The 2010 Population and Housing Census put the district population at 136,140. Using the 2000 Population of 89,967 as the base year, the district has an annual growth rate of 3.9%. This means that the district is experiencing a faster growth rate than the regional and national which has 2.7% and 2.5% annual growth rate respectively.
The faster growth rate for the district can be attributed to a number of factors. The district has assumed a dormitory status serving the Regional Capital, Kumasi. Again, due to the pressure on land in Kumasi, some developers are moving from the metropolis to the peri- urban areas. The presence of the Habitat for Humanity Project in two communities namely, Nkwantakese and Mowire in the District with a total of about 600 houses is a contributory factor. The acquisition of large tract of land by Suame Magazine Industrial Development Organisation (SMIDO) at Adubinso in the district for activities of garages is also attracting people and industrial activities to the District.
The major ten (10) communities in the district and their population are as shown in Table below.
From Table1.9 above, it is clear that 51% of the population is concentrated in the ten (10) largest communities; this is an indication that these communities are fast being urbanized. This implies that there’s going to be increasing pressure on existing facilities in the communities. Thus, there is the need to plan adequately to cater for the increasing population.
Spatial Distribution of Population
The total population of the district as projected to the year 2014 using the 2000 Population and Housing Census Report as the base is 153,710. Almost fifty –one percent (51%) of this is concentrated in the ten largest settlements. Atimatim which is the largest settlement in the district has a population of 23,948 representing 16% of the total population in the district. The next largest settlements are Tetrem, Afrancho, Kyekyerewere, Ankaase, Ahenkro, Adumakaase-kesse, Nkukua Buoho, Boamang and Kodie.
However, about forty-nine percent (49%) of the people are concentrated in other settlements which are mostly rural.
The sex structure of the district indicates 48.7% for males and 51.3% for females which does not differ very much from what pertains in 2000. The 2000 Population and Housing Census indicted that there were 48.3% males and 51.7% females.
By implication conscious policies should be formulated to increase women participation in development. Policies should also be formulated to empower women to contribute meaningfully to the development efforts.
From Figure 1.2 above, the age structure of the population within 0–14 cohort decreased form 45% to 41% in 2000. In this vein, the population at the age of 65 and above has decreased from 6% to 4%. However, the population within the age grouping from 15-64 has rather increased from 49% to 55%. The decrease in population between 0-14 and 65and above gives an indication that the burden on the economically active population is reducing. For instance, the dependency ratio for 2000 1:1.06 whiles that of 2010 is 1:0.82. The increase of population within 15-64 also means that, more people are maturing into the labour force. Policies and strategies must be formulated to create more employment avenues for the people.
According to 2010 Population and Housing Census Report, the district has a population density of 332.5 sq. km. This compared to the national and regional density indicates that the district is more densely populated than that of national and regional. The high density, as explained earlier, is attributed to the nearness of the district to Kumasi. Also, part of the district has assumed peri-urban status attracting a lot of people from Kumasi and other areas. This has brought a lot of pressure on the existing facilities bringing in its trail issues of waste generation and management.
Rural Urban Split
According to the 2010 Population and Housing Census Report, the district has 25.8% urban population as against 74.2% rural. This indicates that the district has large rural population that must be planned for to make life comfortable in the rural areas.
From the 2010 Population and Housing Census, the household size for the district is 4.4. This differs from what pertained in 2009 which was 6.5 according to the Socio Economic Survey Conducted by the District Planning and Coordinating Unit.
Room occupancy is 2.1 compared with 4 in 2009 from the same report. Male Household heads form 63.3% as against 36.65% of females. This compares favorably with the national figures which has 65.3 for males and 34.7% for females.
The dependency ratio of the district is 1:0.82 from the 2010 Population and Housing Census. This compared to the 2000 figure of 1:1.06 means that the dependence on the active population is reducing. This situation can be exploited to encourage workers to show interest in savings which would have a rippling effect on the development activities of the district.
Migration is a critical factor of population growth in the District. The closeness of the District to Kumasi has turned most of its communities into dormitory towns. Again, the availability of land for residential and agriculture purposes has resulted in attracting people from Kumasi into the District.
The population between the ages of 15-64yrs is 74,732. Out of this, 54,348 form the economically active population. The total number of the employed within the economically active population is 51,604 whiles the unemployed stands at 2,744 forming 5% of the economically active population.
There is the need to put in place measures for creating more employment avenues for this population if the district is to achieve full employment.
This stage of the analysis deals with the organization of human and economic activities in space within Afigya-Kwabre District.
This approach to development planning is concerned with the social and economic functions that settlements perform and how in combination they form a pattern or system that can influence economic and social development in the district as a whole.
The approach uses a combination of methods to determine the spatial pattern or system of the District’s development. Those considered important for analysis of the Afigya-Kwabre District’s Spatial Organization are:
a. Scalogram analysis
b. Surface accessibility analysis
The scalogram is a graphic device that illustrates in the form of a matrix chart the distribution of functions of all selected settlements in a locality or district by their frequency of presence or absence. The scalogram gives a good impression about the functions that settlements perform in a particular locality or District. This in a way assists in the determination of which settlements lack which services or facilities.
It is also useful in categorizing settlements in the district into levels of functional complexity. The complexity serves as the means to the determination, in the future of types and diversity of services of the district at various levels in the hierarchy. In effect, a scalogram can be used to make decision about appropriate ‘Package’ of investments for settlements in the district at different levels in the spatial hierarchy.
In constructing the district scalogram, a total of 31 functions were considered on presence or absence basis for all selected settlements. The settlements included in the analysis were selected using a population of 2000 as the cutoff point.
Since the scalogram does not give any indication of quantitative and qualitative features or services and facilities, a weighting technique based on the frequency of occurrence of service/facilities was applied.
The weights were added to determine the total centrality from highest to lowest hierarchy. The resultant diagram is shown in Table 1. Therefore, the centrality index for a settlement is the sum of the weights of functions found there. The higher the index, the greater its functional complexity.
Functional Hierarchy of Settlements
The hierarchies of settlement in the Afigya-Kwabre District were distinguished by calculating the centrality index of top twenty (20) settlements as a percentage of the total weighted centrality index using the scalogram analysis.
Date Created : 11/10/2017 7:40:46 AM