{"doc_desc":{"title":"IDRC-RECAP","idno":"DDI-KEN-APHRC-IDRCRECAP-2020-v1.0","producers":[{"name":"African Population and Health Research Center","abbreviation":"APHRC","affiliation":"","role":"Documentation of the DDI"}],"prod_date":"2024-09-19","version_statement":{"version":"Version 1.0 (September 2024)"}},"study_desc":{"title_statement":{"idno":"DDI-KEN-APHRC-IDRCRECAP-2020-v1.0","title":"Developing a package of effective regulatory interventions for healthier food environments in Kenya","sub_title":"RECAP","alt_title":"RECAP"},"authoring_entity":[{"name":"Gershim Asiki (PhD)","affiliation":"APHRC"}],"production_statement":{"producers":[{"name":"Shukri Mohamed (PharmD)","affiliation":"African Population and Health Research Center","role":"Co-investigator"},{"name":"Milkah Njeri","affiliation":"African Population and Health Research Center","role":"Co-investigator"},{"name":"Florence Sipalla","affiliation":"African Population and Health Research Center","role":"Co-investigator"},{"name":"Caroline Karugu","affiliation":"African Population and Health Research Center","role":"Co-investigator"},{"name":"Michelle Holdsworth","affiliation":"French National Research Institute for Sustainable Development","role":"Co-investigator"},{"name":"Dr. Victor Kibe","affiliation":"Nairobi Metropolitan Services (NMS)","role":"Co-investigator"},{"name":"Martha Chege","affiliation":"Nairobi Metropolitan Services (NMS)","role":"Co-investigator"},{"name":"Stefanie Vandevijvere","affiliation":"Sciensano Research Institute Rue Juliette Wytsmanstraat","role":"Collaborator and technical experts"},{"name":"Amos Laar","affiliation":"University of Ghana","role":"Collaborator and technical experts"},{"name":"Safura Abdool Karim","affiliation":"PRICELESS South Africa","role":"Collaborator and technical experts"},{"name":"Karen Hofman","affiliation":"PRICELESS South Africa","role":"Collaborator and technical experts"},{"name":"Agnes Erze","affiliation":"PRICELESS South Africa","role":"Collaborator and technical experts"},{"name":"Sofia Jomo","affiliation":"African Population and Health Research Center","role":"Data Documentation Specialist "},{"name":"Bonface Ingumba","affiliation":"African Population and Health Research Center","role":"Data Governance Officer"}],"copyright":"Copyright \u00a9 APHRC, 2024","funding_agencies":[{"name":"International Development Research Center","abbreviation":"IDRC","role":"Funder"}]},"series_statement":{"series_name":"Demographic and Health Survey [hh\/dhs]","series_info":"N\/A"},"version_statement":{"version_date":"2024-09-19","version_notes":"N\/A"},"study_info":{"keywords":[{"keyword":"Food environment","vocab":"","uri":""},{"keyword":"Package of interventions","vocab":"","uri":""}],"abstract":"The rate of overweight and obesity has increased among children and adolescents in low- and middle-income countries (LMICs) over the past decade. This increase is largely driven by unhealthy diets resulting from unhealthy food environments. Available evidence shows that fiscal policies and regulatory measures to restrict unhealthy food environments yield substantial and cost-effective health gains in LMICs. However, there are significant challenges associated with the adoption and implementation of such policies. We aim to identify concrete context-relevant priority actions that promote a healthy food environment as a strategy to enhance healthy dietary patterns\/practices and to facilitate knowledge translation pathways to prevent nutrition-related non-communicable diseases (NR-NCDs) in Kenya. This three-year project has four objectives that will be delivered through four interlinked work packages (WPs): i. to assess gaps, barriers and facilitators to developing and implementing public food policies and government actions (WP1); ii. To assess the frequency and nature of unhealthy food and beverage marketing to children, the power of promotions on television, in stores, and in and around schools (WP2); iii. To estimate the cost of inaction for selected NR-NCD policies (WP3); and iv. To assess the legal and administrative feasibility of adopting and implementing context-specific NR-NCD interventions (WP4). The findings of this project will provide concrete context-relevant priority actions that promote healthy food consumption patterns and practices and facilitate knowledge translation pathways to prevent NR-NCDs in Kenya.","coll_dates":[{"start":"2021-07-21","end":"2021-09-18","cycle":"Final_Outlet_School_Neighborhoods"},{"start":"2021-10-05","end":"2021-11-05","cycle":"Supermarket instore mapping"},{"start":"2022-06-24","end":"2022-10-31","cycle":"Updated tv data"},{"start":"2022-06-14","end":"2022-10-17","cycle":"Radio data"}],"nation":[{"name":"Kenya","abbreviation":"KEN"}],"geog_coverage":"National coverage (Nairobi, Mombasa, and Baringo).","analysis_unit":"Individuals (Policy and decision makers, media, children\/adolescents, parents, store managers, food service vendors, sports event managers, civil society representatives, Shoppers in food stores)","universe":"Policy and decision makers, media, children\/adolescents, parents, store managers, food service vendors, sports event managers, civil society representatives, Shoppers in food stores","notes":"The scope includes Outdoor advertising (around the school) questionnaire \u2013 questionnaire about outdoor\nadvertisement around schools. The questionnaire contains identification, school, advertisement,\nfood, and promotional information\nAdvertisement in school events \u2013 questionnaire about advertisement in school events. The\nquestionnaire contains identification, school, advertisement, food, and promotional information.\nTelevision advertisement \u2013 questionnaire about television\/radio advertisement. The questionnaire\ncontains contextual, channel and program, food advertised, and power of advertising information.\nOutlet mapping \u2013 questionnaire about information of food outlets near schools. The questionnaire\ncontains identification and outlet information (including types of foods sold\/advertised in the outlet)\ninformation\nInstore observation \u2013 questionnaire about instore observation of supermarkets and stores near\nschools. The questionnaire contains identification and store information (including types of foods\nsold\/advertised in the store)","study_scope":"The scope includes Outdoor advertising (around the school) questionnaire \u2013 questionnaire about outdoor\nadvertisement around schools. The questionnaire contains identification, school, advertisement,\nfood, and promotional information\nAdvertisement in school events \u2013 questionnaire about advertisement in school events. The\nquestionnaire contains identification, school, advertisement, food, and promotional information.\nTelevision advertisement \u2013 questionnaire about television\/radio advertisement. The questionnaire\ncontains contextual, channel and program, food advertised, and power of advertising information.\nOutlet mapping \u2013 questionnaire about information of food outlets near schools. The questionnaire\ncontains identification and outlet information (including types of foods sold\/advertised in the outlet)\ninformation\nInstore observation \u2013 questionnaire about instore observation of supermarkets and stores near\nschools. The questionnaire contains identification and store information (including types of foods\nsold\/advertised in the store)"},"method":{"data_collection":{"sampling_procedure":"Work Package 1\na) Sampling design \t\nPurposive and snowball sampling techniques was used to identify eligible participants for the key informant interviews. Relevant government departments and agencies that have responsibilities related to development and implementation of policies on nutrition, the food environment and NR-NCDs were purposively identified. This iincluded the government departments, civil societies and representatives of relevant organizations in the wider food system in Kenya. Purposive and snowball sampling was then used to select the key people (policy & decision makers) in each of the departments who best understand the issues of interest to this study) to be interviewed.\nThe initial sample commenced with 1) Government agencies with responsibilities related to policies on nutrition\/food environment, and NR-NCDs: Finance, Industry\/Commerce, Trade, Health, Agriculture; 2) Food industries and manufacturers; 3) Civil Society actors relevant to health and\/or food; 4) Journalists; 5) the media. \nRecruitment of interviewees was through formal approaches to the heads of relevant agencies. Once approval was obtained, we contacted relevant departments for identification of the individuals who best understand the issues of interest to this study either by their positions (senior\/intermediate) or period worked in the department; and subsequently request for interviews. At the end of each interview, we asked interviewees to identify further relevant interviewees. \nb) Sample size \nApproximately 10 key informant interviews were conducted with key policy and decision makers relating to NR- NCDs as well as the food environment in Kenya. We anticipated that this number of experts from the various government departments and the wider food systems' stakeholders, would adequately present the issues relevant to policies and actions on nutrition, creating a healthy food environment and NR-NCDs in Kenya. However, there was flexibility to accommodate emerging issues that may need additional follow-up interviews, hence the final sample size was based on saturation of the ideas from the interviews. \n\nWork Package 2\nTELEVISION AND RADIO MONITORING\na) Sampling design \nTV and Radio to be monitored were sampled in three  stages including i) selection of the TV and radio channels to monitor, ii) the calendar period (duration) of the monitoring (months, days, hours) and iii)  days of the week to record.\nFirst, purposive sampling was used to select TV channels to be recorded. In the past years, Kenya has completely transitioned from analogue to digital television type with both free to air and paid for TV channels. According to the communication authority of Kenya (CAK)'s report (2019 -2020), the free to Air TV is the most popular form of television, enjoying a 95% popularity in Kenya [52]. As such only the free to air TV channels that broadcast advertisements were included. Paid for TV channels and those that do not broadcast advertisements were excluded.\nAfter the identification of the free to air TV channels and Radio that broadcast advertisements, the most popular television and radio channels were then selected for monitoring, based on their levels of popularity with children aged <12, <16 or <18 years during peak viewing times. Popularity was assessed based on the updated local ratings data obtained from TV and radio audience measurement institutions such as GeoPoll [53], the CAK. For instance, KARF report of 2020 rated Citizen and KTN televisions as the most preferred channels, with children 15 to 17 years as the age group that watched most TV [52]. However, this may change with time, and therefore the prevailing TV and Radio ratings at the time of data collection were used. Where local ratings data were not available, we consulted with experts in the media industry in Kenya.\n\nSecond, based on the recommendation for recording over at least a 3 month period [48], random sampling was used to select three consecutive months for recording. In a typical school (primary and secondary) calendar in Kenya, school term runs from January to March, May to July and September to mid-November, with April, August and December as vacation Months. The selection of the recording month ensured inclusion of both school term months and a vacation month in order to capture any variations in food advertisement or promotion during school days and vacations\nThe data collection period excluded national holidays and special events, to ensure that data represents typical broadcasting.\n\nThirdly, stratified sampling design was applied to select the days for recording, with weekdays and weekend days comprising the two strata. The INFORMAS protocol recommends at least four week days and four weekends as optimal for recording [48]. Thus, the random sampling was used to select four week days and four weekend days in each of the three months selected for recording. Each channel was recorded for 18 hours a day, from 0600hrs to 2400hrs (midnight), which entail the peak viewing times for children. \n\nb)  Sample size\nGiven that the focus of the monitoring was children\/adolescents, TV and radio channels were chosen based on their levels of popularity with children aged <12, <16 or <18 years during peak viewing times. At minimum, the top three most popular television and radio channels respectively were included for monitoring. Monitoring was conducted on at least four week days and four weekends over a three month period, hence a total of twelve week days and twelve weekend days. These number of channels, days of monitoring and duration of monitoring have been documented as optimal to assess the nature and frequency of advertisement and promotion of foods to children [48].\n\nOUTDOOR ADVERTISING\na) Sampling design \nA multistage sampling approach was employed. At the first stage, purposive sampling was applied in the selection of the three counties, Nairobi, representing an urban and major capital city, Nairobi representing a metropolitan city, Mombasa, a coastal tourist city and Baringo, a rural setting and all the three counties are in different geo-political areas. Inclusion of these three counties ensures that we capture any variations in outdoor advertising and marketing of unhealthy food to children in different geographical and social contexts. \nIn the second stage, Nairobi and Mombasa Counties were stratified further into urban formal and informal settlements according to deprivation levels and socio-economic differences defined by the county government and one area (sub-county) was selected from each of these strata, while in Baringo County, one rural sub county was randomly selected from a list of all rural sub-counties in Baringo.\nIn the third stage, a random sample of schools was drawn from each area selected in stage 2. The schools were further stratified by type of school (public and private, primary and secondary). The number of schools selected in each location was proportionate to the size of the area (in terms of the total number of schools in the area).\nThis selection of different sub counties\/ strata within the three counties captured the range of schools by deprivation levels and socio-economic differences to show the variations in advertisements in each of these contexts. \n\nIn order to undertake this process of sampling, we approached the counties, sub-counties and the ministry of education to provide the list of schools with the level of detailed information needed for sampling.  \nb) Sample size\nWe estimated approximately 149 schools per county to be sampled based on prevalence of 23% unhealthy advertising in Nairobi low income settings [29], a 10% higher or lower unhealthy food advertising around schools depending on location, a power of 80% and a margin of error of 0.05. Considering the three counties, yields a total sample of 447 (? 450) schools.\n\nMARKETING IN-STORES\na) Sampling strategy\nPurposive sampling was used to select the major supermarkets or grocery stores selling foods and non-alcoholic drinks in the selected sub-counties. The major supermarkets or food outlets were identified through local or international market research reports such as Euromonitor International. Where such information is unavailable, a rapid assessment was conducted to identify the major food outlets in the study area after which purposive sampling was applied to select the most popular outlets for inclusion in the survey.  \n\nb) Sample size\nTo implement this, the main supermarkets were identified through a local market research reports or rapid assessment of the main supermarkets in the selected sub counties\/ neighborhoods. All the main supermarkets identified were included in the survey.\n\nQUALITATIVE INTERVIEWS\na) Sampling design \nFor the key informant interviews with policy and decision makers, purposive and snowball sampling were then used to select the key people (policy & decision makers) in each of the departments who best understand the issues of interest to this study, to be interviewed.\nPurposive sampling was used to select parents and children to participate in the in-depth interviews and focus group discussions respectively. Participant characteristics on gender, location (urban\/rural) SEC status (informal and formal settings), and type of school (public\/private) were considered during sampling and participant selection to ensure representation and collection of information from a wide variety of participants and perspectives.\n\nb) Samples size\nAn estimated 15 key informant interviews were conducted with various stakeholders representing policy makers, school authorities, media houses, store managers, other food service vendors, and sports event managers.\nFor children in schools, three focus group discussions with six to eight participants each were conducted in each sub county\/neighborhood, one male-only, one female-only and a mixed group; and hence an estimated 90 participants \/ children).\nSimilarly, In-depth interviews with parents representing at least 2 to 3 parents with children schools in the sub-counties\/ neighborhoods selected, and hence an estimated 15 parents. Gender representation were considered while selecting the parents to participate in the interviews in each school.","sampling_deviation":"N\/A","coll_mode":"Face-to-face [f2f]","research_instrument":"There were 4 questionnaires used to collected data which included\n-School outlet neighborhoods questionnaire which collected data on the food oulets around schools and the contents of food products sold in those outlets\n-Supermarket instore mapping questionnaire which collected data on the mapping of mini and main supermarkets and the food products sold in the supermarkets, their shelf space as well as their positioning in the supermarket.\n-TV questionnaire which collected data on the frequency of of food advertisement on the TV\n- Radio questionnaire which collected data on the frequency of food advertisement on the Radio\n\nOutdoor advertising (around the school) questionnaire \u2013 questionnaire about outdoor\nadvertisement around schools. The questionnaire contains identification, school, advertisement,\nfood, and promotional information\nAdvertisement in school events \u2013 questionnaire about advertisement in school events. The\nquestionnaire contains identification, school, advertisement, food, and promotional information.\nTelevision advertisement \u2013 questionnaire about television\/radio advertisement. The questionnaire\ncontains contextual, channel and program, food advertised, and power of advertising information.\nOutlet mapping \u2013 questionnaire about information of food outlets near schools. The questionnaire\ncontains identification and outlet information (including types of foods sold\/advertised in the outlet)\ninformation\nInstore observation \u2013 questionnaire about instore observation of supermarkets and stores near\nschools. The questionnaire contains identification and store information (including types of foods\nsold\/advertised in the store)","act_min":"To ensure that high quality quantitative data are collected, validation rules, constraints or checks (skips) in the questionnaire were embedded within the data collection electronic software during programming of the tool. This allowed the interviewers to quickly notice missing data and implausible or out of range values. The data collection program was also tested severally prior to data collection. Regular spot checks by the project team with field interviewers, and an automated routine check on data completeness and discrepancies was also implemented to enhance data quality. Interviewers were responsible for following-up on any inconsistencies or errors in the data with their participants as\/when needed. \nTo ensure that high quality qualitative interviews were conducted, the research team sat on a select number of interviews and regularly reviewed the data collected for quality. Regular debriefing sessions with the interviewers also ensured that emerging ideas are followed-up on in subsequent interviews. In addition, transcripts underwent data verification by checking them to confirm accuracy against the original audio-recordings. \nAn INFORMAS expert provided training on food promotion data collection processes to ensure that the data collected during the study meets high standards.","weight":"N\/A","cleaning_operations":"For TV and Radio: Data was collected by recording live television and radio programs on the sampled days, directly onto external hard drives, from 6.00am in the morning to 12.00midnight.\n\nFood advertisements around the schools: Outdoor advertisements and food outlets surrounding primary and secondary schools (both private and public) were observed and recorded manually, using geo-positioning systems to estimate the rate of healthy and unhealthy food advertising within the school and around the school premises, at a distance 250 meters  along all the roads connecting to the school entrances and exits.\n\nFood outlets around the school: The research team visited the selected food stores and record the promotional and marketing techniques in the stores using Survey CTO and ODK Survey on the tablets. All advertising\/food promotion were recorded, including the presence of promotional characters, premium offers and\/or nutrition and health claims. Indicators such as frequency of overall food products with promotions on packaging; frequency of unhealthy food ads vs. healthy food products with promotions on packaging; Frequency of products within different food groups with promotions on packaging; and types of promotions present on packaging of various foods in Kenya were observed and recorded using a pre-designed checklis on the tablets"},"analysis_info":{"response_rate":"100%","sampling_error_estimates":"N\/A"}},"data_access":{"dataset_use":{"contact":[{"name":"African Population and Health Research Center","affiliation":"","email":"datarequests@aphrc.org\/info@aphrc.org","uri":"aphrc.org"}],"cit_req":"Citation requirement\nUse 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","conditions":"All non-APHRC staff seeking to use data generated at the Center must obtain written approval to use the data from the Director of Research. This form is developed to assess applications for data use and facilitate responsible sharing of data with external partners\/collaborators\/researchers. By entering into this agreement, the undersigned agrees to use these data only for the purpose for which they were obtained and to abide by the conditions outlined below:\n\n1. Data Ownership: The data remain the property of APHRC; any unauthorized reproduction and sharing of the data is strictly prohibited. The user will, therefore, not release nor permit others to use or release the data to any other person without the written authorization from the Center.\n\n2. Purpose: The provided data must be used for the purpose specified in the Data Request Form; any other use not specified in the form must receive additional or separate authorization.\n\n3. Respondent Identifiers: The Center is committed to protecting the identity of the respondents who provide information in its research. All analytical data sets (both qualitative and quantitative) released by the Data Unit MUST are stripped of respondent identifiers to protect the identity of the respondents. By accepting to use APHRC data, the user is pledging that he\/she will not, under any circumstance, regenerate the identifiers or permit others to use the data to learn the identity of any individual, household or community included in any data set.\n\n4. Confidentiality pledge: The user will not use nor permit others to use the data to report any information in the data sets that could identify, directly or by inference, individuals or households.\n\n5. Reporting of errors or inconsistencies: The user will promptly notify the Head of the Statistics and Survey Unit any errors discovered in the data as soon as the errors are discovered.\n\n6. Publications resulting from APHRC data: The Center requires external collaborators to work with APHRC staff on all publications resulting from its data. In order to facilitate this, lead authors should send a detailed concept note of the paper (including the background, rationale, data, analytical methods, and preliminary findings) to the Principle Investigator (or Theme Leader) for the project (with a copy to the Director of Research), who will circulate the abstract to concerned researchers for possible expression of interest in participating in the publication as co-authors. Any exception to the involvement of APHRC staff should be approved by the Director of Research, APHRC.\n\n7. Security: The user will take responsibility for the security of the data by ensuring that the data are used and stored in a secure environment where access is password protected. This will ensure that non-authorized people should not have access to the data.\n\n8. Loss of privilege to use data: In the event that APHRC determines that the data user is in violation of the conditions for using the data, or if the user wishes to cancel this agreement, the user will destroy the data files provided to him\/her. APHRC retains the right to revoke this agreement or informs publishers to withhold publication of any work based wholly or in part on its data if the conditions for using the data are violated.\n\n9. Acknowledgement: Any work\/reports from this data must acknowledge APHRC as the source of these data. For example, the suggested acknowledgement for NUHDSS data is:\n\n\"This research uses livelihoods data collected under the longitudinal Nairobi Urban Health and Demographic Surveillance System (NUHDSS) since 2006. The NUHDSS is carried out by the African Population and Health Research Center in two slums settlements (Korogocho and Viwandani) in Nairobi City.\"\n\nAdditionally all funders, the study communities that provided the data, and staff who collected and analyzed or processed the data should be acknowledged.\n\n10. Deposit of Reports\/Papers: The user should submit electronic and paper copies of all publications generated using APHRC data to the Policy Engagement and Communications Department, with copies to the Director of Research.\n\n11. Change of contact details: The user will promptly inform the Director of Research of any change in your personal details as contained on this data request form.","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."}}}}