The content of this publication does not necessarily reflect the opinion of. FAO ...... survai ini akan dimanfaatkan pem
FISH AND ANIMAL PROTEIN CONSUMPTION AND AVAILABILITY IN TIMOR-LESTE
National Directorate of Fisheries and Aquaculture Ministry of Agriculture and Fisheries Supported by the Regional Fisheries Livelihoods Programme for South and Southeast Asia Timor-Leste 2011
REGIONAL FISHERIES LIVELIHOODS PROGRAMME FOR SOUTH AND SOUTHEAST ASIA (RFLP)
FISH AND ANIMAL PROTEIN CONSUMPTION AND AVAILABILITY IN TIMOR-LESTE (Activity Code 1.2.3; 2010-2011 work plan)
For the Regional Fisheries Livelihoods Programme for South and Southeast Asia
Prepared by AMSAT INTERNATIONAL
June 2011
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Disclaimer and copyright “This publication has been made with the financial support of the Spanish Agency of International Cooperation for Development (AECID) through an FAO trust-fund project, the Regional Fisheries Livelihoods Programme (RFLP) for South and Southeast Asia. The content of this publication does not necessarily reflect the opinion of FAO, AECID, or RFLP.” All rights reserved. Reproduction and dissemination of material in this information product for educational and other non-commercial purposes are authorized without any prior written permission from the copyright holders provided the source is fully acknowledged. Reproduction of material in this information product for resale or other commercial purposes is prohibited without written permission of the copyright holders. Applications for such permission should be addressed to: Chief Electronic Publishing Policy and Support Branch Communication Division FAO Viale delle Terme di Caracalla, 00153 Rome, Italy or by e-mail to:
[email protected] © FAO 2011 Bibliographic reference For bibliographic purposes, please reference this publication as: AMSAT International (2011). Fish and animal protein consumption and availability in Timor-Leste. Regional Fisheries Livelihoods Programme for South and Southeast Asia (GCP/RAS/237/SPA) Field Project Document 2011/TIM/02.
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TABLE OF CONTENTS ACKNOWLEDGMENT .................................................................................................................... 10 EXECUTIVE SUMMARY ................................................................................................................ 11 1
INTRODUCTION ........................................................................................................................ 13 1.1 BACKGROUND ......................................................................................................................... 13 1.2 OBJECTIVE ............................................................................................................................... 13 1.3 SURVEY LOCATIONS ................................................................................................................ 13 1.4 OUTPUT ................................................................................................................................... 14 1.5 STRUCTURE OF THE REPORT .................................................................................................... 14
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METHODOLOGY ....................................................................................................................... 15 2.1 QUANTITATIVE SURVEY .......................................................................................................... 15 2.1.1 Selection of respondents .................................................................................................. 15 2.1.2 Sampling design ............................................................................................................... 16 2.1.3 Survey constraints in Oecussi .......................................................................................... 17 2.1.4 Respondents and their households ................................................................................... 17 2.1.5 Weightings........................................................................................................................ 18 2.1.6 Coastal, non-coastal and urban categories ..................................................................... 18 2.2 QUALITATIVE .......................................................................................................................... 19 2.3 ENUMERATORS ........................................................................................................................ 20 2.4 QUESTIONNAIRE ...................................................................................................................... 21 2.5 DATA ANALYSIS OF THE COLLECTIVE RESULT RELATED TO OECUSSI DISTRICT ..................... 21
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DEMOGRAPHIC PROFILE ...................................................................................................... 22 3.1 POPULATION PROFILE .............................................................................................................. 22 3.2 AGE DISTRIBUTION .................................................................................................................. 22 3.3 MARITAL STATUS .................................................................................................................... 23 3.4 HOUSEHOLD SIZE ..................................................................................................................... 24 3.5 GENDER DISTRIBUTION OF POPULATION ................................................................................. 26 3.6 RELIGION ................................................................................................................................. 28 3.7 EDUCATION LEVEL .................................................................................................................. 28 3.8 OCCUPATION ........................................................................................................................... 31 3.9 OWNERSHIP OF CATTLE, BOATS AND GOODS .......................................................................... 33 3.10 MONTHLY INCOME ................................................................................................................ 34
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ANIMAL MEAT OR FISH CONSUMPTION IN TIMOR-LESTE ....................................... 38 4.1 HOUSEHOLD CONSUMPTION BEHAVIOUR ................................................................................ 38 4.2 FREQUENCY OF MEAT OR FISH CONSUMPTION ........................................................................ 39 4.3 TYPES OF PROTEIN CONSUMED ................................................................................................ 43 4.4 TYPES OF FISH/SEAFOOD USUALLY CONSUMED ...................................................................... 44 4.5 COOKING PREFERENCES FOR FISH/SEAFOOD ........................................................................... 46 4.6 REASONS FOR CONSUMING FISH/SEAFOOD .............................................................................. 47 4.7 REASONS FOR NOT CONSUMING FISH/SEAFOOD ...................................................................... 49 4.8 SOURCES OF FISH/SEAFOOD ..................................................................................................... 52 4.9 DISTANCE FROM SOURCES OF FISH/SEAFOOD.......................................................................... 53 4.10 PERCEIVED EASE OF ACCESS TO FISH/SEAFOOD .................................................................... 56 4.11 FISH BUYING VOLUME ........................................................................................................... 57 4.12 FREQUENCY OF BUYING FISH ................................................................................................ 59
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4.13 CONSUMPTION OF PROCESSED FISH....................................................................................... 61 4.14 FISH AND ANIMAL MEAT CONSUMPTION ............................................................................... 63 4.14.1 Frequency of annual consumption per year .................................................................. 63 4.14.2 Weight of consumption per meal .................................................................................... 63 4.14.3 Final calculation of consumption per capita per year ................................................... 64 4.14.4 Average consumption ..................................................................................................... 64 4.14.5 Consumption by area ..................................................................................................... 66 4.14.6 Consumption by district ................................................................................................. 66 4.14.7 Fish and meat consumption by age ................................................................................ 67 4.14.8 Fish and meat consumption by marital status ............................................................... 68 4.14.9 Fish and meat consumption by level of education ......................................................... 69 4.14.10 Fish and meat consumption by level of income and family size .................................. 70 4.14.11 Meat consumption versus ownership of cattle and chicken ......................................... 71 4.14.12 Meat/fish consumption against reported preferences .................................................. 72 4.14.13 Fish supply and fish consumption ................................................................................ 72 4.15 PERCEIVED LEVEL OF CONSUMPTION .................................................................................... 73 4.16 SEASONAL AVAILABILITY OF FISH ........................................................................................ 75 5
CONCLUSIONS AND RECOMMENDATIONS ..................................................................... 76 5.1 CONCLUSIONS ......................................................................................................................... 76 5.2 RECOMMENDATIONS ............................................................................................................... 78
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REFERENCES ............................................................................................................................. 80
APPENDIX 1. QUESTIONNAIRE .................................................................................................. 81 APPENDIX 2. LIST OF SURVEYED ALDEIAS (VILLAGES) ................................................ 112 APPENDIX 3. RESULTS OF FISH AND MEAT CONSUMPTION LEVELS ........................ 115 APPENDIX 4. FINDINGS OF FGD’S AND IDI’S IN 5 DISTRICTS ........................................ 118
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LIST OF FIGURES Figure 1-1. 5 districts in Timor-Leste as target survey area (map source: United Nations 2008) ................................................................................................................................ 14 Figure 2-1. Sample distribution (%) ....................................................................................... 16 Figure 3-1. Age distribution of respondents ........................................................................... 22 Figure 3-2. Age distribution of respondents by district .......................................................... 23 Figure 3-3. Age distribution by urban-coastal categorisation ................................................. 23 Figure 3-4. Marital status of respondents. .............................................................................. 24 Figure 3-5. Marriage status of respondents by district ........................................................... 24 Figure 3-6. Percentage of respondents by household size (N = 820) ..................................... 25 Figure 3-7. Distribution of household size by total (left) and by district (right) ..................... 25 Figure 3-8. Household size of respondents based on urban-coastal-non-coastal categorisation .......................................................................................................................................... 26 Figure 3-9. Age distribution of population by gender and by district .................................... 26 Figure 3-10. Percentage of schooling experience (N = 820) .................................................. 29 Figure 3-11. Level of education (N = 820) ............................................................................. 29 Figure 3-12. School experience of respondents by district ..................................................... 29 Figure 3-13. School experience of respondents by urban-coastal categorisation (excluding Oecussi)............................................................................................................................ 30 Figure 3-14. Completion of school education......................................................................... 30 Figure 3-15. Percentage of drop-out status of respondents in the past ................................... 31 Figure 3-16. Percentage of work force (N = 820) ................................................................... 31 Figure 3-17. Ownership of goods, cattle and boats ................................................................. 33 Figure 3-18. Ownership of assets by district .......................................................................... 34 Figure 3-19. Respondents worked for money a month before the survey (by district) .......... 35 Figure 3-20. Respondents worked for money a month before the survey (by urban - coastal) .......................................................................................................................................... 35 Figure 3-21. Monthly income (USD), by district ................................................................... 35 Figure 3-22. Income level groups versus type of main job..................................................... 36 Figure 3-23. Average income groups by district .................................................................... 36 Figure 3-24. Average income groups by urban-coastal categorization .................................. 37 Figure 4-1. The way family members eat fish or seafood ...................................................... 38 Figure 4-2. Part of fish eaten by male and female members in the household ....................... 39 Figure 4-3. Part of fish eaten by age of respondent ................................................................ 39 Figure 4-4. When people have meal with fish or meat (by district and by urban-coastal) ..... 40 Figure 4-5. Frequency of consumption of meat/fish protein .................................................. 41 Figure 4-6. Past frequency of eating meat/fish by district (percent)....................................... 41 Figure 4-7. Frequency of animal protein consumption by area .............................................. 42 Figure 4-8. Frequency of animal protein consumption (by district) ....................................... 42 Figure 4-9. Types of animal protein consumed (by district) .................................................. 44 Figure 4-10. Species of fish/seafood consumed (% by area) .................................................. 46 Figure 4-11. Methods of preparing fish/seafood (by district) ................................................. 47
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Figure 4-12. Methods of preparing fish/seafood (by area) ..................................................... 47 Figure 4-13. What do you like about fish? (percentages based on all respondents = 100%) . 48 Figure 4-14. Reasons for consuming fish/seafood (%, by district)......................................... 48 Figure 4-15. Reasons for consuming fish/seafood (%, by area) ............................................. 49 Figure 4-16. What is disliked about fish (percentages based on all respondents = 100%)..... 49 Figure 4-17. What is disliked about fish (by urban-coastal) ................................................... 50 Figure 4-18. Reasons limiting consumption of fish/seafood .................................................. 51 Figure 4-19. Reasons for not eating fish or seafood (by urban-coastal) ................................. 51 Figure 4-20. Sources of fish/seafood (by district) .................................................................. 52 Figure 4-21. Sources of fish/seafood (by area) ....................................................................... 53 Figure 4-22. Distance/access to fish/seafood (by district) ...................................................... 54 Figure 4-23. Distance/access to salt water fish/seafood (by area) .......................................... 54 Figure 4-24. Availability of fish/seafood at the market the respondent goes to (by district) . 55 Figure 4-25. Availability of fish/seafood at the market the respondent goes to (by urbancoastal) ............................................................................................................................. 56 Figure 4-26. Perceptions of ease/difficulty of access to fish/seafood (by district) ................. 56 Figure 4-27. Perceptions of ease/difficulty of access to fish/seafood (by area) ..................... 57 Figure 4-28. Volume of fish/seafood bought .......................................................................... 58 Figure 4-29. Volume bought (kg) everytime buying fish ....................................................... 58 Figure 4-30. Frequency of buying fish in general (percent) ................................................... 59 Figure 4-31. Frequency of buying fish by district .................................................................. 59 Figure 4-32. Frequency of buying fish/seafood by area ......................................................... 60 Figure 4-33. Frequency of buying fish/seafood with their weight.......................................... 60 Figure 4-34. Experience in buying processed fish/seafood .................................................... 61 Figure 4-35. Processed fish/seafood bought (by urban-coastal) ............................................. 62 Figure 4-36. Frequency of buying processed fish/seafood (by type)...................................... 62 Figure 4-37. Per-capita level of consumption of protein sources in 4 districts ...................... 65 Figure 4-38. Fish and animal meat consumption level (by urban-coastal) ............................. 66 Figure 4-39. Fish and animal meat consumption level (by district) ....................................... 67 Figure 4-40. Fish and meat consumption (g) by respondent's age .......................................... 68 Figure 4-41. Fish and meat consumption level (g) by marital status. ..................................... 69 Figure 4-42. Level of fish and meat consumption based on education level .......................... 69 Figure 4-43. Level of fish and meat consumption categorised by income level .................... 70 Figure 4-44. Fish and meat consumption level categorised by household size ...................... 71 Figure 4-45. Fish and meat consumed against livestock owned ............................................. 71 Figure 4-46. Levels of fish and meat consumption categorised by what was mostly consumed .......................................................................................................................................... 72 Figure4-47. Fish supplyand consumption ............................................................................... 73 Figure 4-48. Perception on the quantity of fish consumed ..................................................... 74 Figure 4-49. Willingness to consume more fish if having more money ................................. 74 Figure 4-50. Fishing calendar 5 districts (source: RFLP Baseline Survey data, 2011) .......... 75
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LIST OF TABLES Table 0-1. Per-capita consumption of fish and meat by urban-coastal categorisation and by district .............................................................................................................................. 12 Table 2-1. Weight scores for district sampling ....................................................................... 18 Table 2-2. Locations and participants of FGDs and IDIs ....................................................... 19 Table 3-1. Population Profile (Census 2010) .......................................................................... 22 Table 3-2. Average household size by district (survey result and census) ............................. 25 Table 3-3. Gender comparison of population by age group and by district ........................... 27 Table 3-4. Distribution of gender in the sample ..................................................................... 27 Table 3-5. Meat or fish consumed grouped by religion of respondents ................................. 28 Table 3-6. Main job/occupation in respondent’s household (N = 528) .................................. 31 Table 3-7. Distribution of jobs in districts .............................................................................. 32 Table 4-1. Type of meal consumed......................................................................................... 43 Table 4-2. Type of animal protein consumed (urban, coastal and non-coastal areas) ............ 43 Table 4-3. Species of fish/seafood consumed by district (% within district) ......................... 44 Table 4-4. Species of fish/seafood consumed by area (% within area) .................................. 45 Table 4-5. Fish and animal meat consumption (summary)..................................................... 65
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LIST OF ATTACHMENTS 1. 2. 3. 4.
Questionnaire List of Aldeia Result on fish and meat consumption level Summary of key points from Focus Group Discussions and In Depth Interviews
LIST OF DATA 1. 2. 3.
IDI and FGD Records SPSS Database Summary Excel Spreadsheet
LIST OF ACRONYMS BPS FAO FGD IDI JICA MAF RFLP UNTL
Biro Pusat Statistik (Statistics Indonesia) Food and Agriculture Organization Focus Group Discussions In-Depth Interviews Japan International Cooperation Agency Ministry of Agriculture and Fisheries Regional Fisheries Livelihoods Programme Universidade Nacional Timor Lorosa’e
LIST OF TERMS Aldeia
Timorese term for a sub-village grouping. In terms of size, an aldeia can be equivalent to a dusun in Indonesia or a hamlet in English. Aldeias are not formalized divisions with administrative authority. Timor-Leste has a total of 2,225 aldeias.
Animal protein Protein sourced from animals including fish, other sea or freshwater animals. Fish
Fish and other sea or freshwater animals consumed as sources of animal protein.
Meat
Non-sea or non-freshwater animal meat consumed as source of animal protein.
Suco
Sucos are the smallest administrative division. A group of sucos creates a subdistrict. According to the National Directorate of Statistics there are 442 sucos in Timor-Leste. In terms of size a suco can be equivalent to a desa/kelurahan (administrative village) in Indonesia. 9
ACKNOWLEDGMENT This report has been prepared for the Regional Fisheries Livelihoods Programme (RFLP) of the Food and Agriculture Organization of the United Nations (FAO) by AMSAT INTERNATIONAL. This survey of fish and animal protein consumption and availability was conducted in parallel with the Timor-Leste Baseline Survey under the RFLP programme. This report was developed by a team led by project manager Dr. Linda Christanty. Frieda Subrata, community development and nutrition specialist, led the field survey team which consisted of: Risang Rimbatmaja as survey specialist, Andreas Medah as post-harvest and marketing expert in agriculture and fisheries and Lamidi as expert in livelihoods enhancement and diversification. Jim Travers coordinated the final report analysis and report production working with the entire team. Rudy Purba assisted the team in the report analysis and report writing. The team also thanks Dr. Paul McShane for reviewing the final analysis and assisting in final editing work. We would like to thank Don Griffiths, Chief Technical Advisor RFLP, for his continuing support and guidance in finalizing the report. Also Dr. Enrique Alonso and Pedro Rodriques of the RFLP office in Dili for their continuous support in every aspect of the survey at the national and district level and specifically to Dr. Enrique Alonso for his comments and feedback in finalizing this report. We also thank the people who provided us with strong cooperation and assistance during the field survey: Alexio Gusmao Correia from the District Fisheries Officer (DFO) in Baucau, Junior Pascoal de Carvalho from the DFO in Bobonaro, Elsa de Carvalho from the DFO in Covalima and Agustinho Lao from the DFO in Oecussi. The survey included hundreds of respondents and covered large areas of five districts in Timor-Leste (Baucau, Dili, Bobonaro, Covalima and Oecussi) and would have been impossible without the strong cooperation and support of the Universidade Nacional de Timor-Leste (UNTL). We thank UNTL professors for their comments on the survey questionnaire and all senior students of the UNTL who became part of our team as enumerators in the survey and who faced the challenges of the survey including bad weather, rough seas, poor roads, accidents and inadequate facilities, with good spirits and perseverance. Lastly we thank FAO for the funding and we acknowledge the funding support of the Spanish Agency for International Development (AECID) that made this survey and report writing possible.
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EXECUTIVE SUMMARY A survey of fish and meat consumption and its availability in Timor-Leste was undertaken during January 2011 in the five districts of Baucau, Dili, Bobonaro, Covalima and Oecussi. The survey was conducted together with a baseline livelihoods survey for the Regional Fisheries Livelihoods Programme (RFLP) in Timor-Leste. The RFLP is a 4-year programme of the FAO with activities in Cambodia, Indonesia, the Philippines, Sri Lanka, Timor-Leste and Viet Nam which is being implemented with financial support from Spain (US$19.4 million). The RFLP aims to “strengthen capacity among participating small-scale fishing communities and their supporting institutions towards improved livelihoods and sustainable fisheries resources management”. RFLP management is headquartered in the FAO in Bangkok and has dedicated management staff based in Dili. The survey included 820 randomly selected respondents in 80 aldeia (hamlets) in 55 suco (villages) in 5 districts. A mixed method approach was used including household survey (structured interviews), focus group discussions and in-depth interviews. Interviews were conducted by enumerators recruited from the Universidade Nacional Timor Lorosa’e (UNTL) who were trained and supervised by AMSAT International. The questionnaire was developed by AMSAT International in collaboration with RFLP and five professors from the Universidade Nacional de Timor Lorosa’e, and was field tested in Dili before the survey. Respondents are grouped according to age, gender, household size, marital status, educational achievement, occupation, asset ownership and monthly income. The consumption and availability data collected have been analysed by district, and also by area, i.e. urban, noncoastal and coastal. Regional coverage was affected by difficulty of access to some targeted aldeias in Oecussi (see section 2.1.3 below). Oecussi results are therefore only representative of 70% of Oecussi’s total population, covering the Pante Makasar and Oesilo subdistricts. As a consequence the Oecussi data has been excluded from the collective survey in relation to district comparisons of fish and meat consumption levels. The results therefore reflect data from Baucau, Dili, Bobonaro and Covalima districts. However, Oecussi data has been included in the overall comparisons of urban, coastal and non-coastal areas, as these comparisons are not based on districts. As its population representativeness was quite high (70%) in many cases Oecussi results were also included in the overall, collective results and collective analysis. Key findings include: Combined fish and meat consumption averages 19.4 kg/cap/year Fish consumption was relatively low 6.1 kg/cap/year There was significant variation in consumption of fish between districts ranging from 2.7 kg/cap/year in Bobonaro to 7.7 kg/cap/year in Dili.
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There was significant variation in consumption of fish between urban, non-coastal and coastal areas with subsistence fishing and access to markets being considered as the main factors that influenced the variation. Average meat consumption was 13.3 kg/cap/year. Meat consumption was relatively even across urban, coastal and non-coastal areas, but varied greatly between districts.
Table 0-1. Per-capita consumption of fish and meat by urban-coastal categorisation and by district Area/District
Fish
Consumption (kg/capita/year) Meat Total **)
By Area Type Urban 6.0 19.1 Coastal 17.6 12.1 Non-Coastal 4.0 11.6 Mean *) 6.1 13.3 By District Baucau 5.9 11.6 Dili 7.7 18.2 Bobonaro 2.7 7.0 Covalima 5.5 6.6 Mean *) 6.1 13.3 *) Mean was generated from 4 districts, excluding Oecussi **) Values were rounded after calculating fish and meat combined
25.2 29.7 15.6 19.4 17.5 26.0 9.6 12.2 19.4
Note: In Oecussi (with data from Pante Makasar and Oesilo subdistricts only) the fish consumption level was 9.3 kg/capita/year and the meat consumption level was 22.3 kg/capita/year. Total fish and meat consumption was 31.6 kg/capita/year.
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INTRODUCTION
1.1 Background With a coastline of approximately 700 km, there is considerable potential for fisheries to provide valuable protein for the Timorese people. The Ministry of Agriculture and Fisheries (MAF) estimated that 5,265 fishers operate along the Timor-Leste coastline, conducting mainly coastal fishing and harvest of intertidal resources. There is an opportunity to further develop coastal fisheries to improve the nutrition and well being of the people of TimorLeste. The fish and animal protein consumption and availability survey was one of the activities required by the Regional Fisheries Livelihoods Programme (RFLP) in Timor-Leste. The activity aimed to provide information about fish consumption (fresh and processed), together with demand, supply, availability and market chains. This complements baseline information on fishery product development, improving supply chains to market, and strengthening/ diversifying income opportunities of fisher families. Furthermore, a fish consumption survey would fill a gap in regards to patterns of animal protein consumption in Timor-Leste.
1.2 Objective The objectives of the survey were to estimate current levels of fish and meat consumption and obtain related information on supply, demand and availability. The survey results are expected to be used as the basis for the development of policies and strategies of TimorLeste’s fisheries and aquaculture sectors.
1.3 Survey locations The survey was conducted in five districts (Figure 1-1): 1. Baucau 2. Dili (including Atauro) 3. Bobonaro 4. Covalima 5. Oecussi (an enclave within Indonesia).
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Figure 1-1. 5 districts in Timor-Leste as target survey area (map source: United Nations 2008)
1.4 Output The outputs include information on: Fish and meat consumption in general, Fish consumption in coastal, non coastal and urban areas, Fish consumption per district, and Fish supply/availability.
1.5 Structure of the report The report consists of five Sections. Section 1 is the introduction, covering the background, the objective and the survey locations. It also describes the broad structure of the report. Section 2 describes the methodology of the survey. Section 3 describes the general demographic features of the survey respondents. Section 4 presents the results of the survey with comments and analyses where appropriate. Section 5 presents conclusions and recommendations.
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METHODOLOGY
The study employed a mixed-method of quantitative and qualitative survey, with quantitative survey as the main focus. Data collection methods included:
Desk review of available secondary data sources e.g. official census, existing reports and research, Household survey (structured interview), Focus group discussions (FGD), and In-depth interviews (IDI).
Finding the level and patterns of consumption of fish and other animal protein sources was the focus of the quantitative survey. The quantitative survey was also broadened to include socio-economic aspects of fish or meat consumption. The qualitative survey targeted the daily activities and socio-economic aspects of respondents that were relevant to fish or meat consumption. The qualitative survey was expected to describe the influence of livelihoods on the level of fish and meat consumption. Although there was some overlap in timing and location between the quantitative and qualitative surveys, conducted by different enumerators and/or field teams, generally the quantitative survey was conducted first followed by the qualitative survey. The quantitative survey assisted in identifying good informants to participate in the FGDs and the IDIs.
2.1 Quantitative survey 2.1.1 Selection of respondents A random survey was conducted in five districts of Timor-Leste (namely Baucau, Dili, Bobonaro, Covalima, and Oecussi). The total number of respondents was 820.
Dili district: 332 respondents (33 aldeias) Baucau district: 164 respondents (16 aldeias) Bobonaro district: 134 respondents (13 aldeias) Covalima district: 90 respondents (9 aldeias) Oecussi district: 100 respondents (9 aldeias)
The sample distribution among the five districts was achieved based on the respective district populations and is described below (Fig. 2-1):
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100 90 80 70 60 50
40.5
40 30
20.0
16.3
20
11.0
12.2
10 0 BAUCAU
DILI
BOBONARO COVALIMA
OECUSSI
Figure 2-1. Sample distribution (%)
Dili had the largest sample size with 332 respondents (41%) followed by Baucau (164 respondents, 20%), Bobonaro (134 respondents, 16%), and Oecussi (100 respondents, 12%). The district with the smallest sample size was Covalima with 90 respondents (11%). 2.1.2 Sampling design The 820 respondents were selected randomly using a two-stage random sampling procedure1 at the aldeia level. Details of available aldeia for each suco were received from local government offices and further verified in the field. Randomization was applied at aldeia level. In total there were 80 aldeias selected across 55 sucos. In each aldeia, 10 or 11 respondents were selected at random. The field team first created a list of households based on official information from the head of the aldeia and this list was then verified in the fieldwork process. In cases where lists of households were not available, the field team derived these from visits to the aldeia and made a simple map in order to list of households. Randomisation was then achieved from the final list of households through a systematic random process. First, the team selected a starting point using randomly selected tickets with numbers corresponding to individual households in the aldeia. Next, households to be interviewed were selected based on an interval number, which was calculated by dividing the total number of all households by the target number in the actual survey, which varies from 10 to 20 per aldeia. (A list of surveyed aldeias and their corresponding subdistricts and districts is presented in Table A in Appendix 2).
1
Sampling was designed using guidelines described in Magnani, R (1997). Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA). Washington: Academy for Educational Development.
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2.1.3 Survey constraints in Oecussi The field surveys were conducted in January 2011, during the rainy season in Timor-Leste. This compromised the survey in several areas of Oecussi district as some parts of the survey area were inaccessible due to flash flooding and road closures during the survey period. Random selection of aldeias was therefore conducted only in the accessible subdistricts. Thus, the results for Oecussi do not fully cover the whole district area. Nonetheless, to allow analysis with the predefined confidence level the sample size was maintained and replacement aldeias were selected in Pante Makasar (70 respondents) and Oesilo (30 respondents) subdistricts. Based on the district and subdistrict population, the respondent sample in Pante Makasar represented 54% of the district population (total population 65,524) and the Oesilo respondent sample represented 16% of the district population2. Therefore the Oecussi survey result could explain the condition and characteristics of 70% population of the district. Many of the aldeias in Pante Makasar (with 27 respondents) belong to coastal areas and are located inside or close to the city of Pante Makasar whereas all Oesilo aldeias surveyed (with 30 respondents) were inland and are non-coastal. Two other subdistricts (Nitibe and Passabe) were not surveyed given the above-mentioned constraints. 2.1.4 Respondents and their households The sampling process used households as the sampling unit. Thus, the 820 respondents were selected as representative of the whole population within five districts. Although the households were selected randomly, most people responding to the questionnaires were the wives of the heads of households. Women were generally the ones (99.3%) available for interview at the time of survey and were knowledgeable about household consumption habits. The per-person consumption data presented is based on the average consumption level of the respondent. However this consumption level was also tested and checked to compare to the average per-person consumption level of the members of the household that the respondent represented (see section 4.1). Overall, the survey design gained +/- 5% Confidence Interval (CI) at 95% Confidence Level (CL) using 50% population parameter (assumed unknown). Confidence intervals for survey data varied according to the sample size at district level (Dili = 8.1%; Oecussi= 13.8%; Covalima = 14.4%; Baucau = 10.7%; Bobonaro =11.5%). Although representativeness of the whole district was compromised by the exclusion of some subdistricts, data for Oecussi were still constructed with random selection and are considered valid since the size of sample was maintained in the survey. However data collected for Oecussi are only representative of 70% of the population of whole district.
2
Based on Census 2010 data, the total population of Oecussi district was 65,524 which comprised the population in Nitibe 11,414, Oesilo 10,717, Pante Makasar 35,159 and Passabe 8,234.
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2.1.5 Weightings The weight applied to each respondent is calculated by: [(district population) / (total population) ] x [ (total sample) / (district sample) ], where total population = 561,189 and total sample = 820. Table 2-1. Weight scores for district sampling
District
Baucau Dili Bobonaro Covalima Oecussi
District population size 111,484 234,331 89,787 60,063 65,524 561,189
% district population by total population (A) 19.8656781 41.7561641 15.9994227 10.7028114 11.6759238 100
Sample size
% sample size by total sample size
164 332 134 90 100 820
(B) 20.0000000 40.4878049 16.3414634 10.9756098 12.1951220 100
Weight (A x 1/B) 0.99328390257 1.03132694573 0.97906914751 0.97514503432 0.95742575140
2.1.6 Coastal, non-coastal and urban categories The respondent households were classified into three geographical types: coastal, non-coastal and urban. The objective of this classification was to assess differences in food consumption patterns among urban, coastal and non-coastal areas. Classification was applied at the scale of the aldeia (i.e. not at the larger village or subdistrict scales). Based on RFLP guidelines the three geographical types were defined as follows:
Urban represents a large city e.g. Dili. All aldeias within Dili city were classified as urban (e.g. Caqueo Laran aldeia in Becora suco Cristo Rei subdistrict, Aimutin aldeia in Comoro suco Dom Aleixo subdistrict). Coastal represents aldeias that border directly with the sea. Thus, all aldeias in Dili district (e.g. all aldeias surveyed in Atauro, Fatu Cama aldeia in Meti Aut suco Cristo Rei subdistrict, Fatuisin aldeia in Camenasa suco Suai subdistrict). Most aldeias in larger villages like Liquiça, Suai or Baucau were classified as coastal. Non-coastal means aldeias that do not directly border the sea. This included all aldeias randomly selected and surveyed in Bobonaro.
Based on this classification, of the 820 respondents, 151 were from urban aldeias, 117 were from coastal aldeias, and 552 were from non-coastal areas (Table B in Appendix 2). Data from Oecussi district, covering coastal and non-coastal areas, were included in the analysis even though it did not cover the whole district due to the survey constraints for Oecussi described in section 2.1.3. The area type comparison, based on urban/coastal/noncoastal, describes the condition regardless of the districts. Therefore the Oecussi results were still included in this area type analysis.
18
2.2 Qualitative The qualitative study was conducted in all districts: Dili, Baucau, Bobonaro, Covalima, and Oecussi. It included two data collection methods: Focus Group Discussions (FGDs) and Indepth Interviews (IDIs). The two methods were employed independently with some overlap among participants. The standard FGDs normally required 6-12 participants to discuss relevant issues facilitated by a moderator and recorded by a dedicated note-taker. Participants had been selected from respondents to questionnaires as being information rich. In two FGDs there were only 3-5 participants, but the participants were especially information rich. Typically each FGD lasted 1 to 1.5 hours with several short breaks to energise participants. FGDs included an introductory session to arouse participation followed by easy-to-respond questions (experiential questions). When all participants were comfortable, more analytical questions were asked. FGDs were undertaken in all districts. FGDs were held at community level (aldeia/suco) with the teams facilitating 2-4 FGDs at each location. Most participants included lay persons and poor families. Although FGDs were only undertaken at aldeia/suco level, IDIs were conducted both at community level and at decision-making (i.e. district) level. The study team completed four IDIs in each district with selected FGD participants, local MAF/DFO (District Fishery Office) and household members. For deeper understanding of salient issues, each informant was interviewed several times with each session lasting 30 to 60 minutes. At community level, some IDI informants were participants in FGDs who had demonstrated richer knowledge on relevant issues, such as cultural matters regarding fish consumption. At decision-making or district level, interviews were held with key informants at local offices (District Fisheries Offices). Topics of discussions in the FGDs were designed to support the topics of questions addressed in the quantitative questionnaire, i.e. occupation; daily activities; daily household expenses; daily menu; fish and meat consumption; aspects of culture, and traditions within communities related to fish and meat consumption. The locations, types and number of participants of FGDs and IDIs are shown in Table 2-2. Table 2-2. Locations and participants of FGDs and IDIs District
Baucau Dili
Subdistrict
Type
Participants
No. of participants
Vemase
FGD
Male farmers
7
Buruma
IDI
Housewife, farmer
1
Bidau Lisidere
FGD
Mainly housewives, adult females
19
10
District
Subdistrict Lisidere and Capella Comoro, Dili city
Bobonaro
Covalima
Oecussi
Type
Participants
No. of participants
IDI
Fishers, unemployed, retired person and housewives Housewife
Bidao, Dili city
IDI
Housewife of expatriate
1
Dili city
IDI
1
Cili city
IDI
Batugade, Balibo
FGD
n/a
IDI
Maudemo, Suai
FGD
Housewife, restaurant owner Male expatriate, development organisation Fishers (2 fisher groups) Local staff of development organisation Housewives, farmers
Cassa Bauk, Suai
IDI
n/a
IDI
Oesono
FGD
Oesilo
IDI
Pante Makasar Oenoah, Bobometo, Oesilo Hoineno, Bobometo, Oesilo Noapai, Kunha, Pante Makasar Bonemese, Naimeco, Pante Makasar Baki, Naimeco, Pante Makasar Bausiu, Nipani, Pante Makasar
IDI
FGD
10 1
1 14 1 3
Housewife, farmer, wife of teacher Local staff of development organisation Housewives, some fishing helpers and reef gleaners Camat (subdistrict head)
1
Housewife, fishing and farming Housewife, farmer, wife of suco chief
1
IDI
Housewife, farmer
1
IDI
Civil servant, wife
1
IDI
Housewife, wife of suco chief
1
IDI
Housewife, farmer
1
IDI
Housewife, wife of aldeia chief
1
IDI
1 5 1
1
Information gained from qualitative surveys, such as livelihood activities and other general activities, reinforced the findings of the quantitative survey covering similar issues. Other important issues from the FGDs and IDIs, although not directly linked to the quantitative survey results, informed sources of variation on fish and meat consumption patterns within households and communities.
2.3 Enumerators The enumerator teams that conducted the field work consisted of students from Universidade Nacional Timor Lorosa'e (UNTL) who spoke both Tetum and Bahasa Indonesia. Fluency in Tetum was important because most respondents were more comfortable with this language. Bahasa Indonesia was used in training sessions and in supervision because some field teams came from Indonesia. The minimum education level of an enumerator was a diploma degree. To ensure adequate skills for the survey activities, a two-day training course with practical 20
sessions was conducted for the enumerators. This included training in the conduct of interviews, random selection of respondents and survey coordination. Quality Control was applied at several levels: Observation during the enumerator training session to ensure level of skill (all participants were observed); Cross checking and spot checking during field work (10% of all questionnaires were checked); Checking of data entry (100% of completed filled questionnaires were checked); and Double check of electronic database entries (10% of entries were checked).
2.4 Questionnaire The questionnaire was developed by the consultant team and revised by RFLP together with a research advisory board comprised of five selected UNTL professors. UNTL input into the survey design was considered important as it was engaged as the principal education organisation in country in the survey process to advise on particularities and potential constraints while doing quantitative research in Timor-Leste. Before implementation of the survey, the questionnaire was also tested through a pilot survey of 29 respondents in Dili to check for appropriate wording and to ensure easy understanding of the questions by respondents. On average, each interview took 60 to 90 minutes to complete. Respondents were advised of the expected duration of interview before starting as part of the informed consent part of the questionnaire. There were no objections regarding the duration of the interview.
2.5 Data analysis of the collective result related to Oecussi district During the initial analysis, it became apparent that the results from Oecussi were distorting the average results of the survey for some issues. They were accordingly excluded from the overall analysis of consumption levels. However due to the high representativeness (70%) of Oecussi sample of total population of Oecussi district (see section 2.1.3), Oecussi district results were included when generating a collective result in many cases. They are included in the rest of the analysis where notice is given (patterns of consumption, type of animal protein and others). However, caution must be used regarding the results from Oecussi in order to avoid erroneous interpretations and extrapolations. When analysis uses categorisation of urban/coastal/non-coastal the Oecussi results were included to generate the collective results as the essence of the analysis lies in the characteristics of respondents, based on the area type, not on the district where they live. In this report, all collective results were generated mainly from 5-district results. Where 4district collective results are considered a more accurate interpretation on the subjects or the variables, the exclusion of Oecussi is mentioned in the texts, figures and tables.
21
3
DEMOGRAPHIC PROFILE
This section describes the main demographic features of the surveyed respondents in terms of age and gender distribution, household size and marital status, educational achievement, occupation, asset ownership, and monthly income. 3.1 Population profile The District of Dili had the greatest population density (479 people/km2) and Covalima District the least (44 people/km2). Oecussi which is an enclave district separated from the mainland of Timor-Leste had the smallest household size (4.7) of all Districts (Table 3-1). Table 3-1. Population Profile (Census 2010) District name Number of subdistrict Number of suco Number of aldeia Average household size (number of people) Number of household Population size Density (people/km2)
Baucau
Dili
Bobonaro
Covalima
Oecussi
6 59 281 5.2
6 31 241 6.7
6 50 193 5.4
7 30 147 5.4
4 18 61 4.7
21,439 111,484 66.9
34,975 234,331 478.8
16,627 89,787 60.7
11,123 60,063 44.1
13,941 65,524 70.8
3.2 Age distribution Most respondents (46.7%) were aged between 30–44 years and only a very small portion (2.8%) were senior citizens (aged 65 or older) (Fig. 3-1). Some 22.1% were aged between 1729 years, and 28.4% were aged between 45 and 64 years. Younger respondents were more prominent in Oecussi (26%), Dili (25%) and Bobonaro (24.6%) (Fig. 3-2). 46.7
50 40 30
28.4 22.1
20 10
2.8
0 17-24 Y
30-44 Y
45-64 Y
Figure 3-1. Age distribution of respondents
22
65+
60 50
46.1
45.7
51
48.9
44.8
36.6
40 30
17-24 Y 25
26.5
29.1
26.7
24.6 20
20 10
26
30-44 Y
22
45-64 Y
12.8 4.9
2.4
1.5
4.4
65+ 1.0
0
BAUCAU
DILLI
BOBONARO
COVALIMA
OECUSSE
Figure 3-2. Age distribution of respondents by district
The greatest frequency of young respondents was in urban areas (Fig. 3-3).
Figure 3-3. Age distribution by urban-coastal categorisation
3.3 Marital status Most respondents (85.7%) were married and only 6.5% were single. About 7.2% were widows and 0.6% were divorcees. Oecussi had the largest percentage of married respondents (96%) and Dili and Bobonaro had the lowest (83%) (Fig. 3-4).
23
0.6 7.2 6.5
MARRIED NOT MARRIED/SINGLE DIVORCE WIDOW 85.7
Figure 3-4. Marital status of respondents.
The distribution based on urban-coastal-non-coastal classification reveals similar marital status (Fig. 3-5).
Figure 3-5. Marriage status of respondents by district
3.4 Household size Most respondents belonged to households of five members or greater (up to 22 members). Only 22.6% of respondents came from small size households (1 – 4 persons) (Fig. 3-6).
24
39.6
37.8
5 - 7 persons
8 persons or more
22.6
1 - 4 persons
Figure 3-6. Percentage of respondents by household size (N = 820)
Across all districts there were a mean of 7.0 people per household, but Baucau and Dili were positively skewed towards larger household sizes (Fig. 3-7).
Figure 3-7. Distribution of household size by total (left) and by district (right)
Among districts, the smallest household size was in Oecussi (5.6) and the highest was in Dili (7.9) (Table 3-2). The mean household sizes showed a similar trend to Census 2010 data, but were significantly higher than that of the Census data. Table 3-2. Average household size by district (survey result and census) Number of people Mean Std. Dev. N Average household size (Census 2010)
Baucau 7.01 3.19 163
Dili 7.87 3.47 342
Bobonaro 6.19 2.35 131
Covalima 5.98 2.15 88
Oecussi 5.58 1.97 96
5.2
6.7
5.4
5.4
4.7
Total 6.96 3.1 820
The District of Dili, being urban, had large household sizes (> 7 members). Results for other categories are shown in Figure 3-8. When coastal and non-coastal areas are compared, large households, with more than 7 people, tended to exist more in the non-coastal area (36%).
25
Figure 3-8. Household size of respondents based on urban-coastal-non-coastal categorisation
3.5 Gender distribution of population The gender distribution in the 5 districts derived from Census 2010 shows males 51-52% of the population in productive age groups. The percentage number of men was lower than women for old age groups (> 65 years) (Fig. 3-9). Male
Female
52%
52%
51%
51% 49%
15-29 Y
49%
48%
48%
30-44 Y
45-64 Y
65+
60% 50% 40% 30%
15-29 Y
20%
30-44 Y
10%
45-64 Y 65+ Male Female
Bobonaro
Dili
Covalima
Male Female
Male Female
Baucau
Male Female
Male Female
0%
Oecussi
Figure 3-9. Age distribution of population by gender and by district
26
Table 3-3. Gender comparison of population by age group and by district
District Baucau Bobonaro Dili Covalima Oecussi
Gender
Age Group 15-29 Y
30-44 Y
45-64 Y
65 +
Male
49%
49%
50%
48%
Female
51%
51%
50%
52%
Male
48%
49%
49%
50%
Female
52%
51%
51%
50%
Male
53%
57%
55%
47%
Female
47%
43%
45%
53%
Male
48%
50%
51%
50%
Female
52%
50%
49%
50%
Male
47%
48%
51%
50%
Female
53%
52%
49%
50%
When comparing the ratio between men and women in each age group among districts, the percentage of women were slightly higher than that of men in the age group of 15-29 years old, except for Dili where men were proportionally greater than women (Table 3-3). Most of the respondents to the survey were women. In almost all cases, based on the questionnaire test, they were considered more information rich than men in regards to food consumption in the households. This was especially so for housewives, who formed the majority in the women respondents, and traditionally undertake most of the household activities related to cooking or preparing meals for their families. This was confirmed by discussions and interviews within FGDs and IDIs. Therefore most women could be considered to be knowledgeable of household food consumption patterns. Table 3-4. Distribution of gender in the sample Sex
Respondent categorisation
Male
Total
Female
By District Baucau
1
162
163
Dili
5
337
342
Bobonaro
0
131
131
Covalima
0
88
88
Oecussi
0
96
96
6
814
820
Urban
0
156
156
Coastal
1
116
117
Non-coastal
5
542
547
6
814
820
Total By Area Type
Total
27
Section 4.1 explains how the survey data was extrapolated to make women respondents representative of the whole survey respondents for animal-protein consumption levels.
3.6 Religion The distribution of religious affiliation of the respondents showed that all districts except Dili were Catholic. Dili respondents were 97.7% Catholic, 1.5% Other Christian and 0.6% Moslem. As most respondents were Catholic, it was difficult to ascribe meat and fish consumption patterns to religion. Most respondents ate chicken and marine (seawater/saltwater) fish. Catholic and Christian respondents ate more pork than beef. A large number of respondents also ate eggs (Table 3-5). Table 3-5. Meat or fish consumed grouped by religion of respondents
Pork
Beef
Buffalo/beef
Freshwater fish
Marine fish
Eggs
Deer
Dog
Horse
Dried fish
Catholic Christian Moslem Other Total
Lamb/ goat
Religion
Chicken
Kind of meat or fish consumed
714 5 2 1 722
355 2 2 1 360
571 4 0 1 576
480 4 0 1 485
407 3 0 1 411
179 1 0 0 180
624 4 1 1 631
533 5 0 1 539
4 0 0 0 4
7 1 0 0 8
2 1 0 0 3
13 0 0 0 13
Total 756 5 2 1 764
3.7 Education level At least 66% of the respondents that were interviewed attended school, whereas the rest (34%) did not have any formal education3 (Fig. 3-10). Of those who had attended school, 39% went to elementary school, although only half of them (20%) graduated. Of those 36.8% respondents who attended high school, 30.9% graduated (Fig. 3-11).
3
If Oecussi is excluded, the percentage of respondents that attended school is 67%, which is similar to the average of 5 districts (66%).
28
100 90 80 70
66.0
60 50 34.0
40 30 20 10 0 YES
NO
Figure 3-10. Percentage of schooling experience (N = 820)
BACHELOR COMPLETED
1.1
BACHELOR NOT COMPLETED
0.6
DIPLOMA COMPLETED
1.1
DIPLOMA NOT COMPLETED
0.2 30.9
SENIOR HIGH SCHOOL COMPLETED
5.9
SENIOR HIGH SCHOOL NOT COMPLETED
14.8
JUNIOR HIGH SCHOOL COMPLETED
7.0
JUNIOR HIGH SCHOOL NOT COMPLETED ELEMENTARY COMPLETED
19.8
ELEMENTARY NOT COMPLETED
18.7 0
10 20 30 40 50 60 70 80 90 100
Figure 3-11. Level of education (N = 820)
Among districts, Dili had the highest number of educated respondents (88%). As most Oecussi respondents were located in the Pante Makasar subdistrict, where the capital city of Oecussi is located, there is a relatively high proportion of school experience among respondents (62%). The other three districts had similar proportions of schooling (56%) (Fig. 3-12).
Figure 3-12. School experience of respondents by district
29
Urban-coastal classification (whilst excluding Oecussi) shows that non-coastal respondents had the highest percentage of non-schooling (39%) followed by coastal respondents (32%) (Fig. 3-13).
Figure 3-13. School experience of respondents by urban-coastal categorisation (excluding Oecussi)
In total only 31% of respondents completed high school and only 27% completed elementary school. 19% of respondents did not complete or attend elementary school (Fig.3-14). These percentages were almost equal to the averages of the 4 districts (excluding Oecussi district), e.g. elementary school not completed 17%, junior high school completed 21% and senior high school completed 32%.
Figure 3-14. Completion of school education
30
When districts were compared, school-drop-out percentages were generally high in elementary school. Drop-out rates declined from elementary to senior high school (Fig. 3-15). It should be noted, however, that data reflect mainly adult women respondents.
Schooling drop-out status of respondents (by district) 70%
61%
60%
53% 53%
50% 40%
38%
43% 35%
BAUCAU 38%
33%
27%
30%
21%
20%
DILI
33%
BOBONARO
25% 20% 21% 18% 14%
10%
20%
COVALIMA 0%
OECUSSI
0%
0% Elementary S
Junior HS
Senior HS
Diploma
Bachelor
Figure 3-15. Percentage of drop-out status of respondents in the past
3.8 Occupation Most of the main income earners in the respondent households (64.4%) worked to earn their living (Fig. 3-16), including occupations such as farmer (56.8%), shop/kiosk owner (10%), and teacher (7.6%) (Table 3-6). Almost a half (48.9%) of those working had a second occupation. 64.4
35.6
YES
NO
Figure 3-16. Percentage of work force (N = 820)
Table 3-6. Main job/occupation in respondent’s household (N = 528) Occupation Teacher Lecturer Director Medical doctor/animal doctor PNTL/F-FDTL employee
Percentage 7.6 0.2 0.4 0.2 2.5
31
Occupation Public servant Farmer Fisher Farm worker Market/shop worker Building worker Seller at market/mall/shop Informal vendor Kiosk/small shop owner Seaweed farmer Processed fish vendor/seller Tailor Home industry /handicraft Staff at private company
Percentage 7.2 56.8 0.4 0.6 1.3 0.9 1.3 3.6 10.0 0.2 0.2 0.6 1.9 2.8
In all districts farmer was the most common occupation within the households of respondents (Table 3-7). There were very few fishers because the data reflect the survey areas, which include non-coastal and urban, as well as coastal areas. Table 3-7. Distribution of jobs in districts Occupation
Baucau Teacher 5.2 Lecturer Director Medical doctor/animal doctor 0.9 PNTL/F-FDTL employee Public servant 5.2 Farmer 80.2 Fisher Farm worker 0.9 Market/shop worker Building worker Seller at market/mall/shop Informal vendor 2.6 Kiosk/small shop owner 4.3 Seaweed farmer Processed fish vendor/seller 0.9 Tailor*) Home industry /handicraft*) Staff at private company*) *): Other jobs collected during survey.
Dili 9.6 0.5 1.0 6.1 13.2 25.4 1.0 0.5 3.6 2.0 6.1 16.8 16.8 0.5 0.5 1.5 0.5 7.1
Percentage per district Bobonaro Covalima 4.4 6.6 1.6 2.2 3.3 73.6 78.7 1.1 1.1 2.2 8.8 1.6 3.3 3.3 4.9 1.6
Oecussi 11.1 3.2 66.7 1.6 3.2 9.5 4.8 -
Total 7.6 0.2 0.4 0.2 2.5 7.2 56.8 0.4 0.6 1.3 0.9 1.3 3.6 10.0 0.2 0.2 0.6 1.9 2.8
Of those earning relatively high incomes ($600 and $1,400), most were farmers, teachers and public servants. However, owning a kiosk/small shop was a common second occupation generating high income for the teachers.
32
The documented occupations are probably not complete as other job categories were not included in the questionnaire during the first survey trial. However occupations identified during the survey included: tailor, home industry/handicraft and staff at a private company.
3.9 Ownership of cattle, boats and goods Most respondents (>90%) owned their own homes. Many (75% of respondents) owned pigs and chickens (Fig. 3-17). 91.5
100.0
76.076.8
80.0
62.3
60.0 40.0 20.0
35.134.1 22.818.5 14.0
20.7 13.3 4.5 0.7 0.5
35.7 27.4 8.8
2.0 0.2 2.2
0.0
Figure 3-17. Ownership of goods, cattle and boats
Ownership of livestock is common. However the survey did not quantify the numbers of cattle and chickens owned and whether the cattle and chickens were consumed by the owners or sold to generate income. The FGD/IDIs revealed that many respondents consumed meat from their own livestock only when they held traditional family ceremonies. Some sold their livestock to generate income and some sold them to pay back creditors or relatives from which they had borrowed money. Outside of Dili, most respondents (at least 83%) in the other 4 districts owned chickens and pigs. In Dili only 52-58% owned chickens and pigs (Fig. 3-18).
33
Goods/house/animals/ownership BAUCAU
DILI
COVALIMA
OECUSSI
All Districts
9797 92 93 91 87
100.0
93 939191
77
80.0 Percent
BOBONARO
76
6060 62
60.0
48
545453
59 43
42
40.0
31
27 14
20.0 6
91 8583 77
58
52
49
96
20
20 6 4 9 2
36
5
0.0 TELEPHONE
HANDPHONE
OWN HOUSE
COW
GOAT/SHEEP
PIG
CHICKEN
Figure 3-18. Ownership of assets by district
In Bobonaro, Covalima and Oecussi districts more than half of the respondents surveyed owned cows, whereas the proportion was lower in Dili (5%) and Baucau (20%) (Fig. 3-18). More than 42% of respondents in the districts of Baucau, Bobonaro and Oecussi owned goats or sheep (Fig. 3-18). The percentage of boat owners across all districts is very low. In Bobonaro 5% of respondents owned motorised boats. Covalima had 8% respondents who owned wooden row boats. Only 1-2% of the respondents in all districts owned motorised boats, wooden sailboats or wooden rowboats. These data reflected the survey areas, which were not only coastal, but also non-coastal and urban.
3.10 Monthly income Of all respondents, 64% worked for money in the month before the survey was conducted (Fig. 3-19). This proportion was highest (69%) in non-coastal areas (Fig. 3-20).
34
Last month worked for money (by district) 80%
71%
68%
70%
68%
63%
59%
60% 50%
41%
40%
37%
32%
32%
29%
YES NO
30% 20% 10% 0% BAUCAU
DILI
BOBONARO COVALIMA
OECUSSI
Figure 3-19. Respondents worked for money a month before the survey (by district)
Last month worked for money 80%
69%
70% 56%
60%
53% 47%
44%
50% 40%
YES
31%
30%
NO
20% 10% 0% URBAN
COASTAL
NON COASTAL
Figure 3-20. Respondents worked for money a month before the survey (by urban - coastal)
With the exception of Dili, more than 50% of respondents in each district lived on monthly incomes of less than $100. Some 43% of respondents in Baucau lived on less than $50 per month, as did 34% of respondents in Bobonaro and 28% of respondents in Covalima (Fig. 321). Monthly income 1x a month
SALTED GRILLED everyday several times a month
FRIED BOIL/STEAM several times a week once a month
Figure 4-36. Frequency of buying processed fish/seafood (by type)
62
4.14 Fish and animal meat consumption Respondents were questioned on their consumption of (i) marine fish and (ii) freshwater fish. Meat consumed was recorded as either: chicken, beef (cow), pork, buffalo meat, goat meat and lamb. Eggs were also presented as a food choice. Fish and meat consumption from a specific protein source (e.g. chicken, beef, pork, freshwater fish, and sea fish) was calculated from two variables, which were recorded in the survey questionnaires: Frequency (of meals with fish or meat per interval time; e.g. day, week, month, year) converted to an annual rate. Weight (of fish or meat consumption per one-time consumption or per meal [in grams]) obtained by multiplying the fish size consumed (most of the time based on sample tools used by the enumerators) with the number of pieces or slices, unless the respondent answered with a specific weight in grams. The total consumption per year per respondent was obtained by multiplying the annual frequency by the weight. 4.14.1 Frequency of annual consumption per year The conversion to annual frequency was defined based on the time-interval frequency answered by the respondents (selection of 1 or 2 or 3 below is used only if consumed every day): 3 x a day = 3 x 365 = 1,095 times 2 x a day = 2 x 365 = 730 times 1 x a day = 365 times Several times per week = 96 times Once a week = 48 times Several times per month = 24 times Once a month = 12 times Several times a year = 4 times Very rarely = 2 times.
4.14.2 Weight of consumption per meal Where the respondent did not explicitly answer in grams or kg, the weight was derived from basic conversion based on sample tools which the interviewer showed to the respondent e.g. ½ of the size of the fish sample, 1 small piece of chicken, 1 large piece of meat. The conversion of the fish samples to grams was: ½ of fish = 40 g 1 whole piece = 80 g 1 small piece = 35 g 1 medium piece = 75 g
63
1 big piece = 115 g.
The basic conversion of the meat samples to grams was: Meat Chicken Goat/lamb Pork Beef Water buffalo
Small (g)
Medium (g) 35 20 30 15 15
Large (g) 55 40 50 35 35
75 60 80 55 55
Example calculation of what one specific respondent ate per meal: Chicken “small piece” with quantity = 2, then per meal he/she ate 35 g x 2 = 70 g, and if he/she also ate; Pork “medium size” with quantity = 3 then per meal he/she ate 50 g x 3 = 150 g, and if s/he also ate; Marine (saltwater) fish “whole piece” with quantity = 1 then per meal he/she ate 80 g x 1 = 80 g.
4.14.3 Final calculation of consumption per capita per year The averages of grams or kg consumed/capita/year per specific group in question (e.g. fish/beef/chicken/egg, urban/coastal/non-coastal, 5 districts) were obtained as weighted means that were based on the number of respondents in that specific group (area category, district). 4.14.4 Average consumption The aggregate and average results calculated from the survey data were based on samples from four districts: Baucau, Dili, Bobonaro and Covalima. Data from Oecussi were excluded in the calculation of total mean but are presented for district comparison. Of all protein sources, chicken was the most consumed with 8.3 kg/capita/year followed by pork (2.2 kg/cap/year). Marine (seawater) fish was consumed at 5.8 kg/cap/year. Egg consumption was relatively high at 4.8 kg/cap/year. Total meat consumption was 13.3 kg/cap/year and total fish consumption was 6.1 kg/cap/year (Fig. 4-37).
64
Figure 4-37. Per-capita level of consumption of protein sources in 4 districts
Of four districts surveyed inTimor-Leste 19.4 kg/capita/year of fish and animal meat was consumed. This is comprised of 6.1 kg/capita/year fish and 13.3 kg/capita/year of meat. Further details on consumption rates per district with their sum values and standard deviations of the means are presented in Appendix 3 (Fish and meat consumption levels). Table 4-5. Fish and animal meat consumption (summary) Area/District
Fish
Consumption (kg/capita/year) Meat Total **)
By Area type Urban 6.0 Coastal 17.6 Non-Coastal 4.0 Mean *) 6.1 By District Baucau 5.9 Dili 7.7 Bobonaro 2.7 Covalima 5.5 Mean *) 6.1 *) Mean was generated from 4 districts, excluding Oecussi **) Values were rounded after calculating fish and meat combined
19.1 12.1 11.6 13.3
25.2 29.7 15.6 19.4
11.6 18.2 7.0 6.6 13.3
17.5 26.0 9.6 12.2 19.4
In Oecussi, where data only includes Pante Makasar and Oesilo subdistricts, the fish consumption level was 9.3 kg/capita/year and the meat consumption level was 22.3 kg/capita/year. Total fish and meat consumption was 31.6 kg/capita/year. These results are
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not included in the table and the average calculations, since they have to be considered with caution. There was a significant correlation between levels of meat consumption and levels of fish consumption (Pearson correlation 0.275 with p significance
