Demographic data gives an important tool for the development and evaluation of policies that shapes the overall    development agenda of every community. Human resource development is the pivot of Development Planning and Management. There is therefore the need to consider the dynamics of population growth, basic demographic characteristics like the population size, structure, growth rate, labour force including the problem of child labour in the galamsey activities at some mining areas in the District and their implications on development.

The rapid growth of population and its youthfulness are matters of great concern which need to be tackled especially, when varied in relation to the performance of the District economy, education, health needs, water and sanitation and its impact on environment and human development. The population analysis will be used as a yard stick to assess the threshold of population and service provision such as health and education to population ratio.


Population refers to the total number of people living in geographical defined area or location at a given point intime. Generally, demograhers seek to know the levels and trends in population size and its components. This section of gthe report focuses on all issues relating to population and characteristics that is the growth rate of the population. It also analyse population densities, dependency ratios, rural-urban spit and the implications of these demographic characteristic to development planning.

Population Size and Distribution

The population of the district in 2010, according to the Ghana Statistical Service was 64,211, out of this figure 31,785 are males and 32,427 are females representing 1.34% of Ashanti Region’s total population of 4,780,380. The current projected population of the District for 2018 is 75,826 with 37,534 Males and 38,292 Females using a growth rate of 2.1% in 2018.

Population Density

Population density is the measurement of people per unit area. Thus, the population devided by the total land area. The population density based on the land surface of 713.30 (321.12) km2 with a projected population of 75,826. The population density stands at 106.2 persons per square kilometer.

Using the 2010 population as the base, the projected population for the District is calculated using gthe geometric is assumed that the growth rate of 2.1% would be held constant gthrough out the plan period (2018-2021).

The Geometric ethod of calculating population growth was used.

The formula is indicated below:

P1 is the population for planned year (future)

P0 is the present (base) population

1= is constant factor

t= time period (years) between present and the future

r=Rate of growth

Household Sizes and Characteristics

According to the 2010 Population and Housing Census Report, a household is defined as a person or group of persons, who lived together in the samehouse or compound and shared the same house keeping arrangements. In general, a household consist of a man, wife, children and some other relatives or a house help who may be living with them.

In the district, the male household constitute 30.2% and female 15.2% of the household population. The 2010 population housing and census reveals that the district household headship is dominated by male. This implies that since the male are mostly the heads of the households in the district, the views of the females are less likely to be heard in the decision making proess.

Hence affirmative actions and interactions with identifiable women groups are needed to elicit the perspectives of the women in the development processes. Vigorous educational campaign is also needed to abolish completely or mitigate the social effects of terrible traditional practices that violate the fundamental human rights and liberties of women. However, the total number of child (son/daughter) headed households is Male in this category which represents (47.4%) as against the female category of (44.1%).

Age and Sex Structure

The population of the District could be categorized into three main age groups with 0-14 constituting children being about 42.2% of the population, 15-64 constituting the active working population being about 53.0% and the 65+ constituting the aged being about 4.8% of the population.  Table 1.11 depicts the age and sex distribution of the District in 2010.

The age structure of the district is skewed towards the youth. The highest proportions of the population are in the age cohorts; 15-64 (56.87%). Cumulatively, 35.53% of the population in the District is below 15 years which is lower than the regional figure.

The implication for development planning is that there must be adequate provision of social amenities such as education, health, water and sanitation, recreational centres and other needs for bthese children. It also calls for increasing demand for social facilities such as schools and health. The youthful population promises potential labour force if properly mnaged. Another implication of the youthful population is iits potential to grow rapidly. It is therefore recommended that employment opportunities should be available to utilize the youthful population.

Population Dependency Ratio

Dependency ratio refers to the ratio of the economically dependent part of the population to the productive part that is the ratio of the elderly (65 and above) plus the young (0-14) to the population in the ‘working ages’ (15-64). Age dependency ratio refers to the ratioof the persons in the ages defined as dependent (0-14 and 65+) to the persons in the ages defined as economically active (15-64) in a population.

It is assessed to find the hypothetally ideal situation that should exist for finding the proportion of a population that is dependent. The dependent population conceptually, is made upof age groups 0-14 years (child dependency) and 65 years and older (older age dependency) divided by the working population (15-64). In the Adansi Asokwa District about 56.87% of the population is in the economically active labour force (43,122), whilst 43.12% are classified as inactive. 

The District has a total age dependency ratio of 75.84. This means that a hundred persons in the working age group (15-64) cater for about 70 persons in the dependent age groups (0-14 and 65 years and older). Age dependency ratio is lower in urban areas than in rural areas which mean that the age dependency burden is heavier in the rural than urban areas.

This further raise the level of economic dependency which has a negative impact on the local economic development. The effect of this is the break of social cohesion and support for the family since the little income earned is not able to support nuclear family let alone the extended family. Within the planned period therefore measures like improving Agriculture Service Sectors would be taken to address the problem of unemployment and underemployment.

The dependent population is the proportion of people catered for by the working population or those in the employable age bracket (15-64). The structure or composition of the broad age cohort above indicates that majority (56.87%) of the population are in the working age group, which is a resource potential for the District. Again, 35.53% of the distrct’s population is children below 15 years as shown in table above.

The dependency ratio for Adansi Asokwa District is 75.84. This implies that 75.84 ae dependent on one employable person with a dependency ratio of 0.7584:1. The real dependency burden may be higher since the employable ages include a greater proportion of the unemployed and those in school or acquiring some skills.

Measures are therefore required to increase employment avenues so as to be able to support and cater for the dependent population. There is therefore the need for the creation of employment opportunities so that the active working population could cater for their dependents. The youthful nature of the population (56.87%) is a good source of labour supply in the district. However, this also calls for improving the quality of life of the people and human development and other interventions geared towards improving the quality of life of the people and human development in the district. This also implies that alternative jobs must be created to absorbthe youthful population while those with no skills are given suitable employable skills to make thaem productive to the local economy.

Spatial Distribution


There are about 94 communities in the District after the splitting of Adansi Asokwa from Adansi North in 2018.  However, only four (4) of them have urban characteristics with population of 5000+. The Table below depicts some of these communities and their population as at the year 2010 when the Population census was conducted.

Rural - Urban Split

Looking at the District set up, rural dwellers constitute about 52,168 which is 68.8% as against urban dweller who also constitutes about 23,658  which is 31.2%.  Thus, the district is unable to attract high level investment and infrastructure like banking, second cycle institution, market centres etc. Rural-urban migration is very high in the district due to its proximity to Obuasi, Bekwai and Kumasi.  This therefore negatively affects agricultural development in the District as the young and energetic people migrate to the urban centers leaving the weak and the aged back to engage in agriculture in the District.

Implication of Population Characteristics for Development

The Adansi Asokwa District Assembly Population characteristic, to a large extent inluences the extent to which social and economic infrastructure in district economy could be provided. The increase in the size of the population creates a social burden to service providers such as the district Assembly, NGOs, CBOs, FBOs to channel their scarce resource to provision of infrastructure such as schools, expansion of health infrastructure and recreational centres which will support the youth and children.

Again the need to adopt policies to create wealth and job opportunities for the unemployed and the underemployed youth must be tackled with all seriousness it deserves. Furthermore, as the aged population increases there is the need to come out with policies geared towards the improvement in the lives of the aged. Government policies such as exemption packages for the ages in the premium payment of the health insurance scheme support as care for the aged should be vigorously implemented. In the case of the women, the maternal health which is one of the Sustainable Development Goals which Ghana is investing towards its achievement by 2030.

Furthermore, population density and migrationpattern willaffect access and provision of housing in the district. There is therefore the need to encourage the use of local materials in the housing industry as well as enhance people’s access to facilities such as potable water, electricity, telecommunication facilities in the district.


Migrants are defined as persons who were enumerated in a place different from where they were born during the last census night. The 2010 PHC sought to find out the place of birth and the number of years a person had lived in a particular place. This section of the plan provides information on the people of Adansi Asokwa District born elsewhere in Ashanti region, or in another region outside Ashanti and birth place outside Ghana in relation to their duration of residence in the district.

Migrants born elsewhere in Ashanti region

As shown in figure 2.3, about 30.5 percent   immigrants born elsewhere in Ashanti region have stayed between (1-4) years in the district as the highest percentage,followed by19.8  percent of immigrants who have stayed between 10 to 19 years and 18.3 percent of immigrants have also stayed between 5 to 9 years for 5-9 years.


Fertility is an important component of population change and it is a determinant of the size and structure of the population. Out of the total number of population 64,211, 18,740 were identified as the number of women in their child bearing age between (15-49 years). Within this age group, the total number of live births in the last 12 months before the census night was recorded as 1,736.

The total fertility rate which is referred to as the average number of children that would be born to a woman by the time she ended childbearing if she were to pass through all her childbearing years conforming to the age-specific fertility rates of a given year was (3.93%). Thus in 2010, the total fertility rate for Adansi Asokwa District was 3.93 births per woman (ie, 18,740 births per 1000 women). Therefore, if 2010 age-specific rates continues unchanged, women in Adansi Asokwa District would have average of 4 children each during their childbearing years.The general fertility rate (also called the fertility rate) is the number of live births per 1,000 women ages between 15-49 in a given year. The birth rate (also called the crude birth rate) indicates thenumber of live births per 1,000 populations in a given year.


Mortality, is one of the three components of population growth, plays an important role in determining the growth of a population. Crude Death Rate refers to the number of deaths per 1000 population in a given year (“crude” because, although deaths occur in the entire population the rate of occurrence is not uniform or evenly distributed among all ages).

The computed crude death rate for the District is 7.82 deaths per 1,000 population, using the reported deaths in the year preceding the census as numerator and the total population of the district as denominator.  According to the 2010 census, the rate is higher than the regional death rate of 5.85 deaths per 1,000 population.

The probability of dying depends on many factors, such as age, sex, race, occupation and social class. The incidence of death can reveal much about a population’s standard of living and health care (Haupt and Kane, 1991). Even though under 5 mortality is relatively high for both sexes, the mortality rate steadily declines and rises among the various age cohorts. In all these instances, males suffer more deaths than females. There is a sharp increase in the number of deaths among the the elderly (70 years and older) according to the 2010 census. But the situation changed from the table below.


Date Created : 2/11/2019 7:02:16 AM