{"doc_desc":{"title":"FoodChoicesProject","idno":"APHRC_FCP_2017_v01","producers":[{"name":"African Population and Health Research Center","abbreviation":"APHRC","affiliation":"","role":"Documentation of the DDI"}],"prod_date":"2020-08-12","version_statement":{"version":"Version 1.0 (August 2020)"}},"study_desc":{"title_statement":{"idno":"APHRC_FCP_2017_v01","title":"Dietary transitions in African cities: Leveraging evidence for interventions and policy to prevent diet-related non-communicable diseases (NCDs)","alt_title":"TACLED"},"authoring_entity":[{"name":"Elizabeth Kimani-Murage (PhD)","affiliation":"APHRC - Kenya"},{"name":"Michelle Holdsworth (PhD)","affiliation":"University of Sheffield - UK"}],"production_statement":{"producers":[{"name":"Joseph Mogendi (PhD)","affiliation":"APHRC \u2013 Kenya","role":"Lead research activities including fieldwork, benchmarking food environments, contribution to FBDGs development, photography exhibition, and stakeholder engagement."},{"name":"Gershim Asiki (PhD)","affiliation":"APHRC \u2013 Kenya","role":"Contribute to data analyses, benchmarking food environments, FBDGs development, photography exhibition, and stakeholder engagement. "},{"name":"Dickson Amugsi (PhD)","affiliation":"APHRC \u2013 Kenya","role":"Contribute to data analyses, benchmarking food environments, FBDGs development, photography exhibition, and stakeholder engagement. "},{"name":"Milka Njeri (BSc)","affiliation":"APHRC \u2013 Kenya","role":"Oversee the recruitment of research participants and facilitate training for data collectors. Coordinate implementation of the work plan and logistical assistance to field team. "},{"name":"Teresia Macharia (BSc)","affiliation":"APHRC \u2013 Kenya","role":"Assist with overseeing the recruitment of research participants and facilitating training for data collectors. Assist with coordinating implementation of the work plan and logistical assistance to field team."}],"funding_agencies":[{"name":"Medical Research Fund (MRC) - Global Challenges Research Fund (GCRF)","abbreviation":"","role":""}]},"series_statement":{"series_name":"Other Household Survey [hh\/oth]"},"version_statement":{"version_date":"2017-10-07","version_notes":"Cross-sectional descriptive study, employing a mixed methods approach to data collection and analyses, including a survey and anthropometric measurements, 24 hour dietary recall to collect information on participants' food consumption."},"study_info":{"abstract":"Background: Africa is experiencing rapid urbanisation partly driven by increasing migration of individuals to cities. Dietary habits are also changing with increasing consumption of unhealthy foods. Such changes have resulted in increasing levels of obesity in cities, with rates higher among women. Policy responses have been limited in success so far, and are mostly influenced by experiences in higher income countries. There is also a lower understanding of the factors that drive food consumption in Kenya, particularly the role that people's social networks and the neighbourhoods that individuals live in play in driving these relationships. \nObjective: This project aims to explore the factors associated with people's food consumption and their food environments (where, when and with whom they eat) in Nairobi, Kenya. \nMethods: This is a cross-sectional descriptive study, employing a mixed methods approach to data collection and analyses, including a survey and anthropometric measurements, 24 hour dietary recall to collect information on participants' food consumption, photovoice and qualitative interviews to explore the social, economic, and physical factors influencing participants' food consumption, and spatial (GIS) data collection on the features of the participants' neighbourhoods that may influence food choices. The findings will be shared with experts and policy makers for discussions on designing effective strategies to improve dietary patterns and practices to tackle obesity and related non communicable diseases. \nData Analysis: Anonymised quantitative data will be analysed using STATA, and will involve descriptive and correlational analyses. Qualitative data will be transcribed verbatim, and the word files coded in NVivo. Thematic analysis will then be used to identify emergent themes from the interview data . The GIS data will be analysed using open source software R- and QGIS- data.maps. \nStudy Duration and Budget: The study duration is two years, with a budget of  $255,432, awarded by Medical Research Fund - Global Challenges Research Fund.","coll_dates":[{"start":"2017-09-19","end":"2017-10-07","cycle":""}],"nation":[{"name":"KENYA","abbreviation":"KEN"}],"geog_coverage":"Makadara Constituency, located in the Eastlands suburbs of Nairobi city","analysis_unit":"Individuals","universe":"The study covered all individuals (residents) who were adolescents (13 to 18 years), adults (19 to 49 years) and older adults (50 years or older)","notes":"The scope of the project include:\n- QUANTITATIVE SURVEY AND ANTHROPOMETRIC MEASUREMENTS: Including questions on basic demographic information such as age, education, occupation, income, and health behaviours. Their height and weight will also be measured to allow derivation of their Body Mass Index (BMI). \n- 24 HOUR DIETARY RECALL: Records  all food\/drink consumed inside\/outside the home by the participant in the previous 24hr period excluding weekends, also recording how long a food event lasts ('tempo'), time of day of the food event ('periodicity') and who participants eat with and where ('synchronization') in order to ascertain the place of unhealthy foods in their everyday lives.","study_scope":"The scope of the project include:\n- QUANTITATIVE SURVEY AND ANTHROPOMETRIC MEASUREMENTS: Including questions on basic demographic information such as age, education, occupation, income, and health behaviours. Their height and weight will also be measured to allow derivation of their Body Mass Index (BMI). \n- 24 HOUR DIETARY RECALL: Records  all food\/drink consumed inside\/outside the home by the participant in the previous 24hr period excluding weekends, also recording how long a food event lasts ('tempo'), time of day of the food event ('periodicity') and who participants eat with and where ('synchronization') in order to ascertain the place of unhealthy foods in their everyday lives."},"method":{"data_collection":{"sampling_procedure":"158 individuals were successfully  interviewed from  Makadara Constituency, located in the Eastlands suburbs of Nairobi city. Of these, 48 adolescents (13-18 years), 56 Adults (19-49 years) and 54 Older adults (50+ years) were identified and participated in the study. For those 13 to 17 years, parental consent, and participant assent was obtained prior to participation. Physically or intellectually impaired individuals were excluded, since this may hinder clear communication and accurate anthropometric measurements.","sampling_deviation":"N\/A","coll_mode":"Face-to-face [f2f]","research_instrument":"The questionnaire for the Food choices project were structured questionnaire based on 24-hour recall questions on different food groups. The sociodemographic questionnaire was administerd once for all particpants, which collected various information on sex, age, estate\/village of residence, health status, missed meals frequency, pregancy status, breastfeeding status, length of stay in current neighbourhood, highest level of education, occupation, household possessions, anthropometry, use of tobacco and alcohol, fruits consumption, daily actvities, time spent on food event. In addition to24-hour dietary recall questionnaire, which was conducted on each participant and included information on different food groups that wer consumed in the last 24-hours.","act_min":"The interviews were conducted by10 interviewers distributed in all study areas. The field supervisor role was to coordinate field activities namely spot check, sharing progrress report to the central office and management of interviewers.","weight":"No sampling weights calculated","cleaning_operations":"Data editing took place at a number of stages throughtout the processing, including:\na) data coding\nb) data qulaity checks\nc) data cleaning using STATA"},"analysis_info":{"response_rate":"All the 158 partcipants partcipated in the study with a response rate of 100 percent","sampling_error_estimates":"No sampling errors were estimated."}},"data_access":{"dataset_use":{"contact":[{"name":"Elizabeth Kimani-Murage","affiliation":"APHRC","email":"ekimani@aphrc.org","uri":""}],"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n- the Identification of the Primary Investigator\n- the title of the survey (including country, acronym and year of implementation)\n- the survey reference number\n- the source and date of download","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."}}}}