This report presents statistics on women’s smoking status at time of delivery, at Sub Integrated Care Board (Sub-ICB), Integrated Care Board (ICB), regional and national levels. This release includes provisional data for quarter 3 of 2024-25 using data from the Smoking at Time of Delivery data collection which is submitted by commissioners (presented as SATOD v1). Alongside this and for the third time, comparative data using the Maternity Services Dataset (MSDS) is also presented using data submitted by Trusts (presented as SATOD v2) as a time series from quarter 1 of 2022-23 to quarter 3 of 2024-25. This is available for the same geographical breakdowns and includes an additional breakdown for Local Authorities. This will be repeated for subsequent quarters in 2024-25 to see how the estimates from both data sources align with a view to retiring the Smoking at Time of Delivery data collection at the end of this financial year. Until then, SATOD v1 remains the primary data source for this publication. In 2024, a proposal for the data source for this publication to be changed to the Maternity Services Dataset was included in a wider consultation: Health and social care statistical outputs published by DHSC (including OHID), NHSBSA, UKHSA, ONS and NHS England. A link to this is in the Related Links below. If you would still like to feedback your views on the SATOD data collection retirement and replacement with MSDS, then please contact us on: england.maternityanalysis@nhs.net

Abstract

The 2022 Ghana Demographic and Health Survey (2022 GDHS) is the seventh in the series of DHS surveys conducted by the Ghana Statistical Service (GSS) in collaboration with the Ministry of Health/Ghana Health Service (MoH/GHS) and other stakeholders, with funding from the United States Agency for International Development (USAID) and other partners.

The primary objective of the 2022 GDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the GDHS collected information on: - Fertility levels and preferences, contraceptive use, antenatal and delivery care, maternal and child health, childhood mortality, childhood immunisation, breastfeeding and young child feeding practices, women’s dietary diversity, violence against women, gender, nutritional status of adults and children, awareness regarding HIV/AIDS and other sexually transmitted infections, tobacco use, and other indicators relevant for the Sustainable Development Goals - Haemoglobin levels of women and children - Prevalence of malaria parasitaemia (rapid diagnostic testing and thick slides for malaria parasitaemia in the field and microscopy in the lab) among children age 6–59 months - Use of treated mosquito nets - Use of antimalarial drugs for treatment of fever among children under age 5

The information collected through the 2022 GDHS is intended to assist policymakers and programme managers in designing and evaluating programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-59

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, men aged 15-59, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

To achieve the objectives of the 2022 GDHS, a stratified representative sample of 18,450 households was selected in 618 clusters, which resulted in 15,014 interviewed women age 15–49 and 7,044 interviewed men age 15–59 (in one of every two households selected).

The sampling frame used for the 2022 GDHS is the updated frame prepared by the GSS based on the 2021 Population and Housing Census.1 The sampling procedure used in the 2022 GDHS was stratified two-stage cluster sampling, designed to yield representative results at the national level, for urban and rural areas, and for each of the country’s 16 regions for most DHS indicators. In the first stage, 618 target clusters were selected from the sampling frame using a probability proportional to size strategy for urban and rural areas in each region. Then the number of targeted clusters were selected with equal probability systematic random sampling of the clusters selected in the first phase for urban and rural areas. In the second stage, after selection of the clusters, a household listing and map updating operation was carried out in all of the selected clusters to develop a list of households for each cluster. This list served as a sampling frame for selection of the household sample. The GSS organized a 5-day training course on listing procedures for listers and mappers with support from ICF. The listers and mappers were organized into 25 teams consisting of one lister and one mapper per team. The teams spent 2 months completing the listing operation. In addition to listing the households, the listers collected the geographical coordinates of each household using GPS dongles provided by ICF and in accordance with the instructions in the DHS listing manual. The household listing was carried out using tablet computers, with software provided by The DHS Program. A fixed number of 30 households in each cluster were randomly selected from the list for interviews.

For further details on sample design, see APPENDIX A of the final report.

Mode of data collection

Face-to-face computer-assisted interviews [capi]

Research instrument

Four questionnaires were used in the 2022 GDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Ghana. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

The GSS organized a questionnaire design workshop with support from ICF and obtained input from government and development partners expected to use the resulting data. The DHS Program optional modules on domestic violence, malaria, and social and behavior change communication were incorporated into the Woman’s Questionnaire. ICF provided technical assistance in adapting the modules to the questionnaires.

Cleaning operations

DHS staff installed all central office programmes, data structure checks, secondary editing, and field check tables from 17–20 October 2022. Central office training was implemented using the practice data to test the central office system and field check tables. Seven GSS staff members (four male and three female) were trained on the functionality of the central office menu, including accepting clusters from the field, data editing procedures, and producing reports to monitor fieldwork.

From 27 February to 17 March, DHS staff visited the Ghana Statistical Service office in Accra to work with the GSS central office staff on finishing the secondary editing and to clean and finalize all data received from the 618 clusters.

Response rate

A total of 18,540 households were selected for the GDHS sample, of which 18,065 were found to be occupied. Of the occupied households, 17,933 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 15,317 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 15,014 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 7,263 men age 15–59 were identified as eligible for individual interviews and 7,044 were successfully interviewed.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2022 Ghana Demographic and Health Survey (2022 GDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2022 GDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2022 GDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the GDHS 2022 is an SAS program. This program used the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Standardisation exercise results from anthropometry training
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women and men
• Heaping in anthropometric measurements for children (digit preference)
• Observation of mosquito nets
• Observation of handwashing facility
• School attendance by single year of age
• Vaccination cards photographed
• Number of

The Ukraine Demographic and Health Survey (UDHS) is a nationally representative survey of 6,841 women age 15-49 and 3,178 men age 15-49. Survey fieldwork was conducted during the period July through November 2007. The UDHS was conducted by the Ukrainian Center for Social Reforms in close collaboration with the State Statistical Committee of Ukraine. The MEASURE DHS Project provided technical support for the survey. The U.S. Agency for International Development/Kyiv Regional Mission to Ukraine, Moldova, and Belarus provided funding. The survey is a nationally representative sample survey designed to provide information on population and health issues in Ukraine. The primary goal of the survey was to develop a single integrated set of demographic and health data for the population of the Ukraine. The UDHS was conducted from July to November 2007 by the Ukrainian Center for Social Reforms (UCSR) in close collaboration with the State Statistical Committee (SSC) of Ukraine, which provided organizational and methodological support. Macro International Inc. provided technical assistance for the survey through the MEASURE DHS project. USAID/Kyiv Regional Mission to Ukraine, Moldova and Belarus provided funding for the survey through the MEASURE DHS project. MEASURE DHS is sponsored by the United States Agency for International Development (USAID) to assist countries worldwide in obtaining information on key population and health indicators. The 2007 UDHS collected national- and regional-level data on fertility and contraceptive use, maternal health, adult health and life style, infant and child mortality, tuberculosis, and HIV/AIDS and other sexually transmitted diseases. The survey obtained detailed information on these issues from women of reproductive age and, on certain topics, from men as well. The results of the 2007 UDHS are intended to provide the information needed to evaluate existing social programs and to design new strategies for improving the health of Ukrainians and health services for the people of Ukraine. The 2007 UDHS also contributes to the growing international database on demographic and health-related variables. MAIN RESULTS Fertility rates. A useful index of the level of fertility is the total fertility rate (TFR), which indicates the number of children a woman would have if she passed through the childbearing ages at the current age-specific fertility rates (ASFR). The TFR, estimated for the three-year period preceding the survey, is 1.2 children per woman. This is below replacement level. Contraception : Knowledge and ever use. Knowledge of contraception is widespread in Ukraine. Among married women, knowledge of at least one method is universal (99 percent). On average, married women reported knowledge of seven methods of contraception. Eighty-nine percent of married women have used a method of contraception at some time. Abortion rates. The use of abortion can be measured by the total abortion rate (TAR), which indicates the number of abortions a woman would have in her lifetime if she passed through her childbearing years at the current age-specific abortion rates. The UDHS estimate of the TAR indicates that a woman in Ukraine will have an average of 0.4 abortions during her lifetime. This rate is considerably lower than the comparable rate in the 1999 Ukraine Reproductive Health Survey (URHS) of 1.6. Despite this decline, among pregnancies ending in the three years preceding the survey, one in four pregnancies (25 percent) ended in an induced abortion. Antenatal care. Ukraine has a well-developed health system with an extensive infrastructure of facilities that provide maternal care services. Overall, the levels of antenatal care and delivery assistance are high. Virtually all mothers receive antenatal care from professional health providers (doctors, nurses, and midwives) with negligible differences between urban and rural areas. Seventy-five percent of pregnant women have six or more antenatal care visits; 27 percent have 15 or more ANC visits. The percentage is slightly higher in rural areas than in urban areas (78 percent compared with 73 percent). However, a smaller proportion of rural women than urban women have 15 or more antenatal care visits (23 percent and 29 percent, respectively). HIV/AIDS and other sexually transmitted infections : The currently low level of HIV infection in Ukraine provides a unique window of opportunity for early targeted interventions to prevent further spread of the disease. However, the increases in the cumulative incidence of HIV infection suggest that this window of opportunity is rapidly closing. Adult Health : The major causes of death in Ukraine are similar to those in industrialized countries (cardiovascular diseases, cancer, and accidents), but there is also a rising incidence of certain infectious diseases, such as multidrug-resistant tuberculosis. Women's status : Sixty-four percent of married women make decisions on their own about their own health care, 33 percent decide jointly with their husband/partner, and 1 percent say that their husband or someone else is the primary decisionmaker about the woman's own health care. Domestic Violence : Overall, 17 percent of women age 15-49 experienced some type of physical violence between age 15 and the time of the survey. Nine percent of all women experienced at least one episode of violence in the 12 months preceding the survey. One percent of the women said they had often been subjected to violent physical acts during the past year. Overall, the data indicate that husbands are the main perpetrators of physical violence against women. Human Trafficking : The UDHS collected information on respondents' awareness of human trafficking in Ukraine and, if applicable, knowledge about any household members who had been the victim of human trafficking during the three years preceding the survey. More than half (52 percent) of respondents to the household questionnaire reported that they had heard of a person experiencing this problem and 10 percent reported that they knew personally someone who had experienced human trafficking.

This is a report on NHS-funded maternity services in England for March 2016, using data submitted to the Maternity Services Data Set (MSDS). The MSDS is a patient-level data set that captures key information at each stage of the maternity service care pathway in NHS-funded maternity services, such as those maternity services provided by GP practices and hospitals. The data collected includes mother's demographics, booking appointments, admissions and re-admissions, screening tests, labour and delivery along with baby's demographics, diagnoses and screening tests. The MSDS has been developed to help achieve better outcomes of care for mothers, babies and children. As a 'secondary uses' data set, it re-uses clinical and operational data for purposes other than direct patient care, such as commissioning, clinical audit, research, service planning and performance management at both local and national level. It will provide comparative, mother and child-centric data that will be used to improve clinical quality and service efficiency, and to commission services in a way that improves health and reduces inequalities. As part of this month's publication we are also publishing a special feature presenting further analysis of data submitted to the MSDS pertaining to the birth episodes of pregnant women and comparing this data to similar data reported in Hospital Episode Statistics (HES) during the same period. These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. They are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage. More information about experimental statistics can be found on the UK Statistics Authority website.

About this dataset

Context

The dataset tabulates the data for the Mill Valley, CA population pyramid, which represents the Mill Valley population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Mill Valley, CA, is 24.3.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Mill Valley, CA, is 34.8.
• Total dependency ratio for Mill Valley, CA is 59.0.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Mill Valley, CA is 2.9.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Mill Valley population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Mill Valley for the selected age group is shown in the following column.
• Population (Female): The female population in the Mill Valley for the selected age group is shown in the following column.
• Total Population: The total population of the Mill Valley for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Mill Valley Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Darby, PA population pyramid, which represents the Darby population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Darby, PA, is 37.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Darby, PA, is 21.9.
• Total dependency ratio for Darby, PA is 58.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Darby, PA is 4.6.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Darby population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Darby for the selected age group is shown in the following column.
• Population (Female): The female population in the Darby for the selected age group is shown in the following column.
• Total Population: The total population of the Darby for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Darby Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the South Carolina population pyramid, which represents the South Carolina population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for South Carolina, is 27.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for South Carolina, is 29.0.
• Total dependency ratio for South Carolina is 56.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for South Carolina is 3.4.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the South Carolina population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the South Carolina for the selected age group is shown in the following column.
• Population (Female): The female population in the South Carolina for the selected age group is shown in the following column.
• Total Population: The total population of the South Carolina for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for South Carolina Population by Age. You can refer the same here