Directory UMM :Data Elmu:jurnal:A:Agricultural Systems:Vol67.Issue3.2001:
Agricultural Systems 67 (2001) 139±152
www.elsevier.com/locate/agsy
Relating household characteristics to urban
sheep keeping in West Africa
M. Siegmund-Schultze *, B. Rischkowsky
University of GoÈttingen, Tropical Animal Production, Kellnerweg 6, 37077 GoÈttingen, Germany
Received 25 April 2000; received in revised form 21 July 2000; accepted 19 October 2000
Abstract
Urban sheep production is widespread in Bobo-Dioulasso despite its formal illegality. This
study was aimed at the identi®cation of socioeconomic characteristics in¯uencing the decisions of households to take up this activity. One hundred and thirty-six households (half of
them keeping sheep, half not keeping small ruminants) were interviewed to collect data on
their socioeconomic situation. Three techniques of multivariate analyses were compared.
Cluster analysis and logistic regression revealed the following socioeconomic dierences
between the two groups: the probability of keeping sheep increases with the size of the
household and the rate of illiteracy. Households are also more likely to keep sheep if urban
cattle husbandry is practised, if there is only one household in the compound and if the keeper
has already changed his/her trade at least once. Correspondence analysis provided visual
con®rmation of these results. Cluster analysis allowed a more profound understanding of the
situation by drawing attention to a `transitional dierentiation': non-keepers in a group of
keepers and vice versa tell us something about potential future keepers or non-keepers.
# 2001 Elsevier Science Ltd. All rights reserved.
Keywords: Household characteristics; Urban sheep keeping; West Africa
1. Introduction
The spectacular growth rates in the largest African cities of the 1960s and 1970s
due to rural±urban migration have declined since the 1980s to that associated with a
natural increase. Nevertheless, the urban population on the African continent has
continued to grow in the 1990s by approximately 4.5% per year. Where national
* Corresponding author.
0308-521X/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.
PII: S0308-521X(00)00052-4
140
M. Siegmund-Schultze, B. Rischkowsky / Agricultural Systems 67 (2001) 139±152
economics have stagnated, the continuous urban growth has been associated with
deterioration of services and infrastructure leading to drastic changes in the labour
market. There has been a decline in well-paid secure employment and a shift to the
burgeoning informal or small scale, unregulated sector comprising a wide variety of
activities in response to the needs and ®nancial capacity of the poor (UNCHS,
1996).
This change has led to a rapid expansion of urban farming during the 1980s, e.g. in
Dar Es Salaam an increase from 18% of families engaged in agriculture in 1967 to
67% in 1991 (UNDP, 1996) of which 74% kept livestock. A widespread system of onplot keeping of livestock is practised in West and North African cities, where stallkept
and tethered sheep are fattened for Muslim ceremonies (Waters-Bayer, 1995).
This development of urban small scale livestock production is unplanned and in
the densely populated neighbourhoods gives growing concern that it is creating
health and environmental hazards (UNDP, 1996). Consequently, urban livestock
keeping is often illegal, e.g. in our study area in Burkina Faso (Front Populaire,
1991). Nevertheless, the practice persists because it oers food and jobs which would
not otherwise be available to the community. Therefore, this dilemma has to be
addressed.
To do so, city planners need to understand the underlying reasons and the characteristics that predispose to urban livestock keeping. It may be a consequence of
poverty regardless of the origin and cultural background of the people. However, it
is suggested that rural immigrants are more likely to practice it than their urban
neighbours, because it is the job they are best equipped to do. This study hypothesises that a decision in favour of urban sheep keeping can be related to the socioeconomic pro®le of households. Thus, it compares socioeconomic characteristics of
urban sheep keepers with their non-keeping neighbours.
To test the hypothesis a multivariate method is needed which allows the formation
of socioeconomic groups with comparable behaviour. Dierent analytical techniques are available including cluster analysis, which is a common method and was
used to group e.g. farming systems (Hardiman et al., 1990; Williams, 1994), grazing
patterns of pastoralists (Artz and Jamtgaard, 1988) or years with similar patterns of
¯ock productivity (Rey and Das, 1997).
Logistic regression has also been applied mainly to analyse veterinary aspects, e.g.
modelling dichotomous response of infected/not infected or similar questions (Uhaa
et al., 1990; Jensen and Hùier, 1993; Curnow and Hau, 1996; Jamaluddin et al.,
1996; Martin et al., 1997). Application has been less frequent in the analysis of
reproduction (Gates, 1993; Nash et al., 1996), production aspects (Smuts et al.,
1995) and systems (Roth, 1990; Jolly and Gadbois, 1996). A similar categorical
modelling technique, the loglinear model, was used by Richardson and Whitney
(1995) to predict the occurrence of households keeping goats in Khartoum.
Correspondence analysis is a common French technique, e.g. PeÂnelon (1992) and
Arbelot et al. (1997) applied it to determine suitable variables for a subsequent
classi®cation by cluster analysis. Occasionally it is used on its own, e.g. Hubert
(1996) identi®ed driving factors behind dierent intensities in diversi®cation of
farmers' income.
M. Siegmund-Schultze, B. Rischkowsky / Agricultural Systems 67 (2001) 139±152
141
These three multivariate analyses pursue quite dierent methods to arrive at a
classi®cation: cluster analysis is used in a case-driven and logistic regression in
a variable-driven way, while correspondence analysis leads to relative answers by
comparing proximity between points in an Euclidean space. So there is a need to
check if the characteristics which emerge are dependant on the method used.
Therefore, the aim of this paper is twofold: to identify the driving forces in the
decision for sheep husbandry and to test the consistency of results obtained with
dierent analytical techniques.
2. Material and methods
The study area chosen was Bobo-Dioulasso, the second largest town of Burkina
Faso with approximately 400,000 inhabitants (estimation of MinisteÁre de l'EÂquipement, 1990), located in the sub-humid zone.
In Bobo approximately one sixth of the households kept small ruminants (CentreÁs, 1991). A survey in 1480 urban households keeping sheep organized by CIRDES
in 1995 showed that on average four hair sheep with ¯ock sizes ranging from one to
60 animals are kept. Sheep production is nearly always a secondary activity of the
households, their main activities covering all sorts of trade. Ten percent of
the owners are women. Sheep are of special importance in Muslim ceremonies
and the majority of keepers are Muslim, but the proportion corresponds to their
overall predominance in Bobo-Dioulasso (Kocty-Thiombiano, 1995).
It was planned to interview a subsample of households from the CIRDES survey
which proved impossible because those households could not be retraced due to
missing street names and housenumbers and non reliable documentation of
names. Therefore, 72 sheep keepers in a central and a peripheral district of BoboDioulasso were interviewed assuring that their characteristics represented the main
sample. Similar data were collected in 64 neighbouring households not keeping
small ruminants.
The statistical analyses were performed with socioeconomic variables only, i.e.
no characteristics of sheep husbandry were entered. Table 1 presents the variables
selected for the analysis with their codes and short descriptions. The variables explain
life circumstances and origin of the actors (age, religion, ethnic group, activity of
parents, time spent in the city, changes of activity, possession of compound), others
describe the household (composition, number of households on the compound), the
education (literacy rate, duration and type of school attendance) and the agricultural activities (land, cattle).
After a ®rst descriptive analysis of the data, cluster analysis grouping the actors,
logistic regression (categorical modelling of variables), and correspondence analysis
of variables were performed using the respective procedures cluster, catmod and
corresp of SAS (statistical analysis system for Windows, version 6.11). Multivariate
analyses need a consistent scaling of the variables to be included: as the original
scales of the variables diered, the lowest common level, namely nominal scale, had
to be used.
142
M. Siegmund-Schultze, B. Rischkowsky / Agricultural Systems 67 (2001) 139±152
Table 1
Description of variable codes
Variable code
Description
Numerical variables
AGE
Age of keeper or non-keeper at testing
CATTLE
Number of cattle reared in town by the household
FRLITRAT
French literacy rate of household (household members of all ages, who declared
to be literate in French divided by members above 7 years old assumed to be
potentially literate)
LAND
Ha cultivated by the household
MODMAX
Maximal duration of modern education of one of the household members
NBHH
Number of households in compound
SINCE
Since . . . years in town
SUMRED
Potential manpower of household (sum of persons in household reduced by
infants and children attending school)
Categorical variables and their levels
ACTCHANG
Changed Ð not changed main activity (trade)
ACTPAR
Activity of parents: livestock farmer Ð crop farmer Ð crop farmer+other
non-livestock activity Ð other
BORNIN
Keeper or non-keeper born in Bobo Ð born anywhere else
EDUCAT
Education categories of keeper or non-keeper: only Koran school Ð Koran and
modern school Ð modern up to 6 years Ð modern more than 6 years Ð not
frequented school
ETHNIC
Ethnic groups: Mossi Ð Peulh Ð other groups Ð foreigner, not from Burkina Faso
LOCPROP
Status of habitat: tenant Ð proprietor
RELIGION
Muslim Ð Christian Ð animist
SECTOR
Peripheral Ð central sector of town
CATTLE
Keeping Ð not keeping cattle in town
Signi®cant numerical variables transformed into categories (for cluster analysis)
FRLITRAT
Four quartiles (0±0.357; 0.358±0.625; 0.626±0.810; 0.811±1.00)
NBHH
One Ð more households in the compound
SUMRED
Three terciles (1±3; 4±7; 8±34)
Reduced categories of variables as included in logistic regression
ACTPAR
Three categories: crop farmer Ð livestock farmer Ð other
FRLITRAT
Two categories: index
www.elsevier.com/locate/agsy
Relating household characteristics to urban
sheep keeping in West Africa
M. Siegmund-Schultze *, B. Rischkowsky
University of GoÈttingen, Tropical Animal Production, Kellnerweg 6, 37077 GoÈttingen, Germany
Received 25 April 2000; received in revised form 21 July 2000; accepted 19 October 2000
Abstract
Urban sheep production is widespread in Bobo-Dioulasso despite its formal illegality. This
study was aimed at the identi®cation of socioeconomic characteristics in¯uencing the decisions of households to take up this activity. One hundred and thirty-six households (half of
them keeping sheep, half not keeping small ruminants) were interviewed to collect data on
their socioeconomic situation. Three techniques of multivariate analyses were compared.
Cluster analysis and logistic regression revealed the following socioeconomic dierences
between the two groups: the probability of keeping sheep increases with the size of the
household and the rate of illiteracy. Households are also more likely to keep sheep if urban
cattle husbandry is practised, if there is only one household in the compound and if the keeper
has already changed his/her trade at least once. Correspondence analysis provided visual
con®rmation of these results. Cluster analysis allowed a more profound understanding of the
situation by drawing attention to a `transitional dierentiation': non-keepers in a group of
keepers and vice versa tell us something about potential future keepers or non-keepers.
# 2001 Elsevier Science Ltd. All rights reserved.
Keywords: Household characteristics; Urban sheep keeping; West Africa
1. Introduction
The spectacular growth rates in the largest African cities of the 1960s and 1970s
due to rural±urban migration have declined since the 1980s to that associated with a
natural increase. Nevertheless, the urban population on the African continent has
continued to grow in the 1990s by approximately 4.5% per year. Where national
* Corresponding author.
0308-521X/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.
PII: S0308-521X(00)00052-4
140
M. Siegmund-Schultze, B. Rischkowsky / Agricultural Systems 67 (2001) 139±152
economics have stagnated, the continuous urban growth has been associated with
deterioration of services and infrastructure leading to drastic changes in the labour
market. There has been a decline in well-paid secure employment and a shift to the
burgeoning informal or small scale, unregulated sector comprising a wide variety of
activities in response to the needs and ®nancial capacity of the poor (UNCHS,
1996).
This change has led to a rapid expansion of urban farming during the 1980s, e.g. in
Dar Es Salaam an increase from 18% of families engaged in agriculture in 1967 to
67% in 1991 (UNDP, 1996) of which 74% kept livestock. A widespread system of onplot keeping of livestock is practised in West and North African cities, where stallkept
and tethered sheep are fattened for Muslim ceremonies (Waters-Bayer, 1995).
This development of urban small scale livestock production is unplanned and in
the densely populated neighbourhoods gives growing concern that it is creating
health and environmental hazards (UNDP, 1996). Consequently, urban livestock
keeping is often illegal, e.g. in our study area in Burkina Faso (Front Populaire,
1991). Nevertheless, the practice persists because it oers food and jobs which would
not otherwise be available to the community. Therefore, this dilemma has to be
addressed.
To do so, city planners need to understand the underlying reasons and the characteristics that predispose to urban livestock keeping. It may be a consequence of
poverty regardless of the origin and cultural background of the people. However, it
is suggested that rural immigrants are more likely to practice it than their urban
neighbours, because it is the job they are best equipped to do. This study hypothesises that a decision in favour of urban sheep keeping can be related to the socioeconomic pro®le of households. Thus, it compares socioeconomic characteristics of
urban sheep keepers with their non-keeping neighbours.
To test the hypothesis a multivariate method is needed which allows the formation
of socioeconomic groups with comparable behaviour. Dierent analytical techniques are available including cluster analysis, which is a common method and was
used to group e.g. farming systems (Hardiman et al., 1990; Williams, 1994), grazing
patterns of pastoralists (Artz and Jamtgaard, 1988) or years with similar patterns of
¯ock productivity (Rey and Das, 1997).
Logistic regression has also been applied mainly to analyse veterinary aspects, e.g.
modelling dichotomous response of infected/not infected or similar questions (Uhaa
et al., 1990; Jensen and Hùier, 1993; Curnow and Hau, 1996; Jamaluddin et al.,
1996; Martin et al., 1997). Application has been less frequent in the analysis of
reproduction (Gates, 1993; Nash et al., 1996), production aspects (Smuts et al.,
1995) and systems (Roth, 1990; Jolly and Gadbois, 1996). A similar categorical
modelling technique, the loglinear model, was used by Richardson and Whitney
(1995) to predict the occurrence of households keeping goats in Khartoum.
Correspondence analysis is a common French technique, e.g. PeÂnelon (1992) and
Arbelot et al. (1997) applied it to determine suitable variables for a subsequent
classi®cation by cluster analysis. Occasionally it is used on its own, e.g. Hubert
(1996) identi®ed driving factors behind dierent intensities in diversi®cation of
farmers' income.
M. Siegmund-Schultze, B. Rischkowsky / Agricultural Systems 67 (2001) 139±152
141
These three multivariate analyses pursue quite dierent methods to arrive at a
classi®cation: cluster analysis is used in a case-driven and logistic regression in
a variable-driven way, while correspondence analysis leads to relative answers by
comparing proximity between points in an Euclidean space. So there is a need to
check if the characteristics which emerge are dependant on the method used.
Therefore, the aim of this paper is twofold: to identify the driving forces in the
decision for sheep husbandry and to test the consistency of results obtained with
dierent analytical techniques.
2. Material and methods
The study area chosen was Bobo-Dioulasso, the second largest town of Burkina
Faso with approximately 400,000 inhabitants (estimation of MinisteÁre de l'EÂquipement, 1990), located in the sub-humid zone.
In Bobo approximately one sixth of the households kept small ruminants (CentreÁs, 1991). A survey in 1480 urban households keeping sheep organized by CIRDES
in 1995 showed that on average four hair sheep with ¯ock sizes ranging from one to
60 animals are kept. Sheep production is nearly always a secondary activity of the
households, their main activities covering all sorts of trade. Ten percent of
the owners are women. Sheep are of special importance in Muslim ceremonies
and the majority of keepers are Muslim, but the proportion corresponds to their
overall predominance in Bobo-Dioulasso (Kocty-Thiombiano, 1995).
It was planned to interview a subsample of households from the CIRDES survey
which proved impossible because those households could not be retraced due to
missing street names and housenumbers and non reliable documentation of
names. Therefore, 72 sheep keepers in a central and a peripheral district of BoboDioulasso were interviewed assuring that their characteristics represented the main
sample. Similar data were collected in 64 neighbouring households not keeping
small ruminants.
The statistical analyses were performed with socioeconomic variables only, i.e.
no characteristics of sheep husbandry were entered. Table 1 presents the variables
selected for the analysis with their codes and short descriptions. The variables explain
life circumstances and origin of the actors (age, religion, ethnic group, activity of
parents, time spent in the city, changes of activity, possession of compound), others
describe the household (composition, number of households on the compound), the
education (literacy rate, duration and type of school attendance) and the agricultural activities (land, cattle).
After a ®rst descriptive analysis of the data, cluster analysis grouping the actors,
logistic regression (categorical modelling of variables), and correspondence analysis
of variables were performed using the respective procedures cluster, catmod and
corresp of SAS (statistical analysis system for Windows, version 6.11). Multivariate
analyses need a consistent scaling of the variables to be included: as the original
scales of the variables diered, the lowest common level, namely nominal scale, had
to be used.
142
M. Siegmund-Schultze, B. Rischkowsky / Agricultural Systems 67 (2001) 139±152
Table 1
Description of variable codes
Variable code
Description
Numerical variables
AGE
Age of keeper or non-keeper at testing
CATTLE
Number of cattle reared in town by the household
FRLITRAT
French literacy rate of household (household members of all ages, who declared
to be literate in French divided by members above 7 years old assumed to be
potentially literate)
LAND
Ha cultivated by the household
MODMAX
Maximal duration of modern education of one of the household members
NBHH
Number of households in compound
SINCE
Since . . . years in town
SUMRED
Potential manpower of household (sum of persons in household reduced by
infants and children attending school)
Categorical variables and their levels
ACTCHANG
Changed Ð not changed main activity (trade)
ACTPAR
Activity of parents: livestock farmer Ð crop farmer Ð crop farmer+other
non-livestock activity Ð other
BORNIN
Keeper or non-keeper born in Bobo Ð born anywhere else
EDUCAT
Education categories of keeper or non-keeper: only Koran school Ð Koran and
modern school Ð modern up to 6 years Ð modern more than 6 years Ð not
frequented school
ETHNIC
Ethnic groups: Mossi Ð Peulh Ð other groups Ð foreigner, not from Burkina Faso
LOCPROP
Status of habitat: tenant Ð proprietor
RELIGION
Muslim Ð Christian Ð animist
SECTOR
Peripheral Ð central sector of town
CATTLE
Keeping Ð not keeping cattle in town
Signi®cant numerical variables transformed into categories (for cluster analysis)
FRLITRAT
Four quartiles (0±0.357; 0.358±0.625; 0.626±0.810; 0.811±1.00)
NBHH
One Ð more households in the compound
SUMRED
Three terciles (1±3; 4±7; 8±34)
Reduced categories of variables as included in logistic regression
ACTPAR
Three categories: crop farmer Ð livestock farmer Ð other
FRLITRAT
Two categories: index