Number and percentage of live births, by month of birth, 1991 to most recent year.

Vital Statistics: Birth Rate: per 1000 Population: Punjab data was reported at 14.300 NA in 2020. This records a decrease from the previous number of 14.500 NA for 2019. Vital Statistics: Birth Rate: per 1000 Population: Punjab data is updated yearly, averaging 17.000 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 22.400 NA in 1998 and a record low of 14.300 NA in 2020. Vital Statistics: Birth Rate: per 1000 Population: Punjab data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH002: Vital Statistics: Birth Rate: by States.

Vital Statistics: Birth Rate: per 1000 Population: Telangana data was reported at 16.400 NA in 2020. This records a decrease from the previous number of 16.700 NA for 2019. Vital Statistics: Birth Rate: per 1000 Population: Telangana data is updated yearly, averaging 17.200 NA from Dec 2014 (Median) to 2020, with 7 observations. The data reached an all-time high of 18.000 NA in 2014 and a record low of 16.400 NA in 2020. Vital Statistics: Birth Rate: per 1000 Population: Telangana data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH002: Vital Statistics: Birth Rate: by States.

Abstract

The Ouagadougou Health and Demographic Surveillance System (Ouagadougou HDSS), located in five neighborhoods at the northern periphery of the capital of Burkina Faso, was established in 2008. Data on vital events (births, deaths, unions, migration events) are collected during household visits that have taken place every 10 months.

The areas were selected to contrast informal neighborhoods (40,000 residents) with formal areas (40,000 residents), with the aims of understanding the problems of the urban poor, and testing innovative programs that promote the well-being of this population. People living in informal areas tend to be marginalized in several ways: they are younger, poorer, less educated, farther from public services and more often migrants. Half of the residents live in the Sanitary District of Kossodo and the other half in the District of Sig-Nonghin.

The Ouaga HDSS has been used to study health inequalities, conduct a surveillance of typhoid fever, measure water quality in informal areas, study the link between fertility and school investments, test a non-governmental organization (NGO)-led program of poverty alleviation and test a community-led targeting of the poor eligible for benefits in the urban context. Key informants help maintain a good rapport with the community.

The areas researchers follow consist of 55 census tracks divided into 494 blocks. Researchers mapped all the census tracks and blocks using fieldworkers with handheld global positioning system (GPS) receivers and ArcGIS. During a first census (October 2008 to March 2009), the demographic surveillance system was explained to every head of household and a consent form was signed; during subsequent censuses, new households were enrolled in the same way.

Geographic coverage

Ouagadougou is the capital city of Burkina Faso and lies at the centre of this country, located in the middle of West Africa (128 North of the Equator and 18 West of the Prime Meridian).

Analysis unit

Individual

Universe

Resident household members of households resident within the demographic surveillance area. Inmigrants (visitors) are defined by intention to become resident, but actual residence episodes of less than six months (180 days) are censored. Outmigrants are defined by intention to become resident elsewhere, but actual periods of non-residence less than six months (180 days) are censored. Children born to resident women are considered resident by default, irrespective of actual place of birth. The dataset contains the events of all individuals ever residents during the study period (03 Oct. 2009 to 31 Dec. 2014).

Kind of data

Event history data

Frequency of data collection

This dataset contains rounds 0 to 7 of demographic surveillance data covering the period from 07 Oct. 2008 to 31 December 2014.

Sampling procedure

This dataset is not based on a sample, it contains information from the complete demographic surveillance area of Ouagadougou in Burkina Faso.

Reponse units (households) by Round: Round Households
2008 4941
2009 19159 2010 21168
2011 12548 2012 24174 2013 22326

Sampling deviation

None

Mode of data collection

Proxy Respondent [proxy]

Research instrument

List of questionnaires:

Collective Housing Unit (UCH) Survey Form - Used to register characteristics of the house - Use to register Sanitation installations - All registered house as at previous round are uploaded behind the PDA or tablet.

Household registration (HHR) or update (HHU) Form - Used to register characteristics of the HH - Used to update information about the composition of the household - All registered households as at previous rounds are uploaded behind the PDA or tablet.

Household Membership Registration (HMR) or update (HMU) - Used to link individuals to households. - Used to update information about the household memberships and member status observations - All member status observations as at previous rounds are uploaded behind the PDA or tablet.

Presences registration form (PDR) - Used to uniquely identify the presence of each individual in the household and to identify the new individual in the household - Mainly to ensure members with multiple household memberships are appropriately captured - All presences observations as at previous rounds are uploaded behind the PDA or tablet.

Visitor registration form (VDR) - Used register the characteristics of the new individual in the household - Used to capt the internal migration - Use matching form to facilitate pairing migration

Out Migration notification form (MGN) - Used to record change in the status of residency of individuals or households - Migrants are tracked and updated in the database

Pregnancy history form (PGH) & pregnancy outcome notification form (PON) - Records details of pregnancies and their outcomes - Only if woman is a new member - Only if woman has never completed WHL or WGH - All member pregnancy without pregnancy outcome as at previous rounds are uploaded behind the PDA or tablet.

Death notification form (DTN) - Records all deaths that have recently occurred - Includes information about time, place, circumstances and possible cause of death

Updated Basic information Form (UBIF) - Use to change the individual basic information

Health questionnaire (adults, women, child, elder) - Family planning - Chronic illnesses - Violence and accident - Mental health - Nutrition, alcohol, tobacco - Access to health services - Anthropometric measures - Physical limitations - Self-rated health - Food security

Variability of climate and water accessibility - accessibility to water - child health outcomes - gender outcomes - data on rainfall, temperatures, water quality

Cleaning operations

The data collection system is composed by two databases: - A temporary database, which contains data collected and transferred each day during the round. - A reference database, which contains all data of Ouagadougou Health and Demographic Surveillance System, in which is transferred the data of the temporary database to the end of each round. The temporary database is emptied at the end of the round for a new round.

The data processing takes place in two ways:

1) When collecting data with PDAs or tablets and theirs transfers by Wi-Fi, data consistency and plausibility are controlled by verification rules in the mobile application and in the database. In addition to these verifications, the data from the temporary database undergo validation. This validation is performed each week and produces a validation report for the data collection team. After the validation, if the error is due to an error in the data collection, the field worker equipped with his PDA or tablet go back to the field to revisit and correct this error. At the end of this correction, the field worker makes again the transfer of data through the wireless access points on the server. If the error is due to data inconsistencies that might not be directly related to an error in data collection, the case is remanded to the scientific team of the main database that could resolve the inconsistency directly in the database or could with supervisors perform a thorough investigation in order to correct the error.

2) At the end of the round, the data from the temporary database are automatically transferred into the reference database by a transfer program. After the success of this transfer, further validation is performed on the data in the database to ensure data consistency and plausibility. This still produces a validation report for the data collection team. And the same process of error correction is taken.

Response rate

Household response rates are as follows (assuming that if a household has not responded for 2 years following the last recorded visit to that household, that the household is lost to follow-up and no longer part of the response rate denominator):

Year Response Rate
2008 100%
2009 100%
2010 100%
2011 98% 2012 100% 2013 95%

Sampling error estimates

Not applicable

Data appraisal

CentreId MetricTable QMetric Illegal Legal Total Metric RunDate BF041 MicroDataCleaned Starts 151624 2017-05-16 13:36
BF041 MicroDataCleaned Transitions 0 314778 314778 0 2017-05-16 13:36
BF041 MicroDataCleaned Ends 151624 2017-05-16 13:36
BF041 MicroDataCleaned SexValues 314778 2017-05-16 13:36
BF041 MicroDataCleaned DoBValues 314778 2017-05-16 13:36

The Everyday Childhoods collection is a qualitative longitudinal dataset that was collected by researchers from the Universities of Sussex and Brighton and the Open University during 2013-15. The initial project, called ‘Face 2 Face: Tracing the real and the mediated in children’s cultural worlds’ (F2F) was funded by an NCRM Methodology Innovation award. The primary aim of the project was to explore how technologies documented and mediated the everyday in children's daily lives. The F2F project generated the majority of the data contained in this collection and the dataset comprises data from two research panels: firstly, a younger panel (the 'extensive' panel) of children aged 7-8 years (n=6) who had previously been involved with their families in an ESRC funded study of new motherhood ('The Making of Modern Motherhoods: Memories, Representations, Practices'). Their geographical location ranged across the South, South East and South West of England. Secondly, an older panel (the 'intensive' panel) of children aged 10-15 years (n=7) were recruited for the first time in this study. Their geographical location was focused in the South East of England. This latter sample were recruited to illustrate a diversity of youth experiences and identities, including along intersectional lines of ethnicity, religion, dis/ability, urban/rural locality, and economic background. Over the course of 12 months, both groups of children took part in a series of regular research activities aimed at capturing their everyday lives.Face 2 Face: Tracing the Real and the Mediated in Children’s Cultural Worlds (2013-14) was a 12-month methodological innovation project funded by the ESRC’s National Centre for Research Methods. The study documented thirteen children and young people’s everyday lives over a 12-month period, focusing on how new media technologies were infused in their everyday lives and relationships. The research team worked with two panels: a group of 8 year olds who were part of an established longitudinal study of new motherhood and had been followed since before birth, and a newly established panel of 11-15 year olds. Using a combination of biographical, ethnographic and digital/material methods, the research team worked closely with participants and their families to document their everyday lives. One of the key outputs of the research was a set of public multimedia documents that experimented with using data from the study to depict the children's lives. These multi-modal documents used the digital sound recordings, photographs, ethnographic descriptions and other data captured during the different phases of the study. Ethical practice around the documentation and curation of data about children's lives was a key strand of the study, and were further developed through an AHRC funded follow-up study: 'Curating Childhoods'. This study enabled the to follow up questions about the use of research data in digital age into the domains of archiving and data sharing. As part of this follow up project, participants from the Face 2 Face study were invited to take part in a one-day workshop at the Mass Observation Archive to discuss the future archiving and re-use of their data. (1) ‘Favourite Things’ interviews – Carried out with each participant at the beginning of the study, during which children were invited to share ‘favourite’ possessions in their homes with a focus on objects that connected to their past and objects that connected to their future. The interviews were audio recorded and transcribed and the children’s objects were photographed. (2) Family interviews - To gain a sense of the children’s everyday routines, some of the children’s families were interviewed about a typical day in their household. These interviews typically included the child and at least one parent, and sometimes siblings and extended family. The family interviews were audio recorded and transcribed (3) ‘Day in a life’ observations – Each child was ethnographically observed by a researcher over a single day. These included school days, holidays and weekend days – and were normally chosen by the child in conjunction with their parent. The researchers drew on multimodal practices of ethnographic observation – collecting visual and audio data alongside traditional field notes. (4) Recursive interviews – At the conclusion of the 12 months of fieldwork, each child took part in a final interview to look back on their participation in the study, and to look at the data collected as part of the project. All younger children, and some older children, were interviewed with their parents. Data was presented back to the participants in curated multimedia documents which were intended to be shared publicly on the project’s website with the permission of children and parents.

BackgroundGlobally, with a neonatal mortality rate of 27/1000 live births, Sub-Saharan Africa has the highest rate in the world and is responsible for 43% of all infant fatalities. In the first week of life, almost three-fourths of neonatal deaths occur and about one million babies died on their first day of life. Previous studies lack conclusive evidence regarding the overall estimate of early neonatal mortality in Sub-Saharan Africa. Therefore, this review aimed to pool findings reported in the literature on magnitude of early neonatal mortality in Sub-Saharan Africa.MethodsThis review’s output is the aggregate of magnitude of early neonatal mortality in sub-Saharan Africa. Up until June 8, 2023, we performed a comprehensive search of the databases PubMed/Medline, PubMed Central, Hinary, Google, Cochrane Library, African Journals Online, Web of Science, and Google Scholar. The studies were evaluated using the JBI appraisal check list. STATA 17 was employed for the analysis. Measures of study heterogeneity and publication bias were conducted using the I2 test and the Eggers and Beggs tests, respectively. The Der Simonian and Laird random-effect model was used to calculate the combined magnitude of early neonatal mortality. Besides, subgroup analysis, sensitivity analysis, and meta regression were carried out to identify the source of heterogeneity.ResultsFourteen studies were included from a total of 311 articles identified by the search with a total of 278,173 participants. The pooled magnitude of early neonatal mortality in sub-Saharan Africa was 80.3 (95% CI 66 to 94.6) per 1000 livebirths. Ethiopia had the highest pooled estimate of early neonatal mortality rate, at 20.1%, and Cameroon had the lowest rate, at 0.5%. Among the included studies, both the Cochrane Q test statistic (χ2 = 6432.46, P

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

In 2022, the infant mortality rate in India was at about 25.5 deaths per 1,000 live births, a significant decrease from previous years. Infant mortality as an indicatorThe infant mortality rate is the number of deaths of children under one year of age per 1,000 live births. This rate is an important key indicator for a country’s health and standard of living; a low infant mortality rate indicates a high standard of healthcare. Causes of infant mortality include premature birth, sepsis or meningitis, sudden infant death syndrome, and pneumonia. Globally, the infant mortality rate has shrunk from 63 infant deaths per 1,000 live births to 27 since 1990 and is forecast to drop to 8 infant deaths per 1,000 live births by the year 2100. India’s rural problemWith 32 infant deaths per 1,000 live births, India is neither among the countries with the highest nor among those with the lowest infant mortality rate. Its decrease indicates an increase in medical care and hygiene, as well as a decrease in female infanticide. Increasing life expectancy at birth is another indicator that shows that the living conditions of the Indian population are improving. Still, India’s inhabitants predominantly live in rural areas, where standards of living as well as access to medical care and hygiene are traditionally lower and more complicated than in cities. Public health programs are thus put in place by the government to ensure further improvement.