{"type":"survey","study_desc":{"title_statement":{"idno":"ZWE_2005_STEPS_v01_M","title":"STEPwise Survey for Non Communicable Diseases Risk Factors 2005","alt_title":"NCD STEPS 2005"},"authoring_entity":[{"name":"Ministry of Health and Child Welfare","affiliation":"Government of Zimbabwe"},{"name":"World Health Organization","affiliation":""}],"oth_id":[{"name":"University of Zimbabwe","affiliation":"","email":"","role":"Consultants"},{"name":"Ministry of Health and Child Welfare","affiliation":"","email":"","role":"Technical Support, Survey Supervision & Fieldwork"}],"production_statement":{"funding_agencies":[{"name":"Ministry of Health and Child Welfare","abbreviation":"MOHCW","role":"Funding"},{"name":"World Health Organization","abbreviation":"WHO","role":"Funding"},{"name":"United Nations Children\u2019s Fund","abbreviation":"UNICEF","role":"Funding"}]},"distribution_statement":{"contact":[{"name":"Regional Adviser, Health Risk Factors","affiliation":"World Health Organization","email":"alisalada@who.int","uri":"http:\/\/www.who.int\/chp\/steps\/contact\/en\/"},{"name":"Team Leader, Surveillance","affiliation":"World Health Organization","email":"rileyl@who.int","uri":"http:\/\/www.who.int\/chp\/steps\/contact\/en\/"}]},"series_statement":{"series_name":"Other Household Health Survey [hh\/hea]","series_info":"This is the first NCD STEPS survey conducted in Zimbabwe."},"study_info":{"abstract":"Noncommunicable diseases are the top cause of deaths. In 2008, more than 36 million people worldwide died of such diseases. Ninety per cent of those lived in low-income and middle-income countries.WHO Maps Noncommunicable Disease Trends in All Countries<\/a>\nThe STEPS Noncommunicable Disease Risk Factor Survey, part of the STEPwise approach to surveillance (STEPS) Adult Risk Factor Surveillance project by the World Health Organization (WHO), is a survey methodology to help countries begin to develop their own surveillance system to monitor and fight against noncommunicable diseases. The methodology prescribes three steps\u2014questionnaire, physical measurements, and biochemical measurements. The steps consist of core items, core variables, and optional modules. Core topics covered by most surveys are demographics, health status, and health behaviors. These provide data on socioeconomic risk factors and metabolic, nutritional, and lifestyle risk factors. Details may differ from country to country and from year to year.\n\nThe general objective of the Zimbabwe NCD STEPS survey was to assess the risk factors of selected NCDs in the adult population of Zimbabwe using the WHO STEPwise approach to non-communicable diseases surveillance.\nThe specific objectives were:\n- To assess the distribution of life-style factors (physical activity, tobacco and alcohol use), and anthropometric measurements (body mass index and central obesity) which may impact on diabetes and cardiovascular risk factors.\n- To identify dietary practices that are risk factors for selected NCDs.\n- To determine the prevalence and determinants of hypertension\n- To determine the prevalence and determinants of diabetes.\n- To determine the prevalence and determinants of serum lipid profile.","coll_dates":[{"start":"2005-05","end":"2005-06","cycle":"Field Survey"},{"start":"2005-07","end":"2005-08","cycle":"Running Biochemical Samples"}],"nation":[{"name":"Zimbabwe","abbreviation":"ZWE"}],"geog_coverage":"Mashonaland Central, Midlands and Matebeleland South Provinces.","analysis_unit":"Household\nIndividual","universe":"The survey comprised of individuals aged 25 years and over.","data_kind":"Sample survey data [ssd]","notes":"The scope of the Zimmbabwe NCD STEPS survey includes:\n- Demographic information\n- Tobacco use\n- Alcohol consumption\n- Diet\n- Physical activity \n- History of High Blood Pressure\n- History of Diabetes\n- Step2: Physical measurements - height, weight, waist circumference, hip circumference, blood pressure readings\n- Step 3: Biochemical measurements - blood glucose, blood lipids - fasting\/random","study_scope":"The scope of the Zimmbabwe NCD STEPS survey includes:\n- Demographic information\n- Tobacco use\n- Alcohol consumption\n- Diet\n- Physical activity \n- History of High Blood Pressure\n- History of Diabetes\n- Step2: Physical measurements - height, weight, waist circumference, hip circumference, blood pressure readings\n- Step 3: Biochemical measurements - blood glucose, blood lipids - fasting\/random"},"method":{"data_collection":{"sampling_procedure":"A multistage sampling strategy with 3 stages consisting of province, district and health centre was employed. The World Health Organization STEPwise Approach (STEPS) was used as the design basis for the survey. The 3 randomly selected provinces for the survey were Mashonaland Central, Midlands and Matebeleland South. In each Province four districts were chosen and four health centres were surveyed per district. The survey comprised of individuals aged 25 years and over.The survey was carried out on 3,081 respondents consisting of 1,189 from Midlands,944 from Mashonaland Central and 948 from Matebeleland South.\nA detailed description of the sampling process is provided in sections 3.8 -3.9. if the survey report provided under the related materials tab.","sampling_deviation":"Designing a community-based survey such as this one is fraught with difficulties in ensuring representativeness of the sample chosen. In this survey there was a preponderance of female respondents because of the pattern of employment of males and females which also influences urban rural migration.\n\nThe response rate in Midlands was lower than the other two provinces in both STEP 2 and 3. This notable difference was due to the fact that Midlands had more respondents sampled from the urban communities. A higher proportion of urban respondents was formally employed and therefore did not complete STEP 2 and 3 due to conflict with work schedules.","coll_mode":"Face-to-face [f2f]","research_instrument":"In this survey all the core and selected expanded and optional variables were collected. In addition a food frequency questionnaire and a UNICEF developed questionnaire, the Fortification Rapid Assessment Tool (FRAT) were administered to elicit relevant dietary information.","coll_situation":"Conduct of the survey\nNational Team: The national team consisted of representatives from the Ministry of Health and Child Welfare (1) and the University of Zimbabwe (3). The members of the team jointly developed the proposal, conducted adaptation of the survey instruments, approached stakeholders and carried out training of the survey team. The MOH&CW representative provided co-ordination of all survey activities. The University of Zimbabwe representatives provided survey design, clinical, statistical, data management and laboratory expertise.\n\nField Team: Three teams selected from each of the three survey provinces carried out the survey. Each team comprised of 12 members with the following composition; 1 supervisor, 1 team leader, 7 interviewers (5 senior nurses, 2 nutritionists), 1 laboratory scientist and 2 drivers.\n\nAdaptation of survey tools and training manuals: An adaptation workshop was held in June 2004. The objectives of this workshop were; (a) adopt the WHO STEPwise approach and training manuals (b) map out fieldwork activities (c) identify field team members (d) define the age population profile of the selected study sites (e) translate the tools into Shona and Ndebele (the two main vernacular languages in the survey area).\n\nTraining of Interviewers: A 5-day training workshop was held in May 2005. The objectives of the training workshop were; (a) how to gain entry into the study areas and households (b) how to conduct interviews (c) how to observe research ethics (d) how to administer questionnaires and complete laboratory forms (e) how to collect, store and transport blood samples (f) how to accurately keep records of laboratory forms and questionnaires (g) how to ensure quality control of all field processes including questionnaires, laboratory forms and specimens.\nInterviewers participated in mock interviews and practiced taking both physicalmeasurements and collection of blood samples. Team supervisors were further trained on; (a) checking and correcting interview data (b) editing completed questionnaires (c) complete registration of samples before transportation (d) problem solving in the field (e) field sampling procedures and calculation of sampling intervals.\n\nPilot test of field procedures: A one day field pilot survey was conducted in both a rural and urban setting with the following objectives; (a) to assess the applicability of the questionnaires to the local communities (b) to assess reactions of the respondents to the research procedures (c) to assess whether the instructions in the field manual were relevant and straightforward (d) to estimate time needed to administer each questionnaire (e) to assess the sequencing\/flow of questions (f) to check the content validity of the questions after translation. \n\nThis exercise identified issues which enabled revision of critical steps in the survey procedure including changes of items in the questionnaire.\n\nField Activities - a detailed description of the field activities is provided in the survey report provided under the related materials tab.","cleaning_operations":"Data entry for Step 1 and Step 2 data was carried out as soon as data became available to the data management team. Step 3 data became available in October and data entry was carried out when data quality checks were completed in November. Report writing started in September and a preliminary report became available in December 2005. \n\nTraining of data entry clerks\nFive data entry clerks were recruited and trained for one week. The selection of data entry clerks was based on their performance during previous research carried out by the MOH&CW. The training of the data entry clerks involved the following:\n- Familiarization with the NCD, FRAT and FFQ questionnaires.\n- Familiarization with the data entry template.\n- Development of codes for open-ended questions.\n- Statistical package (EPI Info 6).\n- Development of a data entry template using EPI6.\n- Development of check files for each template\n- Trial runs (mock runs) to check whether template was complete and user friendly for data entry.\n- Double entry (what it involves and how to do it and why it should be done).\n- Pre-primary data cleaning (check whether denominators are tallying) of the data entry template was done.\n\nData Entry for NCD, FRAT and FFQ questionnaires\nThe questionnaires were sequentially numbered and were then divided among the five data entry clerks. Each one of the data entry clerks had a unique identifier for quality control purposes. Hence, the data was entered into five separate files using the statistical package EPI Info version 6.0. The data entry clerks inter-changed their files for double entry and validation of the data. Preliminary data cleaning was done for each of the five files. The five files were then merged to give a single file. The merged file was then transferred to STATA Version 7.0 using Stat Transfer version 5.0.\n\nData Cleaning\nA data-cleaning workshop was held with the core research team members. The objectives of the workshop were:\n1. To check all data entry errors.\n2. To assess any inconsistencies in data filling.\n3. To assess any inconsistencies in data entry.\n4. To assess completeness of the data entered.\n\nData Merging\nThere were two datasets (NCD questionnaire dataset and laboratory dataset) after the data entry process. The two files were merged by joining corresponding observations from the NCD questionnaire dataset with those from the laboratory dataset into single observations using a unique identifier. The ID number was chosen as the unique identifier since it appeared in both data sets. The main aim of merging was to combine the two datasets containing information on behaviour of individuals and the NCD laboratory parameters. When the two data sets were merged, a new merge variable was created. The merge variable took values 1, 2 and 3.\nMerge variable==1 Observation appeared in the NCD questionnaire data set but a corresponding observation was not in the laboratory data set\nMerge variable==2 Observation appeared in the laboratory data set but a corresponding observation did not appear in the questionnaire data set\nMerge variable==3 Observation appeared in both data sets and reflects a complete merge of the two data sets.\n\nData Cleaning After Merging\nData cleaning involved identifying the observations where the merge variable values were either 1 or 2. Merge status for each observation was also changed after effecting any corrections. The other two unique variables that were used in the cleaning were Province, district and health centre since they also appeared in both data sets.\n\nObjectives of cleaning:\n1. Match common variables in both data sets and identify inconsistencies in other matching variables e.g. province, district and health centre.\n2. To check for any data entry errors.","method_notes":"Data Analysis\nThis preliminary stage of the survey report employed simple descriptive statistics with means, proportions and frequency distributions. 95% CI were used as a measure of precision on the estimated population parameters. In the next report further analysis will be performed as follows. T-tests will be used to compare continuous data such as systolic Blood Pressure, LDL-C HDL-C, and triglycerides between groups. Chisquare tests will be used to assess relationships between variables and analysis of variance (ANOVA) for continuous variables for comparisons across more than two groups. In situations where the normality assumptions are not met, the non-parametric equivalents of the above tests will be used (Fisher\u2019s exact test, Kruskal Wallis test, etc). Logistic regression analysis will be employed to assess predictors of diabetes and hypertension in each particular group controlling for potential confounders."},"analysis_info":{"response_rate":"A total of 3,081 respondents were included in the survey against an estimated sample size of 3,000. The response rate for Step 1 was 80% for and for Step 2 70% taking Step 1 accrual as being 100%."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"Before being granted access to the dataset, all users have to formally agree: \n1. To make no copies of any files or portions of files to which s\/he is granted access except those authorized by the data depositor. \n2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files. \n3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her\/his analysis will be immediately brought to the attention of the data depositor.","required":"yes","form_no":"","uri":""}],"disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}},"data_files":[],"variables":[],"variable_groups":[]}