is obvious that with seasonal variation in production, fish processors household spend more income on food and increases level of poverty incidence. Seasonal variations in fish supply thereby, leads to serious economic, nutritional and poverty consequences. The study concluded that considering the importance of fish processing to food security and poverty alleviation, especially to coastal communities, a multi-dimensional approach is required to achieve considerable improvement in the living standards of the poor fish processors.
Databáze: OpenAIRE