Mozambique Population: Maputo City data was reported at 1,273,076.000 Person in 2017. This records an increase from the previous number of 1,257,453.000 Person for 2016. Mozambique Population: Maputo City data is updated yearly, averaging 1,194,121.000 Person from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 1,273,076.000 Person in 2017 and a record low of 1,111,638.000 Person in 2007. Mozambique Population: Maputo City data remains active status in CEIC and is reported by National Statistics Institute. The data is categorized under Global Database’s Mozambique – Table MZ.G003: Population: by Region.

Mozambique Population: Maputo data was reported at 1,858,597.000 Person in 2017. This records an increase from the previous number of 1,782,380.000 Person for 2016. Mozambique Population: Maputo data is updated yearly, averaging 1,506,442.000 Person from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 1,858,597.000 Person in 2017 and a record low of 1,225,489.000 Person in 2007. Mozambique Population: Maputo data remains active status in CEIC and is reported by National Statistics Institute. The data is categorized under Global Database’s Mozambique – Table MZ.G003: Population: by Region.

Maputo was the most populated city in Mozambique as of 2020. Around *** million people lived in the country's capital. Other *** thousand individuals dwelled in the neighboring Matola, which is part of Maputo's metropolitan area. Overall, Mozambique had a total population of over ** million people as of the same year.

Abstract

The 2008 MICS aims essentially to do the following: - Provide up-to-date information for assessing the situation of children and women in Mozambique. - Contribute to assessing the Government Five-Year Programme 2005–2009 and the Action Plan for the Reduction of Absolute Poverty 2007–2009 (PARPA II), thus allowing an analysis of progress relative to a series of targets established in the PARPA II monitoring matrix. - Provide the data necessary to monitor progress towards the Millennium Development Goals (MDGs) and the goals of A World Fit for Children, as well as progress towards other internationally agreed targets. - Serve as a fundamental source of information for the Government on the country’s stage of development as it draws up its next five-year programme. - Contribute to the improvement of data and monitoring systems in Mozambique and strengthen specialist technical expertise in the design, implementation and analysis of these systems.

Kind of data

Sample survey data [ssd]

Sampling procedure

The universe defined for this survey included all households living in individual homes in Mozambican territory. It excluded households living in collective homes (barracks, hotels, student residences, etc.), the homeless, and diplomats living in embassies/representations.

The MICS 2008 sample was obtained from the preliminary data and the cartography of the 2007 Census. Selection of the MICS 2008 sample followed a two-stage plan: 1) select the Primary Sampling Units (PSU) or Enumeration Areas (EAs); 2) select households within the sample EAs and, within these, exhaustively select units of analysis (that is, women aged 15–49 and children under five).

Thus, the MICS sample covered 715 PSUs (or EAs) selected systematically, with probability proportional to the size of each urban or rural stratum within each province. In each of the 715 PSUs 20 households were selected, which resulted in a total national sample of 14,300 households. Of the 14,300 households, 6,160 were urban and 8,140 were rural.

The division of the sample by urban and rural stratum within each province is proportional, and the unit of measurement is the number of households in each stratum within each province. The minimum number of households expected in each province was 1,200; exceptions were made for Nampula and Zambézia provinces, with 1,600 households each due to their demographic weight, and Maputo City, with 1,500 households due to the greater variability of its socio-demographic characteristics.

Mode of data collection

Face-to-face [f2f]

Research instrument

To collect data, the methodology of household interviews was adopted, and three types of questionnaire were used: 1) a questionnaire to gather information on all members of the household and the house; 2) one for women aged 15–49; and 3) one for children under five, administered to mothers or caregivers of all children under five living in the household.

The household questionnaire included the following modules: - Sheet to list household members - Education - Water and sanitation - Characteristics of the household - Security of tenure of the house - Mosquito nets and spraying - Child labour - Disability - Orphaned and vulnerable children - Income - Iodized salt.

The questionnaire for women was administered to all women aged 15–49. The questionnaire had the following modules: - Characteristics of the woman interviewed - Matrimonial situation and sexual activity - Child mortality - Maternal and newborn health - Tetanus toxoid - Contraception - Attitudes towards domestic violence - HIV and AIDS.

For the questionnaire for children under five, the mothers or caregivers in each household were identified and interviewed. The questionnaire had the following modules: - Birth registration and early learning - Child development - Vitamin A - Breastfeeding - Care of illness - Malaria - Immunization - Anthropometry.

The three survey questionnaires were based on the MICS3 model questionnaires. Starting with the English version of the MICS3 model, the questionnaires were translated into Portuguese and put into the Mozambican context. Specific themes were added to meet the country’s needs. The pilot survey was held in April 2008 in Maputo City and in Boane district, Maputo province. Based on the results of the pilot survey, modifications were made to the drafting and translation of the questionnaires.

In addition to administering the questionnaires, the fieldwork teams tested the level of iodine in the kitchen salt in use in households and measured the height and weight of all children under five. Details and conclusions from these measurements are presented in the respective sections of the report.

Cleaning operations

Data processing Data processing began in October 2008 and ended in April 2009. Survey processing involved both manual and automatic procedures: receiving and verifying questionnaires, criticism (revision and codification), inputting, editing and analysis of inconsistencies. Data were captured using the interactive software CSPro (Census and Survey Processing System) on 20 microcomputers. Forty data entry operators took part, distributed in two shifts, and a supervisor. To ensure quality control, all the questionnaires were input twice. Throughout the work, procedures and standard programmes developed under the global MICS3 project were used and adapted to the local questionnaire. For cleanness and consistency of data input, the software Stata was used.

Sampling error estimates

Estimate of sampling errors

Since MICS 2008 was a survey by sampling, the results presented in this report are subject to two types of error: sampling errors and non-sampling errors. Non-sampling errors are produced during data collection and processing; sampling errors result from the fact that only a part of the population was interviewed rather than the entire population.

Non-sampling errors include such problems as: failure to question all the women and children selected, errors in formulating the questions and registering the replies, confusion or incapacity of the women in giving information about themselves or their children, and codification or processing errors. Attempts were made to keep this type of error to a minimum by following a series of procedures used in well designed and implemented samples, such as, for example, careful interview design, numerous tests of the questionnaire, intensive training of the interviewers, permanent supervision of the field work, and office review of the questionnaires by the criticism staff. Furthermore, to reduce this type of error, a coverage team was trained to assess the magnitude of such errors, including the coverage of MICS 2008. This team visited all the EAs selected for MICS in all the provinces but the contents or themes were covered by samples.

Appropriate supervision at the stage of data codification and processing, careful cleaning of the archives, feedback to the supervisors, and criticism of the interviewers based on quality control tables also helped minimize errors. The assessment elements available indicate that this type of error was kept within reasonable margins in MICS 2008.

See Appendix C of the Final Report for more detailed information and tables on Estimate of sampling errors.

Demographic data on Portuguese speakers in Maputo, Mozambique.

As of May 2021, ***** percent of the population in Maputo, province of Mozambique, lacked access to sufficient food for consumption. The region had the largest prevalence of food insecurity in the country. The situation was also critical in Inhambane, with ***** percent of the province's population affected. Overall, Mozambique counted *** million people facing insufficient food consumption in the same period.

Dataset resulting from a study on the banking and non-banking agents’ network and their usage in Maputo City and Province in Mozambique. The research project surveyed 498 bank and non-bank agents and 266 users of these financial services. These data provide basic information about the financial services ecosystem in the Maputo region and the role financial agents play in the financial inclusion journey of the population of Mozambique.

人口：马普托在12-01-2017达1,858,597.000人，相较于12-01-2016的1,782,380.000人有所增长。人口：马普托数据按年更新，12-01-2007至12-01-2017期间平均值为1,506,442.000人，共11份观测结果。该数据的历史最高值出现于12-01-2017，达1,858,597.000人，而历史最低值则出现于12-01-2007，为1,225,489.000人。CEIC提供的人口：马普托数据处于定期更新的状态，数据来源于Instituto Nacional De Estatistica，数据归类于Global Database的莫桑比克 – 表 MZ.G003：人口：按地区。

Abstract

The objectives of the Smallholder Household Survey in Mozambique were to:

• Generate a clear picture of the smallholder sector at the national level, including household demographics, agricultural profile, and poverty status and market relationships; • Segment smallholder households in Mozambique according to the most compelling variables that emerge; • Characterize the demand for financial services in each segment, focusing on customer needs, attitudes and perceptions related to both agricultural and financial services; and, • Detail how the financial needs of each segment are currently met, with both informal and formal services, and where there may be promising opportunities to add value.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The universe for the survey consists of smallholder households defined as households with the following criteria: 1) Household with up to 5 hectares OR farmers who have less than 50 heads of cattle, 100 goats/sheep/pigs, or 1,000 chickens 2) Agriculture provides a meaningful contribution to the household livelihood, income, or consumption.

Kind of data

Sample survey data [ssd]

Sampling procedure

The CGAP smallholder household survey in Mozambique is a nationally-representative survey with a target sample size of 3,000 smallholder households. The sample was designed to provide reliable survey estimates at the national level and for the following regions: 1. North region, comprised of the provinces of Niassa, Cabo Delgado, and Nampula; 2. Centre region, comprised of Zambezia, Tete, Maica, and Sofala, Manica; and 3. South region, consisting of Inhambane, Maputo Province, Maputo City and Gaza.

(a) SAMPLING FRAME

The sampling frame for the smallholder household survey is the 2009-2010 Census of Agriculture and Livestock (Censo Agro-Pecuário, CAP II) conducted by the Mozambique National Statistical Office (INE) and based on the 2007 Census of Population and Housing (2007 RGPH). CAP II is a large sample that was designed to be representative at the district level and its sample of enumeration areas (EAs) is considered as the master sample; for the national agricultural surveys. EAs with less than 15 agricultural households (mostly in urban areas) were excluded from the sampling frame for CAP II.

(b) SAMPLE ALLOCATION AND SELECTION

In order to take non-response into account, the target sample size was increased to 3,158 households assuming a household non-response rate of 5% observed in similar national households. The total sample size was first allocated to the three regions based on the number of agricultural households. Within each region, the resulting sample was further distributed proportionally to urban and rural areas. The sample for the smallholder survey is a stratified multistage sample. Stratification was achieved by separating urban and rural areas within each region. Since the CAP II master sample that was used as the sampling frame for the survey is stratified by district, rural and urban areas, the rural strata of the individual districts for the CAP II master sample were collapsed up to the province level, and the same for the urban strata within each province. However, the district was still used as a sorting variable in order to provide implicit stratification by district. At the first sampling stage the CAP II sample EAs were selected systematically with PPS within each district, rural and urban stratum, where the measure of size was the number of agricultural households in the census frame.

The full description of the sample design can be found in the user guide for this data set.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

During data collection, InterMedia received a weekly partial SPSS data file from the field which was analysed for quality control and used to provide timely feedback to field staff while they were still on the ground. The partial data files were also used to check and validate the structure of the data file. The full data file was also checked for completeness, inconsistencies and errors by InterMedia and corrections were made as necessary and where possible.

Response rate

85.8 percent for single respondent questionnare and 92.5 percent for household questionnaire

Sampling error estimates

The sample design for the smallholder household survey was a complex sample design featuring clustering, stratification and unequal probabilities of selection. For key survey estimates, sampling errors considering the design features were produced using either the SPSS Complex Sample module or STATA based on the Taylor series approximation method.

Data appraisal

Following the finalization of questionnaires, a script was developed using Dooblo to support data collection on smart phones. The script was thoroughly tested and validated before its use in the field.

Socio-demographic characteristics by use of prescribed and non-prescribed antibiotics.

Abstract

The People's Security Survey (PSS) is a household survey conducted by the International Labour Orgnaisation's (ILO) Social Security Department (SECSOC). The survey seeks to track the seven forms of work-related security comprising decent work, as well as highlighting people's aspirations and sense of social justice. Between 2000 and 2003, these surveys were conducted in 15 countries and in 2005 these were conducted in three countries: Namibia, Mozambique and Sri Lanka. Because the survey instrument was being developed during that time, and for budgetary reasons, the samples and survey design varied. In some countries, a national representative survey was conducted; in others, representative samples were drawn only from selected regions or from urban areas only. The overriding strategic objective of the PSS is to gather information on people’s security at work and in life through a household-based survey instrument that is internationally comparable. Immediate objectives are: · To develop a multi-dimensional methodology for measuring people’s security at work and in life. · To collect quantitative and qualitative information on the nature, scope, magnitude and depth of and forms of security and insecurity, as well as information on the aspects of each type of security in Mozambique and analyse the interactions of these various factors. · To provide adequate data for the planning, monitoring and analysis of political, economic and social policies and programmes with respect to their impact on household living standards and work life. · To provide an integrated set of information, that measures socio-economic security, describes patterns of access to and use of public services, provides understanding on how households react to the surrounding economic environment and government programmes, and supports the analyses of relationships between numerous aspects of household and work life. · To improve the capacity of ILO workers and key personnel regarding the collection of data critical for planning for people’s security in the country long-term objectives: · In general, gain better awareness of people’s perception for policies and institutional support to provide them with basic security. · To go beyond merely pinpointing areas of security and insecurity, and deepen the inquiry into the causes and consequences of security and insecurity, as well as examine the effect of changes on government policies. · Improve statistics on insecurity and aspirations for social justice and distributive justice. · To support the creation of a Decent Work Index, crucial to ILO work. · To provide important information that can be used to flag workers’ security concerns in ILO Reports and other documents.

Geographic coverage

The survey covered 3 provinces in Mozambique such as: - Maputo - Sofala - Nampula

Analysis unit

• Households
• Individuals

Universe

The universe of the survey was household members aged 15-64. In the universe of this study, the number of children with fathers living in different households is higher than those not living with their mothers. Maputo has the largest number of children not living with either of their parents. Sofala is the province with the least amount of children not living in the household with their parents. The majority of children not living with their parents did not receive any help from them, particularly from the father. Nevertheless, such results should be studied carefully since the majority of the children live with relatives. In slightly more than 10 percent of the households of Maputo and Sofala live orphans who have lost their fathers. This number is twice the number of those who have lost their mothers. In Nampula, the figures are more even.

Kind of data

Sample survey data [ssd]

Sampling procedure

Of the sample universe, the average size of the households was greater in Maputo and smaller in Nampula. This was the same pattern as the Population Census of 1997. The working age population, as well as the older population (65 or more years old) was greater in Maputo compared to the two other provinces, where the population under 15 was superior to 40 percent. In Maputo, the younger population was only a little over 30 percent. In Maputo and Nampula, informal unions were more frequent than formal ones (legal marriages). Sofala presented the opposite case.

Sampling deviation

The sample was designed based on the NSO main sample in order to assure adequate representation of each of the selected provinces

Mode of data collection

Face-to-face [f2f]

Research instrument

It is fact that throughout the country many Mozambicans are not proficient in Portuguese. Therefore, it was necessary to translate the questionnaires into the four local languages spoken in the areas where the questionnaire would be implemented. Once this was established, the questionnaire was translated into Changane (Maputo), Sena, Ndaw (Sofala) and Makwa (Nampula). It became clear after some time during the interview the interviewees would start hurrying up the responses to finish the questionnaire. This is due to the length of the questionnaire (in fact there are two questionnaires). The length of the questionnaire is an important aspect to consider for future surveys as its large extent may jeopardize its quality. In Sofala and Nampula, the second most common reason was the distance to the health clinic. The response levels of ‘no answer’ were very high, mainly in the urban areas of Maputo and Sofala.

Response rate

“No answer” responses were very low. In Maputo it was inferior to 3 percent, in Sofala less than 12 percent and in Nampula it did not reach 5 percent.

Demographic information of women of reproductive age in in the 12 clusters of Gaza and Maputo province in 2014.

Reliable statistics on maternal morbidity and mortality are scarce in low and middle-income countries, especially in rural areas. This is the case in Mozambique where many births happen at home. Furthermore, a sizeable number of facility births have inadequate registration. Such information is crucial for developing effective national and global health policies for maternal and child health. The aim of this study was to generate reliable baseline socio-demographic information on women of reproductive age as well as to establish a demographic surveillance platform to support the planning and implementation of the Community Level Intervention for Pre-eclampsia (CLIP) study, a cluster randomized controlled trial. This study represents a census of all women of reproductive age (12–49 years) in twelve rural communities in Maputo and Gaza provinces of Mozambique. The data were collected through electronic forms implemented in Open Data Kit (ODK) (an app for android based tablets) and household and individual characteristics. Verbal autopsies were conducted on all reported maternal deaths to determine the underlying cause of death. Between March and October 2014, 50,493 households and 80,483 women of reproductive age (mean age 26.9 years) were surveyed. A total of 14,617 pregnancies were reported in the twelve months prior to the census, resulting in 9,029 completed pregnancies. Of completed pregnancies, 8,796 resulted in live births, 466 resulted in stillbirths and 288 resulted in miscarriages. The remaining pregnancies had not yet been completed during the time of the survey (5,588 pregnancies). The age specific fertility indicates that highest rate (188 live births per 1,000 women) occurs in the age 20–24 years old. The estimated stillbirth rate was 50.3/1,000 live and stillbirths; neonatal mortality rate was 13.3/1,000 live births and maternal mortality ratio was 204.6/100,000 live births. The most common direct cause of maternal death was eclampsia and tuberculosis was the most common indirect cause of death. This study found that fertility rate is high at age 20–24 years old. Pregnancy in the advanced age (>35 years of age) in this study was associated with higher poor outcomes such as miscarriage and stillbirth. The study also found high stillbirth rate indicating a need for increased attention to maternal health in southern Mozambique. Tuberculosis and HIV/AIDS are prominent indirect causes of maternal death, while eclampsia represents the number one direct obstetric cause of maternal deaths in these communities. Additional efforts to promote safe motherhood and improve child survival are crucial in these communities.

Unadjusted associations between demographic and enteric pathogen-related characteristics and ARG outcomes among children < 14 months old, Maputo, Mozambique.

Distribution of people observed by age group, sex and place of observation (n = 49,404) in evaluation of mask use in public places in the context of COVID-19, 19 to 28 October 2020, Maputo City, Mozambique.