A survey on what women consider to be sexual harassment in Great Britain in 2020 showed that 97 percent of women considered a man trying to take a photo up a woman's skirt to be sexual harassment. Of the 12 examples of sexual harassment provided here, asking a woman out for a drink is the scenario seen by the fewest share of women as being harassment, at three percent.

This statistic shows the number of employees in women-owned businesses in the United States from 1997 to 2019. In 2019, women-owned businesses employed about 9.38 million people.

Abstract

The 1997 Jordan Population and Family Health Survey (JPFHS) is a national sample survey carried out by the Department of Statistics (DOS) as part of its National Household Surveys Program (NHSP). The JPFHS was specifically aimed at providing information on fertility, family planning, and infant and child mortality. Information was also gathered on breastfeeding, on maternal and child health care and nutritional status, and on the characteristics of households and household members. The survey will provide policymakers and planners with important information for use in formulating informed programs and policies on reproductive behavior and health.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN AND IMPLEMENTATION

The 1997 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, for urban and rural areas, for the three regions (each composed of a group of governorates), and for the three major governorates, Amman, Irbid, and Zarqa.

The 1997 JPFHS sample is a subsample of the master sample that was designed using the frame obtained from the 1994 Population and Housing Census. A two-stage sampling procedure was employed. First, primary sampling units (PSUs) were selected with probability proportional to the number of housing units in the PSU. A total of 300 PSUs were selected at this stage. In the second stage, in each selected PSU, occupied housing units were selected with probability inversely proportional to the number of housing units in the PSU. This design maintains a self-weighted sampling fraction within each governorate.

UPDATING OF SAMPLING FRAME

Prior to the main fieldwork, mapping operations were carried out and the sample units/blocks were selected and then identified and located in the field. The selected blocks were delineated and the outer boundaries were demarcated with special signs. During this process, the numbers on buildings and housing units were updated, listed and documented, along with the name of the owner/tenant of the unit or household and the name of the household head. These activities took place between January 7 and February 28, 1997.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face

Research instrument

The 1997 JPFHS used two questionnaires, one for the household interview and the other for eligible women. Both questionnaires were developed in English and then translated into Arabic. The household questionnaire was used to list all members of the sampled households, including usual residents as well as visitors. For each member of the household, basic demographic and social characteristics were recorded and women eligible for the individual interview were identified. The individual questionnaire was developed utilizing the experience gained from previous surveys, in particular the 1983 and 1990 Jordan Fertility and Family Health Surveys (JFFHS).

The 1997 JPFHS individual questionnaire consists of 10 sections: - Respondent’s background - Marriage - Reproduction (birth history) - Contraception - Pregnancy, breastfeeding, health and immunization - Fertility preferences - Husband’s background, woman’s work and residence - Knowledge of AIDS - Maternal mortality - Height and weight of children and mothers.

Cleaning operations

Fieldwork and data processing activities overlapped. After a week of data collection, and after field editing of questionnaires for completeness and consistency, the questionnaires for each cluster were packaged together and sent to the central office in Amman where they were registered and stored. Special teams were formed to carry out office editing and coding.

Data entry started after a week of office data processing. The process of data entry, editing, and cleaning was done by means of the ISSA (Integrated System for Survey Analysis) program DHS has developed especially for such surveys. The ISSA program allows data to be edited while being entered. Data entry was completed on November 14, 1997. A data processing specialist from Macro made a trip to Jordan in November and December 1997 to identify problems in data entry, editing, and cleaning, and to work on tabulations for both the preliminary and final report.

Response rate

A total of 7,924 occupied housing units were selected for the survey; from among those, 7,592 households were found. Of the occupied households, 7,335 (97 percent) were successfully interviewed. In those households, 5,765 eligible women were identified, and complete interviews were obtained with 5,548 of them (96 percent of all eligible women). Thus, the overall response rate of the 1997 JPFHS was 93 percent. The principal reason for nonresponse among the women was the failure of interviewers to find them at home despite repeated callbacks.

Note: See summarized response rates by place of residence in Table 1.1 of the survey report.

Sampling error estimates

The estimates from a sample survey are subject to two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the result of mistakes made in implementing data collection and data processing (such as failure to locate and interview the correct household, misunderstanding questions either by the interviewer or the respondent, and data entry errors). Although during the implementation of the 1997 JPFHS numerous efforts were made to minimize this type of error, nonsampling errors are not only impossible to avoid but also difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The respondents selected in the 1997 JPFHS constitute only one of many samples that could have been selected from the same population, given the same design and expected size. Each of those samples would have yielded results differing somewhat from the results of the sample actually selected. Sampling errors are a measure of the variability among 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 percent 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, since the 1997 JDHS-II sample resulted from a multistage stratified design, formulae of higher complexity had to be used. The computer software used to calculate sampling errors for the 1997 JDHS-II was the ISSA Sampling Error Module, which uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics, such as fertility and mortality rates.

Note: See detailed estimate of sampling error calculation in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

Note: See detailed tables in APPENDIX C of the survey report.

Abstract

The 1997 the Kyrgyz Republic Demographic and Health Survey (KRDHS) is a nationally representative survey of 3,848 women age 15-49. Fieldwork was conducted from August to November 1997. The KRDHS was sponsored by the Ministry of Health (MOH), and was funded by the United States Agency for International Development. The Research Institute of Obstetrics and Pediatrics implemented the survey with technical assistance from the Demographic and Health Surveys (DHS) program.

The purpose of the KRDHS was to provide data to the MOH on factors which determine the health status of women and children such as fertility, contraception, induced abortion, maternal care, infant mortality, nutritional status, and anemia.

Some statistics presented in this report are currently available to the MOH from other sources. For example, the MOH collects and regularly publishes information on fertility, contraception, induced abortion and infant mortality. However, the survey presents information on these indices in a manner which is not currently available, i.e., by population subgroups such as those defined by age, marital duration, education, and ethnicity. Additionally, the survey provides statistics on some issues not previously available in the Kyrgyz Republic: for example, breastfeeding practices and anemia status of women and children. When considered together, existing MOH data and the KRDHS data provide a more complete picture of the health conditions in the Kyrgyz Republic than was previously available.

A secondary objective of the survey was to enhance the capabilities of institutions in the Kyrgyz Republic to collect, process, and analyze population and health data.

MAIN FINDINGS

FERTILITY

Fertility Rates. Survey results indicate a total fertility rate (TFR) for all of the Kyrgyz Republic of 3.4 children per woman. Fertility levels differ for different population groups. The TFR for women living in urban areas (2.3 children per woman) is substantially lower than for women living in rural areas (3.9). The TFR for Kyrgyz women (3.6 children per woman) is higher than for women of Russian ethnicity (1.5) but lower than Uzbek women (4.2). Among the regions of the Kyrgyz Republic, the TFR is lowest in Bishkek City (1.7 children per woman), and the highest in the East Region (4.3), and intermediate in the North and South Regions (3.1 and3.9, respectively).

Time Trends. The KRDHS data show that fertility has declined in the Kyrgyz Republic in recent years. The decline in fertility from 5-9 to 0-4 years prior to the survey increases with age, from an 8 percent decline among 20-24 year olds to a 38 percent decline among 35-39 year olds. The declining trend in fertility can be seen by comparing the completed family size of women near the end of their childbearing years with the current TFR. Completed family size among women 40-49 is 4.6 children which is more than one child greater than the current TFR (3.4).

Birth Intervals. Overall, 30 percent of births in the Kyrgyz Republic take place within 24 months of the previous birth. The median birth interval is 31.9 months.

Age at Onset of Childbearing. The median age at which women in the Kyrgyz Republic begin childbearing has been holding steady over the past two decades at approximately 21.6 years. Most women have their first birth while in their early twenties, although about 20 percent of women give birth before age 20.

Nearly half of married women in the Kyrgyz Republic (45 percent) do not want to have more children. Additional one-quarter of women (26 percent) want to delay their next birth by at least two years. These are the women who are potentially in need of some method of family planning.

FAMILY PLANNING

Ever Use. Among currently married women, 83 percent report having used a method of contraception at some time. The women most likely to have ever used a method of contraception are those age 30-44 (among both currently married and all women).

Current Use. Overall, among currently married women, 60 percent report that they are currently using a contraceptive method. About half (49 percent) are using a modern method of contraception and another 11 percent are using a traditional method. The IUD is by far the most commonly used method; 38 percent of currently married women are using the IUD. Other modern methods of contraception account for only a small amount of use among currently married women: pills (2 percent), condoms (6 percent), and injectables and female sterilization (1 and 2 percent, respectively). Thus, the practice of family planning in the Kyrgyz Republic places high reliance on a single method, the IUD.

Source of Methods. The vast majority of women obtain their contraceptives through the public sector (97 percent): 35 percent from a government hospital, and 36 percent from a women counseling center. The source of supply of the method depends on the method being used. For example, most women using IUDs obtain them at women counseling centers (42 percent) or hospitals (39 percent). Government pharmacies supply 46 percent of pill users and 75 percent of condom users. Pill users also obtain supplies from women counseling centers or (33 percent).

Fertility Preferences. A majority of women in the Kyrgyz Republic (45 percent) indicated that they desire no more children. By age 25-29, 20 percent want no more children, and by age 30-34, nearly half (46 percent) want no more children. Thus, many women come to the preference to stop childbearing at relatively young ages-when they have 20 or more potential years of childbearing ahead of them. For some of these women, the most appropriate method of contraception may be a long-acting method such as female sterilization. However, there is a deficiency of use of this method in the Kyrgyz Republic. In the interests of providing a broad range of safe and effective methods, information about and access to sterilization should be increased so that individual women can make informed decisions about using this method.

INDUCED ABORTION

Abortion Rates. From the KRDHS data, the total abortion rate (TAR)-the number of abortions a woman will have in her lifetime based on the currently prevailing abortion rates-was calculated. For the Kyrgyz Republic, the TAR for the period from mid-1994 to mid-1997 is 1.6 abortions per woman. The TAR for the Kyrgyz Republic is lower than recent estimates of the TAR for other areas of the former Soviet Union such as Kazakhstan (1.8), and Yekaterinburg and Perm in Russia (2.3 and 2.8, respectively), but higher than for Uzbekistan (0.7).

The TAR is higher in urban areas (2.1 abortions per woman) than in rural areas (1.3). The TAR in Bishkek City is 2.0 which is two times higher than in other regions of the Kyrgyz Republic. Additionally the TAR is substantially lower among ethnic Kyrgyz women (1.3) than among women of Uzbek and Russian ethnicities (1.9 and 2.2 percent, respectively).

INFANT MORTALITY

In the KRDHS, infant mortality data were collected based on the international definition of a live birth which, irrespective of the duration of pregnancy, is a birth that breathes or shows any sign of life (United Nations, 1992). Mortality Rates. For the five-year period before the survey (i.e., approximately mid-1992 to mid1997), infant mortality in the Kyrgyz Republic is estimated at 61 infant deaths per 1,000 births. The estimates of neonatal and postneonatal mortality are 32 and 30 per 1,000.

The MOH publishes infant mortality rates annually but the definition of a live birth used by the MOH differs from that used in the survey. As is the case in most of the republics of the former Soviet Union, a pregnancy that terminates at less than 28 weeks of gestation is considered premature and is classified as a late miscarriage even if signs of life are present at the time of delivery. Thus, some events classified as late miscarriages in the MOH system would be classified as live births and infant deaths according to the definitions used in the KRDHS.

Infant mortality rates based on the MOH data for the years 1983 through 1996 show a persistent declining trend throughout the period, starting at about 40 per 1,000 in the early 1980s and declining to 26 per 1,000 in 1996. This time trend is similar to that displayed by the rates estimated from the KRDHS. Thus, the estimates from both the KRDHS and the Ministry document a substantial decline in infant mortality; 25 percent over the period from 1982-87 to 1992-97 according to the KRDHS and 28 percent over the period from 1983-87 to 1993-96 according to the MOH estimates. This is strong evidence of improvements in infant survivorship in recent years in the Kyrgyz Republic.

It should be noted that the rates from the survey are much higher than the MOH rates. For example, the KRDHS estimate of 61 per 1,000 for the period 1992-97 is twice the MOH estimate of 29 per 1,000 for 1993-96. Certainly, one factor leading to this difference are the differences in the definitions of a live birth and infant death in the KRDHS survey and in the MOH protocols. A thorough assessment of the difference between the two estimates would need to take into consideration the sampling variability of the survey's estimate. However, given the magnitude of the difference, it is likely that it arises from a combination of definitional and methodological differences between the survey and MOH registration system.

MATERNAL AND CHILD HEALTH

The Kyrgyz Republic has a well-developed health system with an extensive infrastructure of facilities that provide maternal care services. This system includes special delivery hospitals, the obstetrics and gynecology departments of general hospitals, women counseling centers, and doctor's assistant/midwife posts (FAPs). There is an extensive network of FAPs throughout the rural areas.

Delivery. Virtually all births in the

This statistic shows the number of women-owned businesses in the United States from 1997 to 2019. In 2019, about 12.94 million companies in the U.S. were owned by women.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Winhall town. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Winhall town, the median income for all workers aged 15 years and older, regardless of work hours, was $42,500 for males and $41,136 for females.

Based on these incomes, we observe a gender gap percentage of approximately 3%, indicating a significant disparity between the median incomes of males and females in Winhall town. Women, regardless of work hours, still earn 97 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

- Full-time workers, aged 15 years and older: In Winhall town, among full-time, year-round workers aged 15 years and older, males earned a median income of $68,194, while females earned $66,364, resulting in a 3% gender pay gap among full-time workers. This illustrates that women earn 97 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the town of Winhall town.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Winhall town, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Winhall town median household income by race. You can refer the same here

Abstract

The survey was specifically designed to meet the following objectives: -to assess the current situation in Moldova concerning fertility, abortion, contraception and various other reproductive health issues; -to enable policy makers, program managers, and researchers to evaluate and improve existing programs and to develop new strategies; -to measure changes in fertility and contraceptive prevalence rates and study factors that affect these changes, such as geographic and socio-demographic factors, breast-feeding patterns, use of induced abortion, and availability of family planning; -to provide data necessary to develop sex education and health promotion programs; -to obtain data on knowledge, attitudes, and behavior of young adults 15-24 years of age; -to provide information on the level of knowledge about AIDS transmission and prevention; -to identify and focus further reproductive health studies toward high risk groups.

The survey provides data that will assist the Moldovan Government in improving services related to the health of women and children and was proposed in conjunction with the UNFPAsponsored reproductive health (RH) activities in Moldova, which consist of several components intended to increase the use of effective contraception, reduce the reliance on induced abortion as a means of fertility control, and, more generally, to improve RH. Specific projects supported by UNFPA in Moldova include ongoing support to the Government for developing a national RH plan, provisions of contraceptives, and training of family planning providers. In addition, the national RH plan is receiving support from USAID (family planning logistics management, information/ education/communication activities), IPPF (provision of contraceptives), and UNICEF.

Geographic coverage

The 1997 MRHS was designed to collect information from a representative sample of women of reproductive age throughout Moldova.

Universe

The universe from which the respondents were selected included all females between the ages of 15 and 44, regardless of marital status, who were living in Moldova when the survey was carried out.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey employed a three-stage probability sample design and successfully interviewed 5,412 (98%) of 5,543 women identified in sample households as eligible for interview.

The survey employed a three-stage sampling design using two sampling frames (one for urban areas and one for rural areas) provided by the MSDS. The urban sampling frame was based on the 1989 census, whereas the rural sampling frame consisted of a list of the 1,607 villages in the country, recently updated for household composition in January-April 1997 for an agricultural registry.

In the first stage, 128 census sectors in urban areas and 122 villages were selected as Primary Sampling Units (PSUs) with probability proportional to the number of households in each census sector/village. In the second stage of sampling, clusters of households were randomly selected in each census sector/village chosen in the first stage. Before second-stage selection in urban areas, the Census Division of the MSDS redefined each 1989 census sector selected as a PSU for street boundaries, converted the maps and listings from Russian to Moldavian, and updated the sector's household composition in collaboration with personnel from the local health care units. A cluster of households was randomly selected from the updated sector lists of the PSUs in urban areas and from the household listings in the villages selected as PSUs in the first stage. (Since there were roughly equal numbers of urban and rural households, the sample was designed to be geographically self-weighting.) In each sample strata, urban and rural, the third stage consisted of the random selection of one woman if there were two or more eligible women (aged 15-44 years) living in the same household.

Cluster size determination was based on the number of households required to obtain an average of 20 interviews per cluster. The total number of households in each cluster took into account estimates of unoccupied households, average number of women 15-44 per household, the interview of only one woman per household, and an estimated response rate of 90% in urban areas and 92% in rural areas. In urban areas, the cluster size with a yield of 20 interviews, on average, was determined to be 45 households. In rural areas, because the average number of women 15-44 per household varies considerably by raion, the average number of households needed to obtain 20 complete interviews varied from 42 to 60.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was first drafted by CDC/DRH consultants based on a core questionnaire used in the 1993 Romanian Reproductive Health Survey. This core questionnaire was reviewed and modified by Moldovan experts in reproductive health and family planning, as well as by USAID and UNFPA. Based on these reviews, a pretest questionnaire was developed and field-tested in April 1997. The questionnaire, developed in Romanian, was translated into Russian after the pretest. All interviewers spoke these two languages.

The questionnaire had two components: (1) A short household questionnaire used to collect residential and geographic information, select information about all women of childbearing age living in sampled households, and information on interview status. This module was also used to randomly select one respondent when there was more than one eligible woman in the household; (2) The longer individual questionnaire collected information on the topics mentioned above.

The major reproductive health topics on which information was collected were: pregnancies and childbearing (a complete history of all pregnancies, including planning status of pregnancies in the last five years, a detailed history of abortions within the last five years, including postabortion counseling, and the history of all births within the last five years, including the patterns of utilization of health services during pregnancy, maternal morbidity, infant health and breast-feeding); family planning (knowledge and history of use of methods of preventing pregnancy, current use of contraception, source of contraception, reasons for not using, reasons for use of less effective methods of contraception, future fertility preferences and intentions to use voluntary sterilization); women's health (health behavior and use of women's health services, tobacco and alcohol use); reproductive health knowledge and attitudes (especially regarding birth control pills, condoms, and IUDs); knowledge about HIV/AIDS transmission and prevention; domestic violence, including violence during the most recent pregnancy; history of sexual abuse; and socioeconomic characteristics of women and their husbands/families. The young women (15-24 years of age) were asked additional questions on sex education, age and contraceptive use at first sexual intercourse, and sexual behaviors.

Most issues have been examined by geographic, demographic, and socio-economic characteristics, making it possible to identify the segments of the population with specific health needs or problems.

Response rate

Of the 11,506 households selected, 5,543 were found to include at least one 15-44 year-old woman. Of these women, 5,412 were successfully interviewed, for a response rate of 97.6%. Less than one percent of selected women refused to be interviewed, while another 1.3% could not be located. Response rates were slightly better in rural areas (98%) than in municipalities and other urban areas (97%). In Chisinau (not shown), the response rate was 96%; nearly 3% of women selected in the sample could not be located.

Data appraisal

The geographic distribution of the sample, by residence and region, is very close to official figures of the population distribution for 1996, estimated by the Moldovan State Department for Statistics.

The percent distribution of women in the sample by five-year age groups is compared with the 1994 official estimates (the most recent estimates by age group) in Table 2.3. Compared with these estimates, the survey sample has slightly over-represented adolescent women (15-19 yearolds) and under-represented women aged 40-44 by about two percentage points. However, several factors may have contributed to the differences observed: first, there is a three-year difference between the time the official estimates were calculated and the survey was implemented; second, the official estimates are projections of the age composition recorded by the 1989 census and thus dependent on assumptions used in projecting the aging of a cohort; finally, official estimates include any possible age misreporting that occured in the census.

Abstract

The Indonesia Demographic and Health Survey (IDHS), which is part of the Demographic and Health Surveys (DHS) Project, is one of prominent national surveys in the field of population, family planning, and health. The survey is not only important nationally for planning and evaluating population, family planning, and health developments, but is also important internationally since IDHS has been designed so uniquely that it can be compared with similar surveys in other developing countries.

The 1997 Indonesia Demographic and Health Survey (IDHS) is a follow-on project to the 1987 National Indonesia Contraceptive Prevalence Survey (NICPS), the 1991 IDHS, and the 1994 IDHS. The 1997 IDHS was expanded from the 1994 survey to include a module on family welfare; however, unlike the 1994 survey, the 1997 survey no longer investigated the availability of family planning and health services. The 1997 IDHS also included as part of the household schedule a household expenditure module that provided a means of identifying the household's economic status.

The 1997 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, maternal mortality, and awareness of AIDS that can be used by program managers, policymakers, and researchers to evaluate and improve existing programs - Provide data about availability of family planning and health services, thereby offering an opportunity for linking women's fertility, family planning, and child care behavior with the availability of services - Provide household expenditure data that which can be used to identify the household's economic status - Provide data that can be used to analyze trends over time by examining many of the same fertility, mortality, and health issues that were addressed in the earlier surveys (1987 NICPS, 1991 IDHS and 1994 IDHS) - Measure changes in fertility and contraceptive prevalence rates and at the same time study factors that affect the changes, such as marriage patterns, urban/rural residence, education, breastfeeding habits, and the availability of contraception - Measure the development and achievements of programs related to health policy, particularly those concerning the maternal and child health development program implemented through public health clinics in Indonesia - Provide indicators for classifying families according to their welfare status.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data

Sampling procedure

Indonesia is divided into 27 provinces. For the implementation of its family planning program, the National Family Planning Coordinating Board (NFPCB) has divided these provinces into three regions as follows:

• Java-Bali: DKI Jakarta, West Java, Central Java, DI Yogyakarta, East Java, and Bali
• Outer Java-Bali I: Dista Aceh, North Sumatra, West Sumatra, South Sumatra, Lampung, West Nusa Tenggara, West Kalimantan, South Kalimantan, North Sulawesi, and South Sulawesi
• Outer Java-Ball II: Riau, Jambi, Bengkulu, East Nusa Tenggara, East Timor, Central Kalimantan, East Kalimantan, Central Sulawesi, Southeast Sulawesi, Maluku, and Irian Jaya

The 1990 Population Census of Indonesia shows that Java-Bali accounts for 62 percent of the national population, Outer Java-Bali I accounts for 27 percent, and Outer Java-Bali II accounts for 11 percent. The sample for the 1997 IDHS was designed to produce reliable estimates of fertility, contraceptive prevalence and other important variables for each of the provinces and urban and rural areas of the three regions.

In order to meet this objective, between 1,650 and 2,050 households were selected in each of the provinces in Java-Bali, 1,250 to 1,500 households in the ten provinces in Outer Java-Bali I, and 1,000 to 1,250 households in each of the provinces in Outer Java-Bali II, for a total of 35,500 households. With an average of O.8 ever-married women 15-49 per household, the sample was expected to yield approximately 28,000 women eligible for the individual interview.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1997 IDHS used three questionnaires: the household questionnaire, the questionnaire on family welfare, and the individual questionnaire for ever-married women 15-49 years old. The general household and individual questionnaires were based on the DHS Model "A" Questionnaire, which is designed for use in countries with high contraceptive prevalence. Additions and modifications to the model questionnaire were made in order to provide detailed information specific to Indonesia. The questionnaires were developed mainly in English and were translated into Indonesian. One deviation from the standard DHS practice is the exclusion of the anthropometric measurement of young children and their mothers. A separate survey carried out by MOH provides this information.

The household questionnaire includes an expenditure schedule adapted from the core Susenas questionnaire model. Susenas is a national household survey carried out annually by CBS to collect data on various demographic and socioeconomic indicators of the population. The family welfare questionnaire was aimed at collecting indicators developed by the NFPCB to classify families according to their welfare status. Families were identified from the list of household members in the household questionnaire. The expenditure module and the family welfare questionnaire were developed in Indonesian.

Cleaning operations

The first stage of data editing was carried out by the field editors who checked the completed questionnaires for thoroughness and accuracy. Field supervisors then further examined the questionnaires. In many instances, the teams sent the questionnaires to CBS through the regency/municipality statistics offices. In these cases, no checking was done by the PSO. In other cases, Technical Coordinators are responsible for reviewing the completeness of the forms. At CBS, the questionnaires underwent another round of editing, primarily for completeness and coding of responses to open-ended questions. The data were processed using microcomputers and the DHS computer program, ISSA (Integrated System for Survey Analysis). Data entry and office editing were initiated immediately after fieldwork began. Simple range and skip errors were corrected at the data entry stage. Data processing was completed by February 1998, and the preliminary report of the survey was published in April 1998.

Response rate

A total of 35,362 households were selected for the survey, of which 34,656 were found. Of the encountered households, 34,255 (99 percent) were successfully interviewed. In these households, 29,317 eligible women were identified, and complete interviews were obtained from 28,810 women, or 98 percent of all eligible women. The generally high response rates for both household and individual interviews were due mainly to the strict enforcement of the rule to revisit the originally selected household if no one was at home initially. No substitution for the originally selected households was allowed. Interviewers were instructed to make at least three visits in an effort to contact the household or eligible woman.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (I) non-sampling errors and (2) sampling errors. Non-sampling 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 1997 IDHS to minimize this type of error, non-sampling 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 1997 IDHS is only one of many samples that could have been selected from the same population, using the same design and expected 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 percent 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 1997 IDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 1997 IDHS is the ISSA Sampling Error Module. This module

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Wapato. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Wapato, the median income for all workers aged 15 years and older, regardless of work hours, was $28,816 for males and $24,425 for females.

Based on these incomes, we observe a gender gap percentage of approximately 15%, indicating a significant disparity between the median incomes of males and females in Wapato. Women, regardless of work hours, still earn 85 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

- Full-time workers, aged 15 years and older: In Wapato, among full-time, year-round workers aged 15 years and older, males earned a median income of $38,594, while females earned $37,500, resulting in a 3% gender pay gap among full-time workers. This illustrates that women earn 97 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Wapato.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Wapato, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Wapato median household income by race. You can refer the same here

This statistic shows the revenue of women-owned firms in the United States from 1997 to 2019. In 2019, women-owned businesses had a total revenue of about 1.85 trillion U.S. dollars.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Wilson town. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Wilson town, the median income for all workers aged 15 years and older, regardless of work hours, was $49,516 for males and $35,303 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 29% between the median incomes of males and females in Wilson town. With women, regardless of work hours, earning 71 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Wilson town.

- Full-time workers, aged 15 years and older: In Wilson town, among full-time, year-round workers aged 15 years and older, males earned a median income of $61,521, while females earned $59,919, resulting in a 3% gender pay gap among full-time workers. This illustrates that women earn 97 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the town of Wilson town.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Wilson town.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Wilson town median household income by race. You can refer the same here

Abstract

The 2010 Armenia Demographic and Health Survey (2010 ADHS) is the third in a series of nationally representative sample surveys designed to provide information on population and health issues. It is conducted in Armenia under the worldwide Demographic and Health Surveys program. Specifically, the 2010 ADHS has a primary objective of providing current and reliable information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of young children, childhood mortality, maternal and child health, and awareness and behavior regarding AIDS and other sexually transmitted infections (STIs). The survey obtained detailed information on these issues from women of reproductive age and, for certain topics, from men as well.

The 2010 ADHS results are intended to provide information needed to evaluate existing social programs and to design new strategies to improve health of and health services for the people of Armenia. Data are presented by region (marz) wherever sample size permits. The information collected in the 2010 ADHS will provide updated estimates of basic demographic and health indicators covered in the 2000 and 2005 surveys.

The long-term objective of the survey includes strengthening the technical capacity of major government institutions, including the NSS. The 2010 ADHS also provides comparable data for longterm trend analysis in Armenia because the 2000, 2005, and 2010 surveys were implemented by the same organisation and used similar data collection procedures. It also adds to the international database of demographic and health–related information for research purposes.

The 2010 ADHS was conducted by the National Statistical Service (NSS) and the MOH of Armenia from October 5 through December 25, 2010.

Kind of data

Sample survey data

Sampling procedure

The sample was designed to permit detailed analysis-including the estimation of rates of fertility, infant/child mortality, and abortion-at the national level, for Yerevan, and for total urban and total rural areas separately. Many indicators can also be estimated at the regional (marz) level.

A representative probability sample of 7,580 households was selected for the 2010 ADHS sample. The sample was selected in two stages. In the first stage, 308 clusters were selected from a list of enumeration areas in a subsample of a master sample derived from the 2001 Population Census frame. In the second stage, a complete listing of households was carried out in each selected cluster. Households were then systematically selected for participation in the survey.

All women age 15-49 who were either permanent residents of the households in the 2010 ADHS sample or visitors present in the household on the night before the survey were eligible to be interviewed. Interviews were completed with 5,922 women. In addition, in a subsample of one-third of all of the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey. Interviews were completed with 1,584 men.

Appendix A of the Final Report provides additional information on the sample design of the 2010 Armenia DHS.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the ADHS: a Household Questionnaire, a Woman’s Questionnaire, and a Man’s Questionnaire. The Household Questionnaire and the individual questionnaires were based on model survey instruments developed in the MEASURE DHS program and questionnaires used in the previous 2005 ADHS. The model questionnaires were adapted for use by NSS and MOH. Suggestions were also sought from a number of nongovernmental organizations (NGOs). The questionnaires were developed in English and translated into Armenian. They were pretested in July 2010.

The Household Questionnaire was used to list all usual members of and visitors to the selected households and to collect information on the socioeconomic status of the household. The first part of the Household Questionnaire collected for each household member or visitor information on their age, sex, educational attainment, and relationship to the head of household. This information provided basic demographic data for Armenian households. It also was used to identify the women and men who were eligible for an individual interview (i.e., women and men age 15-49). In the second part of the Household Questionnaire, there were questions on housing characteristics (e.g., the flooring material, the source of water, and the type of toilet facilities), on ownership of a variety of consumer goods, and on other aspects of the socioeconomic status of the household. In addition, the Household Questionnaire was used to obtain information on each child’s birth registration, ask questions about child discipline and child labor, and record height and weight measurements of children under age 5.

The Woman’s Questionnaire obtained information from women age 15-49 on the following topics: - Background characteristics - Pregnancy history - Antenatal, delivery, and postnatal care - Knowledge, attitudes, and use of contraception - Reproductive and adult health - Childhood mortality - Health and health care utilization - Vaccinations of children under age 5 - Episodes of diarrhea and respiratory illness of children under age 5 - Breastfeeding and weaning practices - Marriage and recent sexual activity - Fertility preferences - Knowledge of and attitudes toward AIDS and other sexually transmitted diseases - Woman’s work and husband’s background characteristics

The Man’s Questionnaire, administered to men age 15-49, focused on the following topics: - Background characteristics - Health and health care utilization - Marriage and recent sexual activity - Attitudes toward and use of condoms - Knowledge of and attitudes toward AIDS and other sexually transmitted diseases - Attitudes toward women’s status

Cleaning operations

Data Processing

The processing of the ADHS results began shortly after fieldwork commenced. Completed questionnaires were returned regularly from the field to NSS headquarters in Yerevan, where they were entered and edited by data processing personnel who were specially trained for this task. The data processing personnel included a supervisor, a questionnaire administrator (who ensured that the expected number of questionnaires from all clusters was received), several office editors, 12 data entry operators, and a secondary editor. The concurrent processing of the data was an advantage because the senior DHS technical staff were able to advise field teams of problems detected during the data entry. In particular, tables were generated to check various data quality parameters. As a result, specific feedback was given to the teams to improve performance. The data entry and editing phase of the survey was completed in March 2011.

Response rate

A total of 7,580 households were selected in the sample, of which 7,043 were occupied at the time of the fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. The number of occupied households successfully interviewed was 6,700, yielding a household response rate of 95 percent. The household response rate in urban areas (94 percent) was slightly lower than in rural areas (97 percent).

In these households, a total of 6,059 eligible women were identified; interviews were completed with 5,922 of these women, yielding a response rate of 98 percent. In one-third of the households, a total of 1,641 eligible men were identified, and interviews were completed with 1,584 of these men, yielding a response rate of 97 percent. Response rates are slightly lower in urban areas (97 percent for women and 96 percent for men) than in rural areas where rates were 99 and 97 percent, respectively.

Sampling error estimates

Detailed information on sampling errors is provided in Appendix B of the Final Report.

In 2024, the difference between average hourly earnings for men and women in the United Kingdom for all workers was 13.1 percent, compared with seven percent for full-time workers, and -3 percent for part-time workers. During the provided time period, the gender pay gap was at its highest in 1997, when it was 27.5 percent for all workers. Compared with 1997, the gender pay gap has fallen by 13.2 percent for all workers, and 9.7 percent for full-time workers. Gender pay gap higher in older age groups Although the gender pay gap among younger age groups was relatively small in 2024, the double-digit pay gap evident in older age groups served to keep the overall gap high. The gender pay gap for workers aged between 18 and 21 for example was -0.5 percent, compared with 12.1percent for people in their 50s. Additionally, the gender pay gap for people aged over 60 has changed little since 1997, falling by just 1.2 percent between 1997 and 2023, compared with a 14.9 percent reduction among workers in their 40s. Positions of power As of 2024, women are unfortunately still relatively underrepresented in leadership positions at Britain’s top businesses. Among FTSE 100 companies, for example, just 9.4 percent of CEOs were female, falling to just 6.1 percent for FTSE 250 companies. Representation was better when it came to FTSE 100 boardrooms, with 44.7 percent of positions at this level being filled by women, compared with 42.6 percent at FTSE 250 companies. In the corridors of political power, the proportion of female MPs was estimated to have reached its highest ever level after the 2024 election at 41 percent, compared with just three percent in 1979.

Abstract

The 1997 Reproductive Health Survey (RPS) is the sixth in a series of periodic enquiries conducted for the National Family Planning Board (NFPB) into measures of fertility, contraception and other reproductive health issues among women in the reproductive age group and young adults males. The findings are used to monitor and evaluate the effectiveness of the various interventions, which are aimed at achieving the overall goal and objectives of the national programme. It was previously called the Contraceptive Prevalence Survey (CPS) and covered a wide range of issues mainly related to family planning. With the recognition at the 1994 International Conference on Population and Development (ICPD) in Cairo that family planning is the single most important intervention in achieving reproductive health goals, it has been renamed the Reproductive Health Survey. In order to provide reproductive health services to young adults 15-24 years old, a young adult module was also included. Additional questions have been explored in the survey as they related to pap smears and breast self-examination.

Geographic coverage

National.

Results are shown by health regions and by urban and rural areas of residence as well as by demographic and socio economic characteristics. These variables have been selected as being important to the assessment of current programmes and to provide guidelines to areas that might benefit from special or intensified programme efforts. Some data was also produced at the parish level to inform parish administrators of the successes or weaknesses of their programmes.

Analysis unit

Women aged 15-49 and young adult men aged 15-24

Universe

The survey was of women aged 15-49 years and young men aged 15-24 years. Coverage of women was the same as that of the 1983 and 1989 Jamaica Contraceptive Prevalence Surveys, whereas the 1993 survey covered women aged 15-44 years. Conversely, the 1993 survey covered men aged 15-54 years, which provided information used to develop male responsibility programmes for preventing unintended pregnancies.

The 1993 coverage of men was not repeated in this survey, as preference was given to enlarging the sample of women so as to provide information at the parish level. Thus, the 1997 JRHS was designed to be the most comprehensive of the enquiries undertaken since 1983 by providing detailed information on women in their most active reproductive years (15-49) and on young adult males in the 15 to 24-year-old group.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 1997 JRHS utilized the design adopted for the Continuous Social and Demographic Surveys conducted by the Statistical Institute of Jamaica. This design was based on a two-stage stratified sample in which the first stage is a selection of geographic areas and the second stage is a selection of dwellings. For the selection of the first stage units, the country was divided into enumeration districts (EDs), which were grouped into sampling regions consisting of a predetermined number of strata, approximately equal in size (where size is measured by the number of dwellings in each sampling region). Two EDs within each sampling region, selected with probability proportionate to size (determined by the number of dwellings), made up the sample at the first stage. At the second stage, a second predetermined number of dwellings were selected systematically from lists of dwellings arranged on a circular basis in each of the EDs designated in the first stage of selection. The third stage in this survey consisted of the random selection of one eligible male aged 15-24 or female aged 15-49 from the selected dwellings.

In the 1997 JRHS, the female sample was selected at the parish level and the male sample was, as in 1993, selected at the health region level. In the general sample design used by STATIN, the first stage sample was selected by using identical sampling fractions in each parish. The second stage selection of separate male and female households was made in the field. This facilitated enumeration of eligible respondents wherever possible at the first visit. The small populations of Hanover and Trelawny parishes necessitated oversampling the households in order to obtain a large enough sample to obtain meaningful estimates at the parish level. Based on these selections, and taking into consideration expected non-response rates, it was anticipated that a total of approximately 15,046 households would be needed in the female survey and 14,620 households in the male survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four separate survey instruments were developed for use in the 1997 Reproductive Health Survey; one household questionnaire and one individual questionnaire for both male and female surveys.

The Household Questionnaires - Forms RHS 1A and 1B, were used mainly to record information on gender and age to identify eligible members of the household from which the third stage sample was selected. One male aged 15-24 and one female aged 15-49 were then selected by using a random number chart.

The Individual Questionnaires were developed for recording the information collected from women and young adult men selected for interviewing.

The female Individual Questionnaire (Form RHS 2) was divided into the following nine sections: - Section I Respondent's Background - Section II Relationship Status and Partnership History - Section III Fertility and Maternal Morbidity - Section IV Cancer Screening - Section V Contraceptive Knowledge and Usage - Section VI Attitudes towards Contraception, Childbearing and Current Sexual Activity - Section VII Family Life and Sex Education - Section VIII Early Sexual Experience and Child Rearing - Section IX General Attitudes and Opinions

The eight sections in the male Individual Questionnaire (Form RHS 3) are as follows: - Section I Respondent's Background - Section II Relationship Status and Partnership History - Section III Family Life and Sex Education - Section IV Reproductive History - Section V Contraceptive Knowledge and First Sexual Experience - Section VI Current Sexual Activity and Contraceptive Use - Section VII Attitudes towards Childbearing and Contraception - Section VIII General Attitudes and Opinions

The individual questionnaires were designed to provide comparisons with earlier surveys including the 1975/76 Jamaica Fertility Survey; the 1983, 1989 and 1993 Contraceptive Prevalence Surveys; and the 1987 Young Adult Reproductive Health Survey. To design the questionnaire, consultations were held between the Division of Reproductive Health, Centers for Disease Control and Prevention (CDC), whose core questionnaires for family planning, maternal-child health and young adult reproductive health surveys provided guidelines; the National Family Planning Board; the Ministry of Health, United States Agency for International Development, the Survey Director; and the Statistical Institute of Jamaica.

Response rate

Of the total number of 15,140 households selected in the female survey, there were 6,641 (43.9 percent) eligible respondents identified; in the male survey, the number of eligible respondents was 2,470 (17.7 percent). Of the eligible households in the female survey, 12,124 questionnaires (80.1 percent) were completed; in the male survey, 11,159 questionnaires (80.2 percent) were completed.

One respondent was selected from each eligible household. There were 6,384 completed questionnaires (96.1 percent) in the female survey and 2,279 (92.3 percent) in the male survey.

All national results in the final report have been weighted to compensate for the over-sampling of smaller health regions and selection of one respondent per household.

Sampling error estimates

The estimates for a sample survey are affected by two types of errors: non-sampling error and sampling error. Non-sampling error is the result of mistakes made in carrying out data collection and data processing, including the failure to locate and interview the right household, errors in the way questions are asked or understood, and data entry errors. Although intensive quality-control efforts were made during the implementation of the 1997 JRHS to minimize this type of error, nonsampling errors are impossible to avoid altogether and difficult to evaluate statistically. Sampling error is a measure of the variability between an estimate and the true value of the population parameter intended to be estimated, which can be attributed to the fact that a sample rather than a complete enumeration was used to produce it. In other words, sampling error is the difference between the expected value for any variable measured in a survey and the value estimated by the survey. This sample is only one of the many probability samples that could have been selected from the female population aged 15-49 and the male population aged 15-24 using the same sample design and projected sample size. Each of these samples would have yielded slightly different results from the actual sample selected.

Because the statistics presented in the Final Report are based on a sample, they may differ by chance variations from the statistics that would result if all women 15-49 years of age and all men aged 15-24 in Jamaica would have been interviewed. Sampling error is usually measured in terms of the variance and standard error (square root of the variance) for a particular statistic (mean, proportion, Or ratio). The standard error (SE) can be used to calculate confidence intervals (CI) of the estimates within which we can say with a given level of certainty that the

This dataset includes percent distribution of births for females by age group in the United States since 1933. The number of states in the reporting area differ historically. In 1915 (when the birth registration area was established), 10 states and the District of Columbia reported births; by 1933, 48 states and the District of Columbia were reporting births, with the last two states, Alaska and Hawaii, added to the registration area in 1959 and 1960, when these regions gained statehood. Reporting area information is detailed in references 1 and 2 below. Trend lines for 1909–1958 are based on live births adjusted for under-registration; beginning with 1959, trend lines are based on registered live births. SOURCES NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/). REFERENCES National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf. Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf. National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf. Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.

This statistic depicts the share of demonstrations involving women globally from 1997 to July 22, 2020, by type. During this time period, 84.9 percent of demonstrations where women made up a majority or the entirety of demonstrators were peaceful protests.

Abstract

As in the previous Demographic and Health Surveys (DHS) conducted in 1990, 1997, 2002 and 2007 in Jordan, the primary objective of the 2009 Jordan Population and Family Health Survey (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, family planning, fertility preferences, and child mortality as well as the nutritional status of women and children. The data from these surveys can be used by program managers and policy makers to evaluate and improve existing programs. In addition, the JPFHS data will be useful to researchers and scholars interested in analyzing demographic trends in Jordan, as well as those conducting comparative, regional, or cross-national studies.

The content of the 2009 JPFHS has been significantly decreased from the 2007 survey: it does not include data on mother and child health, reproductive health, women’s status, domestic violence, and early childhood development. However, a sub-sample of women age 15-49 and children age 6-59 months were tested to measure the prevalence of anemia. Height and weight of all women age 15-49 and children age five and under were also measured to assess their nutritional status.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN

The 2009 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, urban and rural areas, each of the 12 governorates, and Badia and non-Badia areas. To ensure comparability with the previous surveys, the sample was also designed to provide estimates for the three regions, North, Central and South. The grouping of the governorates into the regions is as follows: the North region consists of Irbid, Jarash, Ajloun, and Mafraq; the Central region consists of Amman, Madaba, Balqa, and Zarqa; and the South region consists of Karak, Tafiela, Ma'an, and Aqaba.

The 2009 JPFHS sample was designed using the 2004 Population and Housing Census as the sampling frame. The sampling frame was stratified by governorate, major cities, other urban, and other rural within each stratum. A two-stage sampling procedure was employed. First, blocks were selected systematically as primary sampling units (PSUs) with a probability proportional to the size of the PSU. A total of 930 PSUs were selected at this stage. In the second stage, a fixed number of 16 households were selected as final sampling units in each PSU, resulting in a sample size of about 15,000 households. Blood testing (for anemia) and the measurements of height and weight were conducted among eligible individuals in the selected households in 465 PSUs (half of the sample).

UPDATING OF SAMPLING FRAME

Prior to the main fieldwork, mapping operations were carried out and the sample units/blocks were selected and then identified and located in the field. The selected blocks were delineated, and the outer boundaries were demarcated with special signs. During this process, the numbers on buildings, housing units, and households were updated, listed, and documented, along with the name of the owner/tenant of the housing unit and the name of the household head. These activities were completed during the second quarter of 2009.

Note: See detailed description of sample design in APPENDIX A of the final report which is presented in this documentation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2009 JPFHS used two questionnaires—namely, the Household Questionnaire and the Individual Questionnaire. Both questionnaires were developed in English and Arabic, based on the questionnaires used in the 2007 survey, in collaboration with ICF Macro. The Household Questionnaire was used to list all usual members and visitors of the sampled households and to obtain information on each household member’s age, sex, educational attainment, relationship to the head of household, and marital status. In addition, questions were included on the socioeconomic characteristics of the household, such as source of water, sanitation facilities, and availability of durable goods.

The Household Questionnaire was also used to identify women who were eligible for the individual interview: ever-married women age 15-49. In addition, in half of the households, all women age 15-49 and children under five years of age were measured to determine nutritional status. Children age 6-59 months and women age 15-49 were tested for anemia.

The household and women’s questionnaires were based on the DHS standard questionnaire. Additions and modifications to the model questionnaire were made in order to provide detailed information specific to Jordan, using experience gained from the 1990, 1997, 2002, and 2007 JPFHS. For each ever-married woman age 15-49, information on the following topics was collected: • Respondent’s general background • Birth history • Family planning • Marriage • Fertility preferences • Respondent’s employment

In addition, information on births and pregnancies, contraceptive use and discontinuation, and marriage during the five years prior to the survey was collected using a monthly calendar for this purpose.

As previously mentioned, anthropometric data were collected during the 2009 JPFHS in a subsample of 50 percent of clusters. All women age 15-49 and children age 0-4 in these households were measured using Shorr height boards and weighed using electronic Seca scales. In addition, a drop of capillary blood was taken from these women and children age 6-59 months to measure, in the field, their hemoglobin level using the HemoCue system. Hemoglobin testing was used to estimate the prevalence of anemia.

Response rate

A total of 14,872 households were selected for the survey from the sampling frame; among those selected households, 13,959 households were found. Of those households, 13,577 (97 percent) were successfully interviewed. In those households, 10,401 eligible women were identified, and complete interviews were obtained with 10,109 of them (97 percent of all eligible women). The overall response rate (the household’s response rate multiplied by the eligible woman response rate) was about 95 percent.

Note: See summarized response rates by place of residence in Table 1.1 of the final report which is presented in this documentation.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling 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 2009 Jordan Population and Family Health Survey (JPFHS) to minimize this type of error, non-sampling 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 2009 JPFHS is only one of many samples that could have been selected from the same population, using the same design and expected 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 among 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 percent 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 2009 JPFHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2009 JPFHS is a Macro SAS procedure. This procedure used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: See detailed estimate of sampling error calculation in APPENDIX B of the report which is presented in this documentation.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Nutritional status of children (JPFHS 2002 based on the WHO Child Growth Standards)

Note: See for the detail in APPENDIX C of the final report which is presented in this documentation.

Worldwide, women in households with children under six years have lower labor market participation rates than men. About 54 percent of women in households with children under six participate in the labor market, while men have a participation rate of about 96 percent. The largest gap lies within Central Asia and Southern Asia, where 28 percent of women and 97 percent of men participate in the labor market, and Northern Africa and Western Asia, where 26 percent of women and 95 percent of men participate in the labor market. Such gaps reflect the prominence of gender roles and the amount of unpaid, domestic labor performed by women.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Wheeler town. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Wheeler town, the median income for all workers aged 15 years and older, regardless of work hours, was $43,452 for males and $44,427 for females.

Contrary to expectations, women in Wheeler town, women, regardless of work hours, earn a higher income than men, earning 1.02 dollars for every dollar earned by men. This analysis indicates a significant shift in income dynamics favoring females.

- Full-time workers, aged 15 years and older: In Wheeler town, among full-time, year-round workers aged 15 years and older, males earned a median income of $50,417, while females earned $48,777, resulting in a 3% gender pay gap among full-time workers. This illustrates that women earn 97 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the town of Wheeler town.

Surprisingly, across all roles (including non-full-time employment), women had a higher median income compared to men in Wheeler town. This might indicate a more favorable income scenario for female workers across different employment patterns within the town of Wheeler town, especially in non-full-time positions.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Wheeler town median household income by race. You can refer the same here

Yemen YE: Women Who were First Married by Age 15: % of Women Aged 20-24 data was reported at 9.400 % in 2013. This records a decrease from the previous number of 14.000 % for 1997. Yemen YE: Women Who were First Married by Age 15: % of Women Aged 20-24 data is updated yearly, averaging 14.000 % from Dec 1992 (Median) to 2013, with 3 observations. The data reached an all-time high of 20.400 % in 1992 and a record low of 9.400 % in 2013. Yemen YE: Women Who were First Married by Age 15: % of Women Aged 20-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Yemen – Table YE.World Bank.WDI: Population and Urbanization Statistics. Women who were first married by age 15 refers to the percentage of women ages 20-24 who were first married by age 15.; ; Demographic and Health Surveys (DHS); ;