BackgroundThe risk factors for tuberculosis (TB) disease development in children remained understudied, particularly in low-income countries like Ethiopia. The objective of this study was to identify determinants of TB disease development in general and in relation to BCG vaccination in children in central Ethiopia.MethodsWe employed a 1:1 age-matched case-control design to compare the characteristics of children who developed TB (cases) with those who did not (controls). Data were collected in healthcare facilities in Addis Ababa city, Adama, and Bishoftu towns between September 25, 2021, and June 24, 2022. Two hundred and fifty-six cases were drawn at random from a list of childhood TB patients entered into SPSS software, and 256 controls were selected sequentially at triage from the same healthcare facilities where the cases were treated. A bivariate conditional logistic regression analysis was performed first to select candidate variables with p-values less than or equal to 0.20 for the multivariable model. Finally, variables with a p-value less than 0.05 for a matched adjusted odds ratio (mORadj) were reported as independent determinants of TB disease development.ResultsThe mean age of the cases was nine years, while that of the controls was 10 years. Males comprised 126 cases (49.2%) and 119 controls (46.5%), with the remainder being females. Ninety-nine (38.7%) of the cases were not BCG-vaccinated, compared to 58 (22.7%) of the controls. Household TB contact was experienced by 43 (16.8%) of the cases and 10 (3.9%) of the controls. Twenty-two (8.6%) of the cases and six (2.3%) of the controls were exposed to a cigarette smoker in their household. Twenty-two (8.6%) of the cases and three (1.2%) of the controls were positive for HIV. Children who were not vaccinated with BCG at birth or within two weeks of birth had more than twice the odds (mORadj = 2.11, 95% CI = 1.28–3.48) of developing TB compared to those who were. Children who ever lived with a TB-sick family member (mORadj = 4.28, 95% CI = 1.95–9.39), smoking family members (mORadj = 3.15, 95% CI = 1.07–9.27), and HIV-infected children (mORadj = 8.71, 95% CI = 1.96–38.66) also had higher odds of developing TB disease than their counterparts.ConclusionsBeing BCG-unvaccinated, having household TB contact, having a smoker in the household, and being HIV-infected were found to be independent determinants of TB disease development among children.

Abstract

The basic goal of this survey is to provide the necessary database for formulating national policies at various levels. It represents the contribution of the household sector to the Gross National Product (GNP). Household Surveys help as well in determining the incidence of poverty, and providing weighted data which reflects the relative importance of the consumption items to be employed in determining the benchmark for rates and prices of items and services. Generally, the Household Expenditure and Consumption Survey is a fundamental cornerstone in the process of studying the nutritional status in the Palestinian territory.

The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality. Data is a public good, in the interest of the region, and it is consistent with the Economic Research Forum's mandate to make micro data available, aiding regional research on this important topic.

Geographic coverage

The survey data covers urban, rural and camp areas in West Bank and Gaza Strip.

Analysis unit

1- Household/families. 2- Individuals.

Universe

The survey covered all the Palestinian households who are a usual residence in the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample and Frame:

The sampling frame consists of all enumeration areas which were enumerated in 1997; the enumeration area consists of buildings and housing units and is composed of an average of 120 households. The enumeration areas were used as Primary Sampling Units (PSUs) in the first stage of the sampling selection. The enumeration areas of the master sample were updated in 2003.

Sample Design:

The sample is a stratified cluster systematic random sample with two stages: First stage: selection of a systematic random sample of 299 enumeration areas. Second stage: selection of a systematic random sample of 12-18 households from each enumeration area selected in the first stage. A person (18 years and more) was selected from each household in the second stage.

Sample strata:

The population was divided by: 1- Governorate 2- Type of Locality (urban, rural, refugee camps)

Sample Size:

The calculated sample size is 3,781 households.

Target cluster size:

The target cluster size or "sample-take" is the average number of households to be selected per PSU. In this survey, the sample take is around 12 households.

Detailed information/formulas on the sampling design are available in the user manual.

Mode of data collection

Face-to-face [f2f]

Research instrument

The PECS questionnaire consists of two main sections:

First section: Certain articles / provisions of the form filled at the beginning of the month,and the remainder filled out at the end of the month. The questionnaire includes the following provisions:

Cover sheet: It contains detailed and particulars of the family, date of visit, particular of the field/office work team, number/sex of the family members.

Statement of the family members: Contains social, economic and demographic particulars of the selected family.

Statement of the long-lasting commodities and income generation activities: Includes a number of basic and indispensable items (i.e, Livestock, or agricultural lands).

Housing Characteristics: Includes information and data pertaining to the housing conditions, including type of shelter, number of rooms, ownership, rent, water, electricity supply, connection to the sewer system, source of cooking and heating fuel, and remoteness/proximity of the house to education and health facilities.

Monthly and Annual Income: Data pertaining to the income of the family is collected from different sources at the end of the registration / recording period.

Second section: The second section of the questionnaire includes a list of 54 consumption and expenditure groups itemized and serially numbered according to its importance to the family. Each of these groups contains important commodities. The number of commodities items in each for all groups stood at 667 commodities and services items. Groups 1-21 include food, drink, and cigarettes. Group 22 includes homemade commodities. Groups 23-45 include all items except for food, drink and cigarettes. Groups 50-54 include all of the long-lasting commodities. Data on each of these groups was collected over different intervals of time so as to reflect expenditure over a period of one full year.

Cleaning operations

Raw Data

Both data entry and tabulation were performed using the ACCESS and SPSS software programs. The data entry process was organized in 6 files, corresponding to the main parts of the questionnaire. A data entry template was designed to reflect an exact image of the questionnaire, and included various electronic checks: logical check, range checks, consistency checks and cross-validation. Complete manual inspection was made of results after data entry was performed, and questionnaires containing field-related errors were sent back to the field for corrections.

Harmonized Data

• The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets.
• The harmonization process starts with cleaning all raw data files received from the Statistical Office.
• Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/compute/recode/rename/format/label harmonized variables.
• A post-harmonization cleaning process is run on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Response rate

The survey sample consists of about 3,781 households interviewed over a twelve-month period between January 2004 and January 2005. There were 3,098 households that completed the interview, of which 2,060 were in the West Bank and 1,038 households were in GazaStrip. The response rate was 82% in the Palestinian Territory.

Sampling error estimates

The calculations of standard errors for the main survey estimations enable the user to identify the accuracy of estimations and the survey reliability. Total errors of the survey can be divided into two kinds: statistical errors, and non-statistical errors. Non-statistical errors are related to the procedures of statistical work at different stages, such as the failure to explain questions in the questionnaire, unwillingness or inability to provide correct responses, bad statistical coverage, etc. These errors depend on the nature of the work, training, supervision, and conducting all various related activities. The work team spared no effort at different stages to minimize non-statistical errors; however, it is difficult to estimate numerically such errors due to absence of technical computation methods based on theoretical principles to tackle them. On the other hand, statistical errors can be measured. Frequently they are measured by the standard error, which is the positive square root of the variance. The variance of this survey has been computed by using the “programming package” CENVAR.

BackgroundMental health disorders among adolescents is on the rise globally. Patients seldom present to mental health physicians, for fear of stigmatization, and due to the dearth of mental health physicians. They are mostly picked during consultations with Family Physicians. This study seeks to identify the common mental health disorders seen by family Physicians in Family Medicine Clinics in Nigeria and Ghana.MethodsA descriptive cross-sectional study involving 302 Physicians practicing in Family Medicine Clinics in Nigeria and Ghana, who were randomly selected for the study. Data were collected using self-administered semi-structured questionnaire, and were entered into excel spreadsheet before analysing with IBM-SPSS version 22. Descriptive statistics using frequencies and percentages was used to describe variables.ResultsOf the 302 Physicians recruited for the study, only 233 completed the study, in which 168 (72.1%) practiced in Nigeria and 65 (27.9%) in Ghana. They were mostly in urban communities (77.3%) and tertiary health facilities (65.2%). Over 90% of Family Medicine practitioners attended to adolescents with mental health issues with over 70% of them seeing at least 2 adolescents with mental health issues every year. The burden of mental health disorder was 16% and the common mental health disorders seen were depression (59.2%), Bipolar Affective Disorder (55.8%), Epilepsy (51.9%) and Substance Abuse Disorder (44.2%).ConclusionFamily Physicians in Nigeria and Ghana attend to a good number of adolescents with mental health disorders in their clinics. There is the need for Family Physicians to have specialized training and retraining to be able to recognize and treat adolescent mental health disorders. This will help to reduce stigmatization and improve the management of the disease thus, reducing the burden.

Abstract (en): This survey is the first broad-based, systematic examination of the nature of civil litigation in state general jurisdiction trial courts. Data collection was carried out by the National Center for State Courts with assistance from the National Association of Criminal Justice Planners and the United States Bureau of the Census. The data collection produced two datasets. Part 1, Tort, Contract, and Real Property Rights Data, is a merged sample of approximately 30,000 tort, contract, and real property rights cases disposed during the 12-month period ending June 30, 1992. Part 2, Civil Jury Cases Data, is a sample of about 6,500 jury trial cases disposed over the same time period. Data collected include information about litigants, case type, disposition type, processing time, case outcome, and award amounts for civil jury cases. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Checked for undocumented or out-of-range codes.. Forty-five jurisdictions chosen to represent the 75 most populous counties in the nation. The sample for this study was designed and selected by the United States Bureau of the Census. It was a two-stage stratified sample with 45 of the 75 most populous counties selected at the first stage. The top 75 counties account for about 37 percent of the United States population and about half of all civil filings. The 75 counties were divided into four strata based on aggregate civil disposition data for 1990 obtained through telephone interviews with court staffs in the general jurisdiction trial courts. The sample consisted of tort, contract, and real property rights cases disposed between July 1, 1991, and June 30, 1992. 2011-11-02 All parts are being moved to restricted access and will be available only using the restricted access procedures.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions.2004-06-01 The data have been updated by the principal investigator to include replicate weights and a few other variables. The codebook and SAS and SPSS data definition statements have been revised to reflect these changes.2001-03-26 The data have been updated by the principal investigator to include replicate weights. The codebook and SAS and SPSS data definition statements have been revised to reflect these changes.2001-03-26 The data had been updated by the principal investigator to include replicate weights. The codebook and SAS and SPSS data definition statements had been revised to reflect these changes.1997-07-29 The codebook had been revised to correct errors documenting both data files. Column location (and width) of variable WGHT "TOTAL WEIGHT" was incorrectly shown as 10.4 for Part 1, Tort, Contract, and Real Property Data. It was accurately shown in the data definition statements as 9.4. Variables listed after WGHT were inaccurately reported one column off in the codebook. Similarly, column location (and width) of variable WGHT "TOTAL WEIGHT" was incorrectly shown as 10.2 for Part 2, Civil Jury Data. It was accurately shown in the data definition statements as 9.2. Variables listed after WGHT were inaccurately reported one column off in the codebook. Fundi...

The impact of the Global Programme to Eliminate Lymphatic Filariasis (GPELF) (initiated in 2000 in Ghana and ran for 12 years) in mitigating soil-transmitted helminth (STH) infections in LF-endemic areas is unknown. During a 1-year hiatus which ensued between 2011 and 2012, a longitudinal study was conducted to determine GPELF effect on hookworm infections in selected communities involved in the programme since its inception, while measuring the effectiveness of biannual ALB treatments on schoolchildren living in such communities. A total of 399 school children aged 3 to 18 years were randomly selected from four communities in the Kpandai district of northern Ghana. Each presented a single stool sample at baseline, 21 days post-treatment, at the 3rd and 6th months, 21 days post-second intervention (i.e. following sample collection and treatment with ALB in the 6th month), and in the ninth month of the study period. Haemoglobin (hb) levels were also measured at all time points using finger prick blood samples and a URIT digital test kit. Each participant submitting a sample, was treated with a single-dose ALB (400mg) at baseline and in the sixth month. Stool samples were processed by preparing duplicate Kato-Katz slides per sample, and examined by microscopy. The Body Mass Index-for-age z-scores (BAZ) of participants were assessed following the determination of BMIs at each time point by measuring their height and weight with a stadiometer and weighing scale. Overall hookworm prevalences were 25.68% (95% CI = 20.51–31.75) at baseline, 11.18% (95% CI = 7.87–15.41) 21 days post-treatment, 11.78% (95% CI = 8.38–16.11) and 6.95% (95% CI = 4.41–10.43) in the 3rd and 6th months, 0.91% (95% CI = 0.19–2.65) 21 days post-second intervention, and 8.46% (95% CI = 5.62–12.23) in the ninth month. Observed overall faecal egg count reduction rates (ERRs) were 94.21% (95% CI = 81.50%– 100.00%) 21 days after baseline treatment, 97.70% (95% CI = 85.08–100.00) and 96.95% (95% CI = 84.18%– 100.00%) in the 3rd and 6th months, 99.98% (95% CI = 86.42%– 100.00%) 21 days post-second intervention, and 17.18% (95% CI = 14.07%– 20.67%) in the 9th month. Respective cure rates (CRs) were 62.35% (95% CI = 46.71–81.56%), 85.88% (95% CI = 67.32–100.00%), 87.06% (95% CI = 68.36%– 100.00%), 98.82% (95% CI = 78.83%– 100.00%), and 36.36% (95% CI = 9.91%– 93.11%). Additionally, increases in the percent frequency of ‘normal hb’ (p < 0.01) were observed across the study time points, whilst ‘normal BAZ’ cases remained high (from 94.87% to 98.87%) throughout the study period. These findings primarily indicate satisfactory effectiveness of ALB which may be maintainable in mass drug administration programmes by the modification of treatment strategies from annual to bi-annual regimes. This could minimize the likelihood of emerging poorly-responding hookworm phenotypes in Ghana. Additionally, a positive impact of bi-annual treatment on participant anaemia status is herein indicated with particular regard to the school children in our cohort.

Data from: Doctoral dissertation; Preprint article entitled: Managers' and physicians’ perception of palm vein technology adoption in the healthcare industry. Formats of the files associated with dataset: CSV; SAV. SPSS setup files can be used to generate native SPSS file formats such as SPSS system files and SPSS portable files. SPSS setup files generally include the following SPSS sections: DATA LIST: Assigns the name, type, decimal specification (if any), and specifies the beginning and ending column locations for each variable in the data file. Users must replace the "physical-filename" with host computer-specific input file specifications. For example, users on Windows platforms should replace "physical-filename" with "C:\06512-0001-Data.txt" for the data file named "06512-0001-Data.txt" located on the root directory "C:". VARIABLE LABELS: Assigns descriptive labels to all variables. Variable labels and variable names may be identical for some variables. VALUE LABELS: Assigns descriptive labels to codes in the data file. Not all variables necessarily have assigned value labels. MISSING VALUES: Declares user-defined missing values. Not all variables in the data file necessarily have user-defined missing values. These values can be treated specially in data transformations, statistical calculations, and case selection. MISSING VALUE RECODE: Sets user-defined numeric missing values to missing as interpreted by the SPSS system. Only variables with user-defined missing values are included in the statements. ABSTRACT: The purpose of the article is to examine the factors that influence the adoption of palm vein technology by considering the healthcare managers’ and physicians’ perception, using the Unified Theory of Acceptance and Use of Technology theoretical foundation. A quantitative approach was used for this study through which an exploratory research design was utilized. A cross-sectional questionnaire was distributed to responders who were managers and physicians in the healthcare industry and who had previous experience with palm vein technology. The perceived factors tested for correlation with adoption were perceived usefulness, complexity, security, peer influence, and relative advantage. A Pearson product-moment correlation coefficient was used to test the correlation between the perceived factors and palm vein technology. The results showed that perceived usefulness, security, and peer influence are important factors for adoption. Study limitations included purposive sampling from a single industry (healthcare) and limited literature was available with regard to managers’ and physicians’ perception of palm vein technology adoption in the healthcare industry. Researchers could focus on an examination of the impact of mediating variables on palm vein technology adoption in future studies. The study offers managers insight into the important factors that need to be considered in adopting palm vein technology. With biometric technology becoming pervasive, the study seeks to provide managers with the insight in managing the adoption of palm vein technology. KEYWORDS: biometrics, human identification, image recognition, palm vein authentication, technology adoption, user acceptance, palm vein technology

BackgroundThe clinical manifestations of Corona Virus Disease of 2019 (COVID-19) varied from patient to patient with evidence of multi-organ involvement. Many patients continue to have a wide range of symptoms for variable periods of time. The long-term effects of COVID-19 infection (post COVID-19 illness or syndrome) are not yet fully explored. This study aims to shed light on the clinical manifestations of the acute COVID-19 infection as well as post COVID-19 syndrome among the United Nations Relief and Works Agency for Palestine Refugee (UNRWA) staff in Jordan.MethodsA clinical case-series was conducted on a sample of COVID-19 positive employees of the UNRWA staff in Jordan. A structured questionnaire based mainly on World Health Organization (WHO) Case Report Form (CRF) verified tool for post COVID-19 was used. A sample of 366 out of a total of 1322 confirmed cases was systemically selected and included in the present study. Data were collected from UNRWA medical records and phone interviews. Data were analyzed using the Statistical Package for Social Sciences (SPSS) software.ResultsThe calculated Case Fatality Ratio was 0.7%. The incidence of COVID-19 among UNRWA staff in Jordan during the period of our study was 20.1%. A total of 366 respondents, 220 (60.1%) females and 146 (39.9%) males were included in the study. The mean (SD) age was 44.2 (8.0) years. Most of the infected (97.8%) developed acute COVID-19 symptoms. Fatigue, fever, joint pain, loss of smell and taste, and cough were the most common symptoms. According to WHO clinical classification of acute illness severity, 65.0% had mild illness. Only 28.7% of all subjects fully recovered from the infection, while most of them (71.3%) continued to suffer from many symptoms. Persistent fatigue (39.7%), shortness of breath (SOB) with activity (18.8%), anxiety (17.4%), forgetfulness (16.9%), trouble in concentrating (16.7%), and depressed mood (15.8%) were the most frequently reported.ConclusionPost COVID-19 illness was very common (71.3%) calling for UNRWA to continue assessment of post COVID-19 syndrome and the medical and psychological needs of affected staff. Despite vaccination, only 2.2% of the infected were asymptomatic. Reinfection was unusually high (24%).

This is an Annotation for Transparent Inquiry (ATI) data project. The annotated article can be viewed on the Publisher's Website. Data Generation The research project engages a story about perceptions of fairness in criminal justice decisions. The specific focus involves a debate between ProPublica, a news organization, and Northpointe, the owner of a popular risk tool called COMPAS. ProPublica wrote that COMPAS was racist against blacks, while Northpointe posted online a reply rejecting such a finding. These two documents were the obvious foci of the qualitative analysis because of the further media attention they attracted, the confusion their competing conclusions caused readers, and the power both companies wield in public circles. There were no barriers to retrieval as both documents have been publicly available on their corporate websites. This public access was one of the motivators for choosing them as it meant that they were also easily attainable by the general public, thus extending the documents’ reach and impact. Additional materials from ProPublica relating to the main debate were also freely downloadable from its website and a third party, open source platform. Access to secondary source materials comprising additional writings from Northpointe representatives that could assist in understanding Northpointe’s main document, though, was more limited. Because of a claim of trade secrets on its tool and the underlying algorithm, it was more difficult to reach Northpointe’s other reports. Nonetheless, largely because its clients are governmental bodies with transparency and accountability obligations, some of Northpointe-associated reports were retrievable from third parties who had obtained them, largely through Freedom of Information Act queries. Together, the primary and (retrievable) secondary sources allowed for a triangulation of themes, arguments, and conclusions. The quantitative component uses a dataset of over 7,000 individuals with information that was collected and compiled by ProPublica and made available to the public on github. ProPublica’s gathering the data directly from criminal justice officials via Freedom of Information Act requests rendered the dataset in the public domain, and thus no confidentiality issues are present. The dataset was loaded into SPSS v. 25 for data analysis. Data Analysis The qualitative enquiry used critical discourse analysis, which investigates ways in which parties in their communications attempt to create, legitimate, rationalize, and control mutual understandings of important issues. Each of the two main discourse documents was parsed on its own merit. Yet the project was also intertextual in studying how the discourses correspond with each other and to other relevant writings by the same authors. Several more specific types of discursive strategies were of interest in attracting further critical examination: Testing claims and rationalizations that appear to serve the speaker’s self-interest Examining conclusions and determining whether sufficient evidence supported them Revealing contradictions and/or inconsistencies within the same text and intertextually Assessing strategies underlying justifications and rationalizations used to promote a party’s assertions and arguments Noticing strategic deployment of lexical phrasings, syntax, and rhetoric Judging sincerity of voice and the objective consideration of alternative perspectives Of equal importance in a critical discourse analysis is consideration of what is not addressed, that is to uncover facts and/or topics missing from the communication. For this project, this included parsing issues that were either briefly mentioned and then neglected, asserted yet the significance left unstated, or not suggested at all. This task required understanding common practices in the algorithmic data science literature. The paper could have been completed with just the critical discourse analysis. However, because one of the salient findings from it highlighted that the discourses overlooked numerous definitions of algorithmic fairness, the call to fill this gap seemed obvious. Then, the availability of the same dataset used by the parties in conflict, made this opportunity more appealing. Calculating additional algorithmic equity equations would not thereby be troubled by irregularities because of diverse sample sets. New variables were created as relevant to calculate algorithmic fairness equations. In addition to using various SPSS Analyze functions (e.g., regression, crosstabs, means), online statistical calculators were useful to compute z-test comparisons of proportions and t-test comparisons of means. Logic of Annotation Annotations were employed to fulfil a variety of functions, including supplementing the main text with context, observations, counter-points, analysis, and source attributions. These fall under a few categories. Space considerations. Critical discourse analysis offers a rich method...

In this dataset we present core data of an integrative evaluation framework for assessing the environmental, social, and economic sustainability of urban agriculture. The multi-criteria analysis is conducted by an Analytic Hierarchy Process and a participatory approach. The data integrate the selection and weighting of sub-criteria based on two online surveys:

1) Survey 1: The selection of suitable sub-criteria for assessing the sustainability of urban agriculture was done by European scientific experts.

2) Survey 2: The weighting of the selected sub-criteria was done on the example of vertical farming and community supported agriculture. Therefore, we involved stakeholders representing key actors for the implementation of urban agriculture: city administrations and non-governmental organizations (NGOs) of ten German case study cities, practitioners and technical-scientific experts.

List of data and content

1) Survey_1 (*.zip):

Survey_1_Criteria_Selection_English: Online survey in English (*.pdf)

Survey_1_Information_Sub-criteria_English: Information about the sub-criteria provided in the survey (in English) (*.pdf)

Survey_1_Groups: Results of the statistical analyses (U-tests and Kruscal-Wallis) to detect group-specific differences (e.g. gender, different length or degree of experience with urban agriculture, scientific focus, target group, expertise); the tests were conducted with IBM SPSS Statistics 25 (*.xlsx)

2) Survey_2 (*.zip):

Survey_2_AHP_City_Administrations_German: Online survey for city administrations in German (*.pdf)

Survey_2_AHP_Practitioners_German: Online survey for practitioners and technical-scientific experts in German (*.pdf)

Survey_2_AHP_NGOs_German: Online survey for NGOs in German (*.pdf)

Survey_2_Information_Sub-Criteria_German: Information about the sub-criteria provided in the survey (in German) (*.pdf)

Survey_2_Groups: Results of the statistical analyses (U-tests and Kruscal-Wallis) to detect group-specific differences (e.g. gender, different length or degree of experience with urban agriculture, scientific focus, target group, expertise); the tests were conducted with IBM SPSS Statistics 25 (*.xlsx)

rdata_CA_AHP_edible_Cities_2022-03-18_10-28: Results of the survey for city administrations (*.csv)

rdata_NGO_AHP_edible_Cities_2022-03-18_10-40: Results of the survey for NGOs (*.csv)

rdata_PE_AHP_edible_Cities_2022-03-18_10-41: Results of the survey for practitioners and technical-scientific experts (*.csv)

rdata_all_AHP_edible_Cities_2022-03-18_09-53: Total results of the survey

Data acquisition and processing

The methods are described in this linked publication:

John, H., & Artmann, M. (2024). Introducing an integrative evaluation framework for assessing the sustainability of different types of urban agriculture. International Journal of Urban Sustainable Development, 16 (1), 35-52. doi: 10.1080/19463138.2024.2317795

The methodology of the performed analytic hierarchy process (AHP) is published in a separate repository on GitHub including a paper that systematically explains the AHP by means of code examples, starting with the raw data, through their adaptation to the software functions of the ahpsurvey R-package, and finally, execution of the AHP up to the visualization of the results.

Acknowledgments

The authors thank Mabel Killinger and Marie Herzig for their help in stakeholder identification as well as all experts and stakeholders for their participation in the two online surveys and their helpful comments. Data processing and analysis by means of an Analytic Hierarchy Process in R would not have been possible without the help of Björn Kasper.

BackgroundTimely and appropriate health care seeking for diarrhea of under-five children is important to reduce severe and life-threatening complications. However, different findings indicate that mothers of under-five children often delay in seeking care which in turn contributes to the death of large number of children without ever reaching a health facility. Therefore, a proper pinpointing of determinants of delay in seeking care informs intervention strategies for health service planners.ObjectivesOf this study was to identify the determinants of delay in care seeking for diarrheal disease among mothers/caregivers of under-five children in public health facilities of Arba Minch town, South Ethiopia, 2019.MethodsFacility based case control study was conducted from March 4 to April 30, 2019. Total sample size was 400. Cases were selected by systematic random sampling technique while controls were mothers of under-five children with signs and symptoms of diarrhea who came to the same health facility within 24 hours following cases. Data was collected by using pretested structured questionnaire by three data collectors and entered into EpiData V4 and exported to SPSS V23 for further analysis. Bivariable logistic regression was done to identify variables candidate for Multivariable LR at p-value

Characteristics of cases at the time of TB diagnosis and that of controls at time of survey in a study conducted in central Ethiopia, 2022.

ObjectivesNeonatal sepsis is a leading cause of neonatal morbidity and mortality, particularly in the developing countries. Delays in the identification and treatment of neonatal sepsis are among the main contributors to the high mortality. The aim of this study was to determine the risk factors of neonatal sepsis in public hospitals of Mekelle City, Tigray Region, North Ethiopia, 2015.MethodsA hospital based case control study was done in public hospitals of Mekelle City, Tigray region. Cases were neonates who had sepsis with their index mothers and controls were neonates who hadn’t had sepsis with their index mothers. Hematologic findings were used to diagnose sepsis once the neonates were being clinically suspected. Cases and controls were selected using the systematic sampling technique. Data were entered using Epi info version 7 and then analyzed using SPSS window 20. The binary logistic regression model was used to test the association between dependent and independent variables and multivariable logistic regression was used to identify the associated risk factors to neonatal sepsis.FindingsA total of 78 cases and 156 controls were included in this study. More than three quarters (76.8%) of cases had early onset sepsis. The multivariable logistic regression analysis showed that the possible risk factors of neonatal sepsis in this study were; history of maternal urinary tract infection or sexually transmitted infection [AOR = 5. 23; 95% CI (1.82, 15.04)], prolonged rupture of membrane [AOR = 7. 43; 95% CI (2.04, 27.1)], Place of delivery; health center delivery [AOR = 5. 7; 95% CI (1.71, 19.03)], intrapartum fever [AOR = 6. 1 95% CI (1.29, 28.31)], APGAR score

BackgroundApproximately 16 million teenagers aged 15–19 years and 2 million teenagers under the age of 15 years give birth annually, with 95% of these births occurring in developing countries. Ethiopia has one of the highest teenage fertility rates in Sub-Saharan Africa; however determinants of teenage pregnancy are not well studied. Therefore, this study aimed to identify determinants of teenage pregnancy among female teenagers in Degua Tembien district, Tigray, Northern Ethiopia, in 2015.MethodsA community-based case-control study was conducted in Degua' Tembien district from February 01, 2015 to March 15, 2015 with a randomly selected total sample size of 414 females (with a ratio of 1:2 case to control, 138 and 276 respectively). Data were entered in to Epi-Info and analyzed using SPSS software. Multivariable logistic regression was used to assess predictors of the outcome variable; variables with a p-value

Maternal health service-related characteristics of mothers of neonates admitted to Public Hospitals in Hadiya Zone, Southern Ethiopia, 2021.

Factors associated with NNM in selected public hospitals of Jimma zone, southwest Ethiopia, 2020 (n = 255).

Sample size determination for determinants of neonatal near miss (NNM) among neonates admitted to public hospitals in Southern Ethiopia, 2021.

Abstract

The main objective of the HEIS survey is to obtain detailed data on household expenditure and income, linked to various demographic and socio-economic variables, to enable computation of poverty indices and determine the characteristics of the poor and prepare poverty maps. Therefore, to achieve these goals, the sample had to be representative on the sub-district level. The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality.

Data collected through the survey helped in achieving the following objectives: 1. Provide data weights that reflect the relative importance of consumer expenditure items used in the preparation of the consumer price index 2. Study the consumer expenditure pattern prevailing in the society and the impact of demograohic and socio-economic variables on those patterns 3. Calculate the average annual income of the household and the individual, and assess the relationship between income and different economic and social factors, such as profession and educational level of the head of the household and other indicators 4. Study the distribution of individuals and households by income and expenditure categories and analyze the factors associated with it 5. Provide the necessary data for the national accounts related to overall consumption and income of the household sector 6. Provide the necessary income data to serve in calculating poverty indices and identifying the poor chracteristics as well as drawing poverty maps 7. Provide the data necessary for the formulation, follow-up and evaluation of economic and social development programs, including those addressed to eradicate poverty

Geographic coverage

National

Analysis unit

• Household/families
• Individuals

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2008 Household Expenditure and Income Survey sample was designed using two-stage cluster stratified sampling method. In the first stage, the primary sampling units (PSUs), the blocks, were drawn using probability proportionate to the size, through considering the number of households in each block to be the block size. The second stage included drawing the household sample (8 households from each PSU) using the systematic sampling method. Fourth substitute households from each PSU were drawn, using the systematic sampling method, to be used on the first visit to the block in case that any of the main sample households was not visited for any reason.

To estimate the sample size, the coefficient of variation and design effect in each subdistrict were calculated for the expenditure variable from data of the 2006 Household Expenditure and Income Survey. This results was used to estimate the sample size at sub-district level, provided that the coefficient of variation of the expenditure variable at the sub-district level did not exceed 10%, with a minimum number of clusters that should not be less than 6 at the district level, that is to ensure good clusters representation in the administrative areas to enable drawing poverty pockets.

It is worth mentioning that the expected non-response in addition to areas where poor families are concentrated in the major cities were taken into consideration in designing the sample. Therefore, a larger sample size was taken from these areas compared to other ones, in order to help in reaching the poverty pockets and covering them.

Mode of data collection

Face-to-face [f2f]

Research instrument

List of survey questionnaires: (1) General Form (2) Expenditure on food commodities Form (3) Expenditure on non-food commodities Form

Cleaning operations

Raw Data The design and implementation of this survey procedures were: 1. Sample design and selection 2. Design of forms/questionnaires, guidelines to assist in filling out the questionnaires, and preparing instruction manuals 3. Design the tables template to be used for the dissemination of the survey results 4. Preparation of the fieldwork phase including printing forms/questionnaires, instruction manuals, data collection instructions, data checking instructions and codebooks 5. Selection and training of survey staff to collect data and run required data checkings 6. Preparation and implementation of the pretest phase for the survey designed to test and develop forms/questionnaires, instructions and software programs required for data processing and production of survey results 7. Data collection 8. Data checking and coding 9. Data entry 10. Data cleaning using data validation programs 11. Data accuracy and consistency checks 12. Data tabulation and preliminary results 13. Preparation of the final report and dissemination of final results

Harmonized Data - The Statistical Package for Social Science (SPSS) was used to clean and harmonize the datasets - The harmonization process started with cleaning all raw data files received from the Statistical Office - Cleaned data files were then all merged to produce one data file on the individual level containing all variables subject to harmonization - A country-specific program was generated for each dataset to generate/compute/recode/rename/format/label harmonized variables - A post-harmonization cleaning process was run on the data - Harmonized data was saved on the household as well as the individual level, in SPSS and converted to STATA format

(n = 414).

Multivariable logistic regression analysis of selected variables on defaulting from completion of immunization among children aged 9–23 months in the Laelay Adiabo District, Tigray Region, Ethiopia, 2015 (N = 270).

Clinical characteristics of neonatal near misses among neonates admitted to public hospitals of Hadiya zone, Southern Ethiopia, 2020.