Estimate population figures at state administrative level and different age groups

Estimate population figures at state administrative level and different age groups

A populated place consisting of more than 15 houses − place or area with clustered or scattered buildings and a permanent human population (city

Populated place − place or area with clustered or scattered buildings and a permanent human population (city, settlement, town, village) and by definition has no legal boundaries

Geographic coverage

National

Analysis unit

• Household
• Individual

Universe

18 of the 37 states in Nigeria were selected using procedures described in the methodology report

Kind of data

Sample survey data [ssd]

Sampling procedure

A. Sampling Frame The sampling frame was the 2006 National Population Census. For administrative purposes, Nigeria has 36 states and the Federal Capital Territory. These states are grouped into six geopolitical zones - the North Central, North East, North West, South East, South South and South West. The states in turn are divided into 776 Local Governments. The demographic and political characteristics of the states vary considerably. For example, the number of component local government areas in the states ranges from 8 in Bayelsa State (in the South South) to 44 in Kano State (in the North West). Likewise state populations vary widely from 1.41 million in the Abuja Federal Capital Territory to 9.38 million in Kano State. The National Bureau of Statistics splits the country further into 23, 070 enumeration areas (EAs). While the enumeration areas are equally distributed across the local government areas, with each local government area having 30 enumeration areas, the differences in the number of local government areas across states implies that there are also huge differences in the number of enumeration areas across states. Appendix table 1 summarizes the population according to the 2006 population census (in absolute and proportionate numbers), number of local government areas, and number of enumeration areas in each state .

Given the above, a stratified random sampling technique was thought to be needed to select areas according to population and the expected prevalence of migrants. The National Bureau of Statistics (NBS) provided a randomly selected set of enumeration areas and households spread across all states in the Federation from the 2006 sampling frame. Every state in Nigeria has three senatorial zones (often referred to as North, Central and South or East, Central and West). The NBS sample enumeration areas were distributed such that within each state, local government areas from each senatorial zones were included in the sample, with Local Governments in each state nearly evenly distributed between rural and urban areas. In all, a total of 3188 enumeration areas were selected. These enumeration areas were unevenly spread across States; some states in the North West (Kano, Katsina, and Jigawa), and a few in the South South (Akwa Ibom and Delta) had over 100 enumeration areas selected while others such as Imo and Abia in the South East, and Borno, Gombe and Taraba in the North East, had as few as 20 enumeration areas selected. This selection partially reflected the relative population distribution and number of Local Government Areas in the component states. Annex Table B shows details of the states and geopolitical regions, their shares in population of the country, the number of Local Government Areas and enumeration areas in each state and the number of enumeration areas given in the NBS list that formed the frame for the study.

B. The Sample for the Migration Survey

a. Sample Selection of States, Local Governments and Enumeration Areas Originally, the intention was to have proportionate allocation across all states, using the population of each state in the 2006 Census to select the number of households to be included in the sample. But it was later recognized that this would not yield enough migrant households, particularly those with international migrants, especially as the total number of households that could likely be covered in the sample to was limited to 2000. Consequently, a disproportionate sampling approach was adopted, with the aim of oversampling areas of the country with more migrants. According to Bilsborrow (2006), this approach becomes necessary because migrants are rare populations for which a distinct disproportionate sampling procedure is needed to ensure they are adequately captured. Given the relative rareness of households with out-migrants to international destinations within the 10 year reference period (selected by the World Bank for all countries) prior to the planned survey, sampling methods appropriate for sampling rare elements were desirable, specifically, stratified sampling with two-phase sampling at the last stage.

Establishing the strata would require that there be previous work, say from the most recent Census, to determine migration incidence among the states. However, the needed census data could not be obtained from either the National Bureau of Statistics or the National Population Commission. Therefore, the stratification procedure had to rely on available literature, particularly Hernandez-Coss and Bun (2007), Agu (2009) and a few other recent, smaller studies on migration and remittances in Nigeria. Information from this literature was supplemented by expert judgement about migration from team members who had worked on economic surveys in Nigeria in the past. Information from the literature and the expert assessment indicated that migration from households is considerably higher in the South than in the North. Following this understanding, the states were formed into two strata- those with high and those with low incidence of migration. In all, 18 States (16 in the South and 2 in the North) were put into the high migration incidence stratum while 19 states (18 in the North and 1 in the South) were classified l into the low migration incidence stratum (column C of Appendix Table 1).

The Aggregate population of the 18 states in the high migration incidence stratum was 67.04 million, spread across 10,850 Enumeration areas. Thus, the mean population of an EA in the high migration stratum was 6179. In turn, the aggregate population of the 19 states in the low migration incidence stratum was 72.95 million spread across 12,110 EAs yielding a mean EA population of 6024. These numbers were close enough to assume the mean population of EAs was essentially the same. To oversample states in the high stratum, it was decided to select twice as high a proportion of the states as in the low stratum. To further concentrate the sample and make field work more efficient in being oriented to EAs more likely to have international migrants, we decided to select randomly twice as many LGAs in each state in the high stratum states as in the low stratum states.

Thus, 12 states were randomly selected with probabilities of selection proportionate to the population size of each state (so states with larger populations were accordingly more likely to fall in the sample) from the high stratum states. Then two LGAs were randomly selected from each sample state and 2 EAs per sample LGA (one urban, one rural) to yield a total of 12 x 2 x 2 or 48 EAs in the high stratum states. For the low stratum, 6 states were randomly selected. From each of these, 1 LGA was randomly picked and 2 EAs were selected per sample LGA to give a total of 6 x 1 x 2 or 12 EAs in the low stratum. This yielded a total of 60 EAs for both strata. Given the expected range of 2000 households to be sampled, approximately 67 households were to be sampled from each local government area or 34 households from each enumeration area.

So far, the discussion has assumed two groups of households - migrant and non-migrant households. However, the study was interested in not just lumping all migrants together, but rather in classifying migrants according to whether their destination was within or outside the country. Migrant households were thus subdivided into those with former household members who were international migrants and those with former household members who were internal migrants. Three strata of households were therefore required, namely:

1. Households with an international migrant: at least one person who was a member of the household since Jan. 1, 2000 left to live in an international destination and has remained abroad;
2. Households with an internal migrant: at least one person who was a member of the household since Jan. 1, 2000 left to live elsewhere in Nigeria (outside the sample LGA) and has not returned to the LGA; and
3. Households with no migrant: No member of the household has left to live elsewhere either within or outside the country since Jan. 1, 2000.

The selection of states to be included in the sample from both strata was based on Probabilities of Selection Proportional to (Estimated) Size or PPES. The population in each stratum was cumulated and systematic sampling was performed, with an interval of 12.16 million for the low stratum (72.95 million divided by 6 States), and 5.59 million for the high stratum (67.04 million divided by 12 States). This yields approximately double the rate of sampling in the high migration stratum, as earlier explained. Using a random start between 0 and 12.16, the following states were sampled in the low stratum: Niger, Bauchi, Yobe, Kano, Katsina, and Zamfara. In the high stratum, states sampled were Abia, Ebonyi, Imo, Akwa Ibom, Delta, Edo, Rivers, Lagos, Ondo, Osun and Oyo. Given its large population size, Lagos fell into the sample twice. The final sample, with LGAs and EAs moving from North to South (i.e. from the low to the high stratum states) is presented in Table 1 below.

The sample was concentrated in the South since that is where it was expected that more households have international migrants. It was expected that the survey would still also be reasonably representative of the whole country and of both internal migrant and non-migrant households through weighting the data. To this effect, field teams were asked to keep careful track at all stages of the numbers of people and households listed compared to the number in the

Populated place − place or area with clustered or scattered buildings and a permanent human population (city, settlement, town, village) and by definition has no legal boundaries

Populated place − place or area with clustered or scattered buildings and a permanent human population (city, settlement, town, village) and by definition has no legal boundaries

Additional file 1. Rates of reported cases of measles per 100,000 populations from January 2016 to December 2018 for all LGA in Osun State. This file shows the data from which Fig. 1 was derived. The first column for each year (2016–2018) is the LGA the second is the estimated population of each LGA from the Nigeria 2006 national census the third is the number of reported case for that year in each LGA and lastly the computed incidence rate.

Abstract

Poverty dynamics enables a better appreciation of the extent of poverty over time by distinguishing between households exiting and entering into poverty, those never poor and the persistently poor. However, it has not received much attention in the poverty literature in Nigeria, largely due to the lack of nationally representative panel data that track the poverty status of households over time.

This survey intends to provide indicators for tracking the welfare status of rural households overtime as well as identify the factors influencing this status for potent policy prescriptions.

Geographic coverage

Southwest Zone Osun State Oyo State

Analysis unit

Households

Universe

Rural household heads

Kind of data

Sample survey data [ssd]

Sampling procedure

The frame for the study was the demarcated Enumeration Area (EA) maps produced by National Population Commission for the 2006 Housing and Population Census. These EAs used are part of the ones usually used by National Bureau of Statistics (NBS) for her regular household-based surveys.

A multi-stage sampling technique was adopted for this study for the selection of respondents. The first stage was a random selection of two states of Oyo and Osun from the six states that make-up the Southwest geo-political zone of the country. The second stage involved the random selection of three local government areas (LGAs) from each of the selected state. The third stage was the random selection of ten rural enumeration areas (EAs) from each of the selected LGA. The final stage of the sampling was the systematic selection of ten households from the households listed in each selected EA. Hence, in each state 300 households were interviewed giving a total of 600 households in the two selected states canvassed for the study in the first period but only 582 households could be re-interviewed in the second round. Data from these 582 households were used for analysis in this study.

Sampling deviation

No deviations from sample design

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire is divided into 6 sections:

Section A: Socio- economic/demographic characteristics Section B: Health
Section C: Housing, Utilities And Amenities Section D: Social Capital Section E: Household Consumption Section F: Shocks and Coping Strategies

Cleaning operations

Data editing took place primarily during processing and includes: a) Office editing and coding b) During data entry

Response rate

The response rate is 97%

Sampling error estimates

No sampling error

Data appraisal

No other form of data appraisal

Populated place − place or area with clustered or scattered buildings and a permanent human population (city, settlement, town, village) and by definition has no legal boundaries

Abstract

The 1993/94 National Agricultural Sample Census was undertaken by the Federal Office of Statistics (FOS) in collaboration with the Federal Ministry of Agriculture, Water Resources and Rural Development. It had technical inputs from FAO.

The operation involved the complete listing of household units and households within units. Farming households which for this purpose includes households engaged in crop farming, livestock and fishing were identified from the listing forms. One out of every four farming households was selected for study. A Holding questionnaire which dealth with farm practice and other agricultural structural issues was administered to all selected households. Also the basic questionnaire, that is the General Household Survey questionnaire, dealing with socio-economic activities of the household (health, education, detailed demographic information, housing status, employment, etc) was applied to all selected households.

The three principal objectives of the census were: a) To provide structural data on Agriculture in Nigeria mostly on those aspects that do not change frequently. In the context of this census, agriculture has been defined to include crop production (temporary and permanent), livestock rearing, keeping of poultry and fishing and forestry. b) To obtain the socio-economic activities, health and educational status, detailed demographic and housing status formation on households, household heads and household members. This would provide Local Government Areas with baseline statistics. c) To obtain production figures at the state level. The Census was in two phases: the first was to meet its first two objectives while the second phase was to meet its third objective. The attached report only deals with the phase 1 of the census.

Geographic coverage

The NASC Phase 1 covered 36 EAs in each LGA. At that time, 540 LGAs had been gazetted by the National Population Commission. Of these 18 LGAs on basis of their relative sizes compared to other LGAs in their respective states were split into sub-LGAs each. Therefore, there were 526 strata each with 36 sample EAs giving a total national sample of 20 232 EAs. Out of each EA, 12 households were selected for study giving a total national sample of 242 794 households.

The 540 LGAs gazetted did not reflect the last exercise of Government to creat new LGAs. Therefore some LGAs on the gazette were in fact two or more LGA8 on the ground. Since for such LGAs it was not possible at HQ to sort out the frame of EAs into their respective LGAs, it became necessary to select multiples of sample of EAs in the gazetted LGA. The selection of additional EAs was a condition- exercise and a total of about 59 additional samples (ach of 26 EA's) were added to the 242,784 indicated.

The pretest was in two phases in line with the design anticipated for the census. The phase one operation was carried out in five pretest states, namely, Anambra, Bauchi, Kano, Osun and Ondo.

Sampling procedure

Sample Design The Sampling Scheme adopted was a two phase stage sampling selection: Phase One involved three levels of stratification.

The basic objective of Phase I was to provide some baseline data on every local Government. Area (LGA) in Nigeria. The LGA thus became the primary of first level of stratification. The EAs in each LGA were stratified into urban or rural, which thus the second level of stratification, Thus, in listing the EAs within each LGA the urban EAs were listed first, followed by the rural EAs. Systematic sampling from the EA list was to ensure that. the sample was distributed between urban EAs in the same proportion as for the whole population, without the need for calculating urban and rural sampling rates separately.

The third level of stratification, again implicitly, reflected general agro-ecological variation. Thus within the rural sector, the listing of EA in each LGA prior to selection was in a serpentine order on the map. 36 EAs were to be selected in each LGA using systematic selection with probability proportional to site. 12 households were selected per EA for study, the household being the primary sampling unit.

Sample Selection and the Associated Problems

The methodology of sample selection for NASC was as contained in the survey design by Chris Scott, FAO consultant. The preferred design which had several levels of stratification as state and Local Government had the Local Government further stratified into urban and rural sector,with additional level ofstratification, this time implicitly imposed on the rural sector to stratify it by cropping pattern. This design was believed to have the twin advantage of marrying most of what was good in the previous sample while at the same time remaining simple in application with regard to methodology of sample selection and estimation procedure. Over all it was believed that the resulting sample will provide us with better estimates than before.

The following steps were taken in the selection process. (i) Stratification or grouping of EAs in each Local Government Areas (LGA) into urban and rural (ii) The grouping of area within the rural EAs that produce similar crops together in a systematic manner until all the EAs within the rural sector of each LGA was strung together. (iii) The selection of 36 EAs systematically in a continious manner from each Local Government Area. By this implicit stratification, the urban EAs will appear in proportion to their weight. Rural EAs with different cropping will also appear according to their presence or weight.

To facilitate the work a two week training of the staff for the sample selection was put in place. During the period, effort was also intensified to get the EAs frame from the National Population Commission (NPC).It was however discovered that the format in which the frame was compiled by NPC did not include areas by locality. This made both the distinction between urban and rural EAs blurred and affected rural stratification by crop. At this junction the methodology for sample selection was reviewed. The above method was then replaced by a simple straight forward systematic selection of EAs via the cumulation and selection of households which are contained in the frame as supplied by NPC. Under this method 36 EAs were in most cases systematically selected from each LGA. However, due to the marked difference or variance in the sizes of EAs, it was decided that some criteria was needed to separate urge LGAs from the average ones to avoid some LGA being relatively over sampled or under sampled, with these 36 EAs were selected in each LGA while 72,108 EAs were selected in large EAs.

Soon after the rule guiding the sample selection for this revised method was established, the proper selection started. Once the initiall part of the frame came out of the computer, the work of selecting sample was done simultaneouslv with computer production of the frame. As the sample list of EAs per state were compiled arrangement was made to collect the corresponding sketch maps from NPC.

There were various problems in the course of compiling the frame for NASC. These were.

(i) Repeated requests and visits to NPC before the frame from which the sample list of EAs was selected. (ii) The frame obtained was somewhat defective and incomplete. It was about 95% complete and listing of EAs did not contain listing of localities. (iii) Because of the incompleteness of the frame a few LGAs in a few of the states were missing and so sample list for each LGA could not be obtained. Also the non-listing of EAs by localities in the frame presented some sampling problems leading to the review of the methodology of sample selection . (iv) Difficulties arising from further state creation was also encountered but it was easier to resolved since in nearly all cases it was a matter of reallocation of LGAs within the affected, state, except where they were subdivided and boundaries were not clearly defined. (v) Where LGAs were split there was the need to draw additional samples.

Mode of data collection

Face-to-face [f2f]

Research instrument

Listing Questionnaire: This was used to list households in the selected EA and to obtain data on crops grown, livestock/poultry kept and fishing activities.

General Household Questionnaire: This was used for sample household in Phase I and contained data on socioeconomic characteristics of each member of the household as well as housing conditions for the household.

Holding Questionnaire: This was for every holding identified as being operated by a member of the sample households in Phase 1 EA. Data was collected in respect of general farm practice, area of holding, tenure, use of inputs, farm implements, kinds of livestock/ poultry kept, access to credit and marketing channels. Most responses on the questionnaire were precoded using international standard classifications.

Cleaning operations

Data Processing: Questionnaires were retrieved from the field for processing at Headquarters. The retrieved questionnaires were first edited and coded manually by trained statistical clerks before being sent to the data entry clerks for computerisation. After data entry had been completed and checked by the programmers, the data diskettes were sent to the Statistician for computer editing and tabulation. The programme for Data Entry was written by FOS programmers, while editing and tabulation programmes were written by an FAO Consultant who worked with FOS for about six months. The FAO Consultant did a lot in building computer capability among the staff of the Division. All aspects Of Data Processing were carried out by our statisticians and programmers.

Data appraisal

Spot/Quality Checks:

Right from the

Demographic data of respondents of the community.

Supplementary Material 1.

Clinical spectrum observed from filarial infected members of the surveyed population.

Socio-demographic characteristics of respondents according to their residence.

Association of socio-demographic characteristics and level of SRHC by their residence.

In the school year 2018/2019, there were roughly 513 thousand senior secondary school teachers in Nigeria, in both private and public schools. The state of Lagos counted more than 65 thousand teachers, the largest number nationwide. In the same year, there were about 27 thousand senior secondary schools in Nigeria. The state of Oyo alone counted around four thousand senior secondary schools, the highest number in the country.

IntroductionSensuality, an essential component of sexuality, is the enjoyment, expression, or pursuit of physical and sexual pleasure or satisfaction. Sensuality expression of women over 50 is under-researched and often ignored, making it difficult to have a scientific basis to develop age-appropriate healthy-ageing programmes for this group in Nigeria. An exploratory study was conducted to explore the lived experiences of the expression of sensuality of Nigerian women over 50 and the meaning they attach thereto.MethodologyAn Interpretative Phenomenological Analysis approach was used to collect and analyze data from 17 female teachers from three public secondary schools in Osun state, Nigeria, to represent a homogenous group of professional women over the age of 50. A semi-structured questionnaire was used to obtain qualitative data that was thematically analyzed.FindingsFour superordinate themes emerged: ‘Self-reinvention to camouflage ageing realities for sensuality expression’; ‘Embracing own sensuality’; ‘Yearning for old self’; and ‘Loss of interest in romantic relationships’, with various subordinate themes.ConclusionThese finding provide the basis to develop age-appropriate healthy-ageing programmes for this group, and a baseline for further sexual health research among this group of women in Nigeria, who are often overlooked or considered asexual due to their being beyond the reproductive age.