Sukuma was the largest ethnic group in Tanzania as of 2021. Around **** percent of the surveyed population identified themselves as from the Bantu ethnic group. Nearly *** percent belonged to the Ha group, while *** percent were from the Gogo group. About *** percent of the respondents identified themselves as Tanzanians only or reported that they don't think of themselves in terms of ethnic communities, cultural groups, or tribes. Overall, around *** ethnic groups are estimated to live in Tanzania.

The Maasai of northern Tanzania, a semi-nomadic ethnic group predominantly reliant on pastoralism, face a number of challenges anticipated to have negative impacts on child health, including marginalisation, vulnerabilities to drought, substandard service provision and on-going land grabbing conflicts. Yet, stemming from a lack of appropriate national survey data, no large-scale comparative study of Maasai child health has been conducted. Savannas Forever Tanzania surveyed the health of over 3500 children from 56 villages in northern Tanzania between 2009 and 2011. The major ethnic groups sampled were the Maasai, Sukuma, Rangi, and the Meru. Using multilevel regression we compare each ethnic group on the basis of (i) measurements of child health, including anthropometric indicators of nutritional status and self-reported incidence of disease; and (ii) important proximate determinants of child health, including food insecurity, diet, breastfeeding behaviour and vaccination coverage. We then (iii) contrast households among the Maasai by the extent to which subsistence is reliant on livestock herding. Measures of both child nutritional status and disease confirm that the Maasai are substantially disadvantaged compared to neighbouring ethnic groups, Meru are relatively advantaged, and Rangi and Sukuma intermediate in most comparisons. However, Maasai children were less likely to report malaria and worm infections. Food insecurity was high throughout the study site, but particularly severe for the Maasai, and reflected in lower dietary intake of carbohydrate-rich staple foods, and fruits and vegetables. Breastfeeding was extended in the Maasai, despite higher reported consumption of cow's milk, a potential weaning food. Vaccination coverage was lowest in Maasai and Sukuma. Maasai who rely primarily on livestock herding showed signs of further disadvantage compared to Maasai relying primarily on agriculture. We discuss the potential ecological, socioeconomic, demographic and cultural factors responsible for these differences and the implications for population health research and policy.

aNumbers in square brackets are standard deviations.Descriptive Statistics for Households Contributing Child Health Data by Ethnicity.

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, Round 7 (2016-2018) 34 countries, and Round 8 (2019-2021). The survey covered 39 countries in Round 9 (2021-2023).

Geographic coverage

National coverage

Analysis unit

Individual

Universe

Citizens of Tanzania who are 18 years and older

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

Tanzania - Sample size: 2,400 - Sample design: Nationally representative, random, clustered, stratified, multi-stage area probability sample - Stratification: Region and urban-rural location - Stages: PSUs (from strata), start points, households, respondents - PSU selection: Probability Proportionate to Population Size (PPPS) - Cluster size: 8 households per PSU - Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval - Respondent selection: Gender quota filled by alternating interviews between men and women; respondents of appropriate gender listed, after which computer randomly selects individual - Weighting: Weighted to account for individual selection probabilities - Sampling frame: 2012 National Population and Housing Census produced by the Tanzania National Bureau of Statistics

Mode of data collection

Face-to-face [f2f]

Research instrument

The Round 9 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

Response rate

Response rate was 92%.

Sampling error estimates

The sample size yields country-level results with a margin of error of +/-2 percentage points at a 95% confidence level.

Information about the ethnic affiliation(s) and characteristics of a human population. Includes, for example, information about: the ethnic groups located within a geographic region, their community social structures, their mutual associations and conflicts with other groups, their historic roles and influence, and the physical distribution of their members. Ethnic groups are human populations whose members identify with each other, usually on the basis of having a common cultural traditions and heritage (for example: as distinguished by customs, language, religious practices, or common history) or a presumed common genealogy or ancestry.

We aim to provide a powerful reference set for genome-wide association studies (GWAS) in African populations. Our pilot study to sequence 100 individuals each from Fula, Jola, Mandinka and Wollof from the Gambia to low coverage has been completed - this first part of the main effort will make available low coverage WGS data for 400 individuals from multiple ethnic groups in Burkina Faso, Cameroon, Ghana and Tanzania. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

We aim to provide a powerful reference set for genome-wide association studies (GWAS) in African populations. Our pilot study to sequence 100 individuals each from Fula, Jola, Mandinka and Wollof from the Gambia to low coverage has been completed - this first part of the main effort will make available low coverage WGS data for 400 individuals from multiple ethnic groups in Burkina Faso, Cameroon, Ghana and Tanzania. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Adjusted odds ratios are adjusted for hunger season and a random intercept for village. See File SI2 for details on the Household Food Insecurity Access Scale.***p

Frequent and unregulated use of antimicrobials (AM) in livestock requires public health attention as a likely selection pressure for resistant bacteria. Studies among small-holders, who own a large percentage of the world’s livestock, are vital for understanding how practices involving AM use might influence resistance. We present a cultural-ecological mixed-methods analysis to explore sectors of veterinary care, loosely regulated AM use, and human exposure to AMs through meat and milk consumption across three rural to peri-urban Tanzanian ethnic groups (N = 415 households). Reported use of self-administered AMs varied by ethnic group (Maasai: 74%, Arusha: 21%, Chagga: 1%) as did consultation with professional veterinarians (Maasai: 36%, Arusha: 45%, Chagga: 96%) and observation of withdrawal of meat and milk from consumption during and following AM treatment (Maasai: 7%, Arusha: 72%, Chagga: 96%). The antibiotic oxytetracycline was by far the most common AM in this sample. Within ethnic groups, herd composition differences, particularly size of small-stock and cattle herds, were most strongly associated with differences in lay AM use. Among the Arusha, proxies for urbanization, including owning transportation and reliance on “zero-grazing” herds had the strongest positive associations with veterinarian consultation, while distance to urban centers was negatively associated. For Maasai, consultation was negatively associated with use of traditional healers or veterinary drug-shops. Observation of withdrawal was most strongly associated with owning technology among Maasai while Arusha observance displayed seasonal differences. This “One-Health” analysis suggests that livelihood and cultural niche factors, through their association with practices in smallholder populations, provide insight into the selection pressures that may contribute to the evolution and dissemination of antimicrobial resistance.

Adjusted odds ratios are adjusted for child age, child sex, hunger season and a random intercept for village.+ p

We aim to provide a powerful reference set for genome-wide association studies (GWAS) in African populations. Our pilot study to sequence 100 individuals each from Fula, Jola, Mandinka and Wollof from the Gambia to low coverage has been completed - this first part of the main effort will make available low coverage WGS data for 400 individuals from multiple ethnic groups in Burkina Faso, Cameroon, Ghana and Tanzania. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Adjusted odds ratios are adjusted for child age, child sex, hunger season and a random intercept for village.*p

We aim to provide a powerful reference set for genome-wide association studies (GWAS) in African populations. Our pilot study to sequence 100 individuals each from Fula, Jola, Mandinka and Wollof from the Gambia to low coverage has been completed - this first part of the main effort will make available low coverage WGS data for 400 individuals from multiple ethnic groups in Burkina Faso, Cameroon, Ghana and Tanzania. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Adjusted B coefficients are adjusted for child age, child sex, hunger season and a random intercept for village.*p

The TAZAMA Health and Demographic Surveillance System (HDSS) study site is located in the Kisesa and Bukandwe rural electoral wards in the Magu district of the Mwanza Region in Northern Tanzania. The two wards are comprised of six villages. There is one health center and five dispensaries (3 public and 2 private) in the study area. The two wards have eleven government primary schools (at least one in each village) and two secondary schools. Both Mwanza city and Magu town are accessible to residents; buses run along the main road and take about an hour and a half to get to Mwanza. Most of the residents are subsistence farmers; a lot of surplus agricultural produce is traded in Mwanza, which is Tanzania's second city. In the year 2012, the research study covered a population of about 30,000 people who live in the Kisesa and Bukandwe wards. The majority of the residents (about ninety five per cent) belong to the Sukuma ethnic group. The DSS collects information on births and deaths and movements in and out of the households. It helps researchers to understand the population dynamics in the study area including fertility, mortality and migration patterns. It provides information on the structure of families that live together. The DSS study is also used to identify people who are eligible to participate in the serological surveys (the right age group, and continuously resident rather than just visiting). It provides the data for calculating the denominators for demographic rates. The objectives of this study are as follows: (1) to improve understanding of the dynamics of the HIV epidemic; (2) to assess the demographic, social and economic impacts of the HIV/AIDS epidemic; (3) to evaluate the effects of national prevention, treatment and care interventions as implemented in Kisesa Ward; (4) to measure child and adult mortality and fertility in the general population and by HIV status; (5) to asses the leading causes of death through verbal autopsy; (6) to assess changes in the family structure due to HIV epidemic; and (7) to provide reliable data for district health planning.

We aim to provide a powerful reference set for genome-wide association studies (GWAS) in African populations. Our pilot study to sequence 100 individuals each from Fula, Jola, Mandinka and Wollof from the Gambia to low coverage has been completed - this first part of the main effort will make available low coverage WGS data for 400 individuals from multiple ethnic groups in Burkina Faso, Cameroon, Ghana and Tanzania. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The initial (Round 1) survey covered 7 countries.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by: - using random selection methods at every stage of sampling; - sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level. The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages: Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries, they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Mode of data collection

Face-to-face [f2f]

FGDs per village, district, division and ethnic groups.

Study sites and major pastoral ethnic groups.

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countires and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. The 18 African countries covered in Round 3 (2005-2006) are:

Benin, Botswana, Cape Verde, Ghana, Kenya, Lesotho, Madagascar, Malawi, Mali, Mozambique, Namibia, Nigeria, Senegal, South Africa, Tanzania, Uganda, Zambia and Zimbabwe

Round 4 (2008) surveyed citizens in 20 countries. The survey covered 34 countries in Round 5 (2011-2013), 36 countries in Round 6 (2014-2015) and 34 countries in Round 7 (2016-2018).

Geographic coverage

The survey has national coverage in the following 18 African countrires: Benin, Botswana, Cape Verde, Ghana, Kenya, Lesotho, Madagascar, Malawi, Mali, Mozambique, Namibia, Nigeria, Senegal, South Africa, Tanzania, Uganda, Zambia and Zimbabwe

Analysis unit

Households and individuals

Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

Kind of data

Sample survey data

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalised settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design: Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages: Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewers alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Further information on sampling protocols, including full details of the methodologies used for each stage of sample selection, can be found in Section 5 of the Afrobarometer Round 5 Survey Manual

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for Round 3 addressed country-specific issues, but many of the same questions were asked across surveys. The survey instruments were not standardized across all countries and the following features should be noted:

• In the seven countries that originally formed the Southern Africa Barometer (SAB) - Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe - a standardized questionnaire was used, so question wording and response categories are the generally the same for all of these countries. The questionnaires in Mali and Tanzania were also essentially identical (in the original English version). Ghana, Uganda and Nigeria each had distinct questionnaires.

• This merged dataset combines, into a single variable, responses from across these different countries where either identical or very similar questions were used, or where conceptually equivalent questions can be found in at least nine of the different countries. For each variable, the exact question text from each of the countries or groups of countries ("SAB" refers to the Southern Africa Barometer countries) is listed.

• Response options also varied on some questions, and where applicable, these differences are also noted.