Demographic and Socio-Economic Trends in the ACDIS
By William Muhwava Makandwe Nyirenda
Monograph Series No. 2 January 2008
Africa Centre for Health and Population Studies, Somkhele 1
South Africa
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This monograph is not copyrighted and can be freely quoted as long as the source is duly acknowledged. The following citation is suggested for this monograph:
Muhwava W. and Nyirenda M (2007) Demographic and Socio-Economic Trends in the ACDIS, Monograph No 2. Africa Centre for Health and Population Studies, Mtubatuba, South Africa.
Monograph Series No.2 January 2008
Published by: Africa Centre for Health and Population Studies P.O. Box 198 Mtubatuba 3935 South Africa Telephone: +27 (0)35 550 7500 Fax: +27 (0)35 550 7565 Email:
[email protected] URL: http://www.africacentre.ac.za Printers:
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CHAPTER 1: Introduction 1.0 Introduction The Africa Centre Demographic Information System (ACDIS) has generated longitudinal demographic data in rural KwaZulu-Natal from January 2000 to date. These data permit the examination of demographic trends in the surveillance area. In this monograph, detailed analyses of population dynamics are presented. First, changes in the population size are presented. Second, fertility, mortality and internal migration trends are analysed. Other important characteristics of the population, for example, education and employment are also presented. 1.1 Background to the DSS The DSS is a system of continuously monitoring the population of a defined geographic area and recording vital events at regular but short intervals. In the case of the Africa Centre, the data are collected every six months. The Africa Centre Demographic Information System (ACDIS) covers all individuals who are members of households based at homesteads or facilities within a defined geographical area referred to as the Demographic Surveillance Areas (DSA). Within this system, three primary subjects are observed longitudinally: bounded structures, households and individuals. Membership and residency are features of individuals and households respectively (Hosegood and Timaeus, 2006). Membership refers to The information is updated twice a year through field worker visits and interview of one informant per household. Events recorded include individual events (births, deaths, migration, pregnancies, marriage), household events (household formation, migration, change of household head), and events affecting homesteads (start of a new building, change of a building’s main purpose or its owner). Additional data are collected in standard modules (e.g. an annual household socioeconomic questionnaire) or special modules (a child grant questionnaire; illness and death). The details of data collection and management systems are provided in Monograph I. 1.2 Data Source The data used in this monograph are from the DSS for the period 2000 to 2006. The first round of the Africa Centre demographic surveillance system took place in 2000. The ACDIS collects data on births, deaths, demographic- and socio-economic characteristics. Initially, the household surveillance took place three times a year, but after two years this was reduced to two rounds. However, it should be noted that this change did not in any way compromise the quality of the data, as events were captured for a six-month period rather than a four-month period before the next round. The number of homesteads/bounded structures in ACDIS has increased from 11078 in Round 1 in the first half of 2000 to 13010 in 2006. Refusal rate has varied between a low of 0.03% to 1.88%. The total population covered is more or less stable: 82,599 in 2000, to 85,957 in 2006. Over the years the number of resident people has declined a little, but the number of non-residents has increased, highlighting how migration remains an important component of the population dynamics of the study area. 1.3 The Project Area The Africa Centre Demographic Surveillance area covers the southern part of the tribal area of Mpukunyoni, the most populous and least mountainous part of the Hlabisa Municipality and Inyala/Mtuba Transitional Local Council (TLC), and includes the township of KwaMsane.and Indlovu Township. It is approximately 438 km² in size and is sharply demarcated by distinct boundaries: large perennial rivers, nature reserves, forestry areas, and commercial farmland on all but its northern boundary. As a result, the area is a well-circumscribed geographical unit, allowing
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clear definition of the survey population. The population is typical of rural populations in KwaZuluNatal and, to a lesser extent, of rural black populations elsewhere in South Africa. People in the area are employed mostly in the commercial towns like Richards Bay, St Lucia and Empangeni; and agricultural sugar estates and forestry plantations which are in the surrounding areas. This is a mostly a cash economy and very little subsistence farming is practiced. Very few households that are engaged in agriculture produce sugarcane which is sold to the local sugar milling company. 1.4 Objectives of the Report This monograph is the second in a series which aims to give descriptive results of the ACDIS data. The report presents the demographic profile of the study population of ACDIS, describing individual and household characteristics, fertility, mortality, and migration patterns. In general, the objectives of the report are: • To describe the demographic trends in the ACDIS from 2000 to 2005. • To provide the changes in the population structure as a results of changes in mortality, fertility and migration. • To examine the impact of HIV/AIDS on population parameters, that is, population composition, population size and mortality.
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CHAPTER 2: Population Composition and Change
The profile of individuals enumerated in households in the ACDIS from Round 1 in January 2000 to Round 15 in 2006 are presented in this chapter. This includes characteristics of the age-sex pattern, sex ratio, population change and age dependency ratio. In presenting population totals, two concepts are usually used, de facto and de jure populations. The de facto population is defined as the people who were present in the household on the night before the interviewer visited. The de jure population is defined as the members who belong to households within a given area at a given time. In populations with high mobility patterns, these two concepts are difficult to discern and therefore two concepts which are easily observable are used, resident and non-resident populations. These concepts are dealt with in detail in Monograph 1 and Hosegood, V. and I.M. Timaeus (2005). Briefly, the resident population consists of people who would have spent most of their nights at the bounded structure in the six months since the last round. The non-resident population consists of people who live elsewhere for most of the time, and whenever they visit the households at their bounded structure, they always leave again. These concepts are applied throughout this monograph. 2.1 Population Size and Growth The mid-year population for each of the years is presented in Table 1 and Fig 1. The numbers are presented separately for non-resident and resident populations. Table 1: Total Mid-Year Population of the DSA 2000-2006 Year Non-Resident Resident 2000 16,816 65,783 2001 24,859 64,643 2002 27,929 67,900 2003 27,359 67,678 2004 27,812 61,368 2005 27,962 56,554 2006 29,166 56,791
Total 82,599 89,502 95,829 95,037 89,180 84,516 85,957
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Figure 1: Non-Resident, Resident and Total Population 100,000
95,829
95,037
89,502
90,000
89,180 85,957
84,516
82,599
80,000
Population
70,000
65,783
67,900 64,643
67,678 61,368
60,000
56,554
56,791
50,000 40,000 27,929
30,000 20,000
24,859
27,359
27,962
27,812
29,166
16,816
10,000 0 2000
2001
2002
2003
2004
2005
2006
Year Non-Resident
Resident
Total
The total mid-year population in the DSA has increased in the initial years. The sharp increase from the first year to the second represents the inclusion of household members who might have been omitted in the first enumeration. This is to be expected, as it took more than 18 months to reach everyone for the first time. The highest recorded mid-year population in the DSA was in 2002 and thereafter there has been a gradual decrease in the total population in subsequent years. The number of non-residents has been gradually increasing indicating that although people are moving out of the DSA for various reasons, they still maintain their membership to households in the DSA. Conversely, the number of residents has been declining. The annual population growth rates are presented in Fig 2. These rates would be able to show the year-on-year changes in the mid-year population.
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Figure 2: Population Growth Rates 2000-2006 40.0 30.0
Growth Rate
20.0 10.0 0.0 2000.5
2001.5
2002.5
2003.5
2004.5
2005.5
-10.0
Year -20.0 -30.0 -40.0
Non-Resident Females
Non-Resident Males
Resident Females
Resident Males
The largest increase is observed among the non-resident population from 2000 to 2001 where the male population grew by 30% while the female population increased by 34%. It should be noted that these large increases could be attributed to better coverage or inclusion of the non-resident population who might have been omitted in the first round. It has been noted that it took about 18 months to register everyone in the DSA. That pattern of positive increase continued from 2001 to 2002, where the non-resident population increased by 10.4% for females and 11.5% for males. For the non-resident population, net decrease was recorded between 2002 and 2003. For the last three years of the surveillance, the non-resident population has increased, although marginally between 2004 and 2005. The trend is similar for both males and females. For the resident population, there was net decrease between 2000 and 2001, while a substantial increase was recorded between 2001 and 2002. Thereafter, net decreases are recorded with the largest loss being over 10% between 2003 and 2004. However, in the last year, net increase for the resident population has been noted. Similar trends are observed for both males and females. For the total population, the first two years recorded positive growth, while the subsequent three years recorded negative growth and in the last year, population increase of 1.6% has been noted. The pattern of population change shows the effects of migration, where movements in and out of the DSA are high and affect population sizes significantly. It can be noted that there was massive out-migration from the DSA in 2004 and 2005. 2.2 Age and sex distributions This section presents two aspects which are important in demographic analysis. The first section analyses age composition and the second section analyses sex composition. The age-sex composition of a population is important in demographic analysis for various reasons. Age-sex structure is the product of past trends in fertility, mortality and migration and influences in turn the current levels of birth, death and migration rates. Moreover, the age-sex composition of a population has significant implications for the reproductive potential, manpower supply, school attendance, household formation, child-mother health care and family planning service delivery, 8
ageing etc. It also provides a basis for estimating requirements for various essential goods and services of a community. The age and sex composition of a population is critical for preparing population estimates as well as projection of households, school enrolment and the labour force, which is in turn urgently needed for the formulation of effective socio-economic development plans in different sectors considering the requirements of population of different age groups and sexes. The age and sex distributions of the population of the DSA for the complete years of surveillance are presented in Table 2. Table 2: Age and sex distributions of resident population, ACDIS, 2000-2006. Age Group
0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Total
2000 Femal e 4865 5358 5532 5467 4448 3699 2962 2550 2053 1313 1178 932 939 825 709 236 192 209 43467
2001
Male 4782 5434 5500 5143 4054 3277 2436 2178 1720 1289 936 713 560 376 396 164 100 74 39132
Female 5015 5761 5871 6105 4959 4194 3276 2689 2342 1461 1284 890 1044 808 798 297 222 212 47228
2002
Male 4994 5726 5888 5760 4386 3707 2722 2279 1850 1413 1004 722 656 376 400 186 125 80 42274
Femal e 5522 6120 6233 6415 5451 4625 3560 2779 2468 1642 1347 893 1088 782 823 381 237 220 50586
Male 5496 6156 6116 6137 4852 3975 2976 2361 1982 1516 1068 737 679 398 385 204 135 69 45242
2003 Female 5060 6039 6213 6324 5650 4519 3573 2740 2473 1734 1382 892 1084 765 831 436 210 243 50168
2004 Male 5087 6057 6151 6031 5076 3951 3041 2238 1989 1530 1137 690 711 389 371 232 118 70 44869
Females 4503 5633 5919 5926 5347 4138 3180 2572 2274 1790 1274 978 960 754 809 484 186 234 46961
2005 Male 4644 5659 5836 5786 4943 3683 2738 2086 1846 1425 1083 718 638 387 316 250 104 76 42218
Female 4246 5331 5553 5670 5293 3843 2999 2396 2096 1765 1161 1063 794 779 699 531 181 217 44617
2006
Male 4383 5242 5538 5496 4866 3544 2581 1904 1655 1307 1026 720 552 406 245 253 100 80 39898
Femal e 4340 5239 5621 5622 5489 3869 3174 2404 2075 1829 1213 1076 727 849 640 595 205 225 45192
Male 4454 5199 5566 5624 5141 3643 2773 1956 1638 1362 1018 740 535 443 235 247 108 82 40764
For all the years, the total male population is lower than the female population. From the data presented in Table 2, measures of age and sex composition are computed. First, population pyramids are presented in Fig 3. For comparative purposes, the percentages presented are calculated using the total population of both sexes combined. The advantages of presenting the pyramid in this format are discussed in Newell (1988).
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Figure 3: Population Pyramids for the Mid-Year Total Population 2002
10-14
10-14
5-9
5-9
0-4
0-4 0
Percent
Percent
2004
2006
Male
Female
Male
Female
Percent
8
7
6
5
4
3
2
0-4 0
5-9
0-4 0
5-9
1
10-14
2
15-19
10-14
3
20-24
15-19
4
25-29
20-24
5
30-34
25-29
6
35-39
30-34
7
40-44
35-39
8
45-49
40-44
8
50-54
45-49
7
55-59
50-54
6
60-64
55-59
5
65-69
60-64
4
70-74
65-69
3
75-79
70-74
2
80-84
75-79
1
80-84
1
85+
0
0
1
2
3
4
5
6
7
85+
8
8
15-19
7
20-24
15-19
6
25-29
20-24
4
30-34
25-29
3
30-34
2
35-39
0
35-39
1
40-44
2
45-49
40-44
3
50-54
45-49
4
50-54
5
55-59
6
55-59
7
60-64
8
60-64
7
65-69
6
70-74
65-69
5
70-74
4
75-79
3
75-79
2
80-84
1
80-84
0
85+
1
Female
85+
0
1
2
3
4
5
6
7
8
Male
Female
Male
5
2000
Percent
The population pyramids exhibit the characteristics of a developing country, where there are still large proportions of children under the age of 15 years. However, rather than a typical expansive pyramid which shows a broad bases as a result of high fertility, the pattern shows some changes at the base showing the effect of declining fertility. The population pyramids show a transitioning to lower fertility rates and there is a decrease in the number of children aged 0-4 years compared to 10
cohorts of children born earlier. In the pyramid for 2006, the thinning of the base is quite evident. This effect is shown graphically in Fig 4. Fig 4: Percent Age Distribution by Sex 2000-2001 16.0
14.0
12.0
Percent
10.0
8.0
6.0
4.0
2.0
0.0 2.5
7.5
12.5 17.5 22.5
27.5 32.5 37.5 42.5 47.5 52.5 57.5 62.5
67.5 72.5 77.5 82.5
85
Mid-Point
2000 Females
2000 Males
2001 Females
2001 Males
2002 Females
2002 Males
2003 Females
2003 Males
2004 Females
2004 Males
2005 Females
2005 Males
2006 Females
2006 Males
The consistency in the pattern of age distribution for both sexes is striking. It is evident that for all the years, the proportion in the age group 0-4 is less than those in the 5-9 age group. In other cases, the proportions in the 5-9 age group are less than the those in the 10-14 age group. This clearly shows the effect of declining fertility where the proportion of young children is decreasing as the number of births fall. There is a possibility of that the decrease in the proportion of children can also be the added result of increase child mortality due to AIDS-related mortality. Another important observation to make is that the proportion of young children in the total population has been decreasing from 2000 to 2006. While in 2000, 11.2% of the population were female children and in 2006 this had decreased to 9.6% in 2006. The same observation can be made of males where the proportion decreased from 12.2% in 2000 to 10.9% in 2006. Beyond childhood years, the percent age distributions show smooth declining trends by age. It can be observed that the patterns by age are similar for the time periods although the magnitude changes over time. So, the effects of mortality and migration are not significantly altering the population structure or shape of the DSA. In Fig 5, time series charts are used to show the changes in the age composition of the population. Stacked area charts are used. The graphs can also be used to show the quality of age reporting.
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Figure 5: One-Hundred Percent Stacked Area Chart Showing Percent Population Distribution by Broad Age Groups
Males
Females 100
100
65+ 45-65
80
65+ 45-65
80
25-44
25-44
60
60
15-24
15-24
40
40
20
20
