Review Article Factors influencing dietary behaviours in urban food environments in Africa: a systematic mapping review Hibbah Osei-Kwasi1,2,* , Aarti Mohindra1, Andrew Booth1, Amos Laar3, Milka Wanjohi4, Fiona Graham1, Rebecca Pradeilles1, Emmanuel Cohen5,6 and Michelle Holdsworth1,7 1Public Health Section, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield S14DA, UK: 2Department of Clinical Sciences and Nutrition, University of Chester, Chester, UK: 3Department of Population, Family & Reproductive Health, School of Public Health, University of Ghana, Accra, Ghana: 4African Population and Health Research Center, Nairobi, Kenya: 5South AfricanMedical Research Council/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa: 6Unité Mixte Internationale 3189 Environnement, Santé, Sociétés, Faculté de Médecine- secteur Nord, Centre National de la Recherche Scientifique, Marseille, France: 7Joint Research Unit on Food & Nutrition Research Global South, French National Research Institute for Sustainable Development (IRD), Montpellier, France Submitted 17 June 2019: Final revision received 8 November 2019: Accepted 19 December 2019: First published online 26 May 2020 Abstract Objective: To identify factors influencing dietary behaviours in urban food environ- ments in Africa and identify areas for future research. Design: We systematically reviewed published/grey literature (protocol CRD4201706893). Findings were compiled into a map using a socio-ecological model on four environmental levels: individual, social, physical and macro. Setting: Urban food environments in Africa. Participants: Studies involving adolescents and adults (11–70 years, male/female). Results: Thirty-nine studies were included (six adolescent, fifteen adolescent/adult combined and eighteen adult). Quantitative methods were most common (twenty- eight quantitative, nine qualitative and two mixed methods). Studies were from fifteen African countries. Seventy-seven factors influencing dietary behaviours were identified, with two-thirds at the individual level (45/77). Factors in the social (11/77), physical (12/77) and macro (9/77) environments were investigated less. Individual-level factors that specifically emerged for adolescents included self- esteem, body satisfaction, dieting, spoken language, school attendance, gender, body composition, pubertal development, BMI and fat mass. Studies involving adolescents investigated social environment-level factorsmore, for example, sharing food with friends. The physical food environment was more commonly explored in adults, for example, convenience/availability of food. Macro-level factors associated with dietary behaviours were food/drink advertising, religion and food prices. Factors associated with dietary behaviour were broadly similar for men andwomen. Conclusions: The dominance of studies exploring individual-level factors suggests a need for research to explore how social, physical and macro-level environments drive dietary behaviours of adolescents and adults in urban Africa. More studies are needed for adolescents and men, and studies widening the geographical scope to encompass all African countries. Keywords Dietary behaviour Africa Urban Food environment Rapid demographic change in Africa, partly driven by increasing migration of individuals into cities, has changed people’s food environments and dietary habits(1). Economic development has increased access to food markets selling energy-dense processed foods at low prices and decreased the price of certain foods such as vegetable oils(2). Public Health Nutrition: 23(14), 2584–2601 doi:10.1017/S1368980019005305 *Corresponding author: Email h.a.osei-kwasi@sheffield.ac.uk © The Authors 2020. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. https://orcid.org/0000-0001-5084-6213 https://orcid.org/0000-0001-5643-1473 https://orcid.org/0000-0001-6028-885X https://doi.org/10.1017/S1368980019005305 http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ Modification of diet structure towards a higher intake of energy-dense foods (especially from fat and added sugars), a higher consumption of processed foods(3), animal source foods, sugar and saturated fats, and a lower intake of complex carbohydrates, dietary fibre, fruit and vege- tables has led to a significant change in diet quality over the past 20 years(4). The nutrition transition in urban areas of many African countries has resulted in a ‘double burden of disease’ in which there is an increased prevalence of nutrition-related non-communicable diseases (NR-NCD) alongside existing communicable diseases. Although obesity prevalence is higher among African women than men, there has been a rise in both(5,6). Children and ado- lescents are an important group to target in the preven- tion of overweight and obesity(7). In 2010, of the 43 million children estimated to be overweight and obesity, 35 million were from low- and middle-income coun- tries(7). The prevalence of overweight and obesity in chil- dren in Africa is expected to increase from 8·5 % (2010) to a projected 12·7 % by 2020. By understanding this shift in nutrition and disease, new NR-NCD prevention strate- gies that account for the factors driving dietary behav- iours can be developed across the life course. A mapping review was previously conducted in 2015(8) to identify drivers of dietary behaviours specifically in adult women within urban settings in African countries and identify priorities for future research. However, the increasing evidence that the overweight and obesity burden is spread more widely across population groups indicates the need for a broader review. Hence, this sys- tematic review mapped the factors influencing dietary behaviours of adolescents and adults of both genders in African urban food environments and identified areas for future research. Methods A systematic mapping review(9) was conducted to map existing literature regarding factors influencing dietary behav- iours in urban Africa. Systematic mapping reviews are often conducted as a prelude to further research and are imperative in the identification of research gaps. Prior to conducting the review, the Cochrane Database of Systematic Reviews and MEDLINE were searched to ensure that no similar reviews were underway or had been conducted beyond the original mapping review(8). A review protocol was produced to ensure transparency in the review methodology and then registered with the PROSPERO database of existing and on-going systematic reviews (registration number CRD4201706893). To determine appropriate inclusion and exclusion crite- ria for the review, the Sample, Phenomenon of Interest, Design, Evaluation, Research type tool was used(10). Criteria used in the original review were modified to acknowledge the additional population groups (adolescents and adult men)(8); otherwise, the same processes were applied to ensure compatibility. Inclusion and exclusion criteria The original review conducted in 2015 investigatedwomen aged 18–70 years living in urban Africa from 1971 to April 2015(8). This current review synthesised recent research in this same group, published since April 2015 to April 2019, and included men (18–70 years) and female/male adoles- cents (11–17 years), between 1971 and April 2019. All par- ticipants were living in urban Africa, those from rural settings were excluded, as were studies with participants <11 years or>70 years. Participants with a clinical diagnosis related to NR-NCD were excluded; excluding studies with specific diseases also ensured that the included studies were of healthy African populations and not specific clinical sub-groups. The phenomenon of interest was defined as factors influencing dietary behaviours. This was purposely broad to enable sensitive mapping of all available literature. Furthermore, studies including African-Americans or African migrants to non-African countries were excluded on the basis of setting. Studies measuring the effect of factors on dietary behaviours were included, but studies that focused on the relationship between diet and diet-related diseases were excluded given the focus on factors influencing dietary behaviour rather than their effect on specific diseases. To ensure broad coverage of research, all types of study designs were included, that is, randomised controlled trials, cohort studies, case–control studies, ecological/observational studies, reviews and meta-analyses. All publication types were included, provided they were in English or French. Languages were chosen to acknowledge the main publish- ing languages in Africa. For adult men and adolescents, any appropriate study from 1971 to 2019 was included. For adult women, studies published since the previous search (April 2015–April 2019) were retrieved. The chosen 1971 start date reflected the earliest appearance of relevant publications concerning health behaviour in the context of the epidemiological transition(11) on the nominated databases and search engines. The primary outcome was dietary behaviour, including macronutrient, food item and food diversity intake, as well as eating habits, preferences, choices and feeding-related mannerisms. Macronutrients were included because of the review’s focus on urban settings where dietary transi- tion is more likely to be associated with dietary change from the nutrition transition, which is associated with increased consumption of fat, vegetable and edible fat and increased added sugar(6). Search strategy Electronic searches were conducted across six key data- bases: EMBASE, MEDLINE, CINAHL, PsycINFO, ASSIA and African Index Medicus. The search strategy replicated that Dietary behaviours in African food environments 2585 used in the previous reviewwith the additional inclusion of search terms representing adult men and adolescents(8). An example of a search strategy used for these databases can be found in Supplemental Table 1 in the online supplemen- tary material. Grey literature was explored through the WHO International Trials Registry Index and Thesis (UK and Ireland) Database. Reference lists for the seventeen studies included in the initial review were examined, and citation tracking using Google Scholar (through Publish or Perish™) was also con- ducted. Forward and backward citation tracking sought to ensure that no important studies were missed and that representation of appropriate literature was maximised. Reference lists of newly identified included studies, reflect- ing the expansion of date range and populations of interest, were also reviewed. The dual approach of subject search- ing and follow-up citation tracking was considered to provide sufficient coverage of the relevant literature(12). Study selection Studies that fulfilled the inclusion and exclusion criteria for title and abstract then underwent full-text screening by two reviewers (A.M./F.G.). Duplicates were removed prior to full-text screening. A second reviewer (H.O.-K./M.H.) assessed 10 % of excluded studies at two stages: the title and abstract stage and the full-text search stage. Any dis- agreements were resolved by discussion. If no agreement was reached, a third reviewer also assessed the study. Quality assessment Quality assessment is not a mandatory requirement for a mapping review(9). However, by incorporating it into the review methodology, it enhances the credibility of the review’s findings and is particularly useful in documenting uncertainties that persist in relation to previous research(9). Quality assessment was conducted with a validated tool(13) for qualitative and quantitative studies by two reviewers independently (A.M., M.W. or F.G.). Data extraction Data were extracted from included studies by one of two principal reviewers (A.M. or F.G.) supported by a second reviewer (H.O.-K. or M.H.) and was checked by a member of the review team (M.W.). As the aim of this mapping review was to map the factors influencing dietary behav- iours of adolescents and adults living in African urban food environments and identify areas for future research, it was decided to include all factors reported by authors and not to restrict the review to reporting factors only where a statis- tical relationship or association had been demonstrated. Data synthesis There are different approaches to updating a review. In this review, the new findings were integrated with those of the original review at the synthesis level(14) in order to present all the evidence for men, women and adolescents for the same timescale. In order to determine which factors influ- ence dietary behaviours in the three population sub-groups, factors influencing dietary behaviours for adults and adoles- cents of all thirty-eight studies were mapped to the socio- ecological model defined by Story et al.(15). Factors were placed within four broad levels: individual, social environ- ment, physical environment and macro-environment and assigned to an appropriate sub-level. For novel factors that emerged, it was decided within the team where to place it in the aforementioned socio-ecological model, similar to the original review(8). Reporting of the review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist(16). Results Search results The search yielded 2433 title and abstract records after duplicates were removed (Fig. 1); 274 records remained for full-text retrieval, at which stage 247 records were excluded, leaving twenty-seven studies for inclusion for studies of adolescents, men and women (from 2015). Twelve studies from an earlier review of women only aged 18–70 years (1971–2015) were integrated in the review findings, giving a total of thirty-nine studies. Description of included studies Thirty-nine studies were included in the final data synthesis (Table 1), of which nineteen were conducted in lower middle-income countries(17): Cape Verde, Egypt, Ghana, Kenya, Morocco, Nigeria and Tunisia. Thirteen studies were conducted in upper middle-income countries: Botswana, Mauritius and South Africa, and one study was undertaken in the Seychelles (high-income country). Only six studies were undertaken in low-income countries: Burkina Faso, Benin, Niger and Tanzania (Table 1). Over half of studies were conducted in Ghana and Morocco (six studies each) or South Africa (ten studies). Of the thirty-nine studies, eight were qualitative (ten records)(18–27), twenty-nine (thirty-three records) were quantitative(28–60) and two used mixed methods(61,62) stud- ies. The qualitative and quantitative data in the latter were extracted separately in order to generate distinct quality assessment scores. Of the thirty-nine studies, thirty-two were cross-sectional studies(18–20,25,28–37,39–45,47–62), four were observational(18,21,26,27,46), two used a longitudinal design(38) and one was a detailed case study(23,24). The methodology consisted of interviews and focus groups to obtain qualita- tive data, whereas self-administered or interviewer-led surveys were mostly used for quantitative studies. Quality assessment In summary, while most of the quantitative studies scored high on criteria such as appropriate study designs, 2586 H Osei-Kwasi et al. https://doi.org/10.1017/S1368980019005305 question/objective sufficiently described and data analy- sis clearly described, these studies did not report on con- trolling for confounders or estimation of variance in the main results. Similarly, in all qualitative studies, authors failed to report on procedures to establish credibility or show reflex- ivity. The individual aspects of the quality assessment con- ducted for all thirty-nine included studies (see online supplementary material, Supplemental Tables 2 and 3). Factors influencing diet or dietary behaviour in urban Africa In total, seventy-seven factors influencing dietary behav- iours were identified, with two-thirds at the individual level (45/77). Factors in the social (11/77), physical (12/77) and macro (9/77) environments were investigated less. Slightly more studies investigating social-level factors studied ado- lescent populations (Table 2). The configuration of dietary factors in adult men paralleled that of adult women, prob- ably because relevant included studies examined a mixed adult population. In all population groups, the individual and household factors level of the socio-ecological model was the most studied. Dietary factors in adult women, adult men and adolescents Individual level Almost two-thirds of factors identified were on the individ- ual level (45/77), of which twelve related to cognitions, fif- teen to lifestyle/behaviours, nine were biological factors and nine were demographic factors (Fig. 2). Factors spe- cific to adolescents included self-esteem, body satisfaction, dieting, spoken language, school attendance, gender, body composition, pubertal development, BMI and fat mass. Records identified through database searching (n 3242 + 216) = 3458 MEDLINE, EMBASE, PsycINFO, CINAHL, African Index Medicus and ASSIA Additional records identified through other sources (n 464) Records after duplicates removed (n 2217 + 216) = 2433 Records screened (title and abstract stage) (n 2217 + 216) = 2433 Records excluded (n 1971 + 188) = 2159 Full-text articles assessed for eligibility (n 246 + 28) = 274 Full-text articles excluded, with reasons (n 224 + 23) 247 Studies included in updated synthesis of adolescents, adult males and women = 27 (twenty quantitative, six qualitative and one mixed methods study) Total n 39 studies Twelve studies from previous review of women only (nine quantitative, two qualitative and one mixed methods study) Id en tif ic at io n S cr ee ni ng El ig ib ili ty In cl ud ed Fig. 1 (colour online) Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram showing the selection of studies for the present systematic mapping review Dietary behaviours in African food environments 2587 https://doi.org/10.1017/S1368980019005305 https://doi.org/10.1017/S1368980019005305 Table 1 Characteristics of the included studies (39 studies and 45 records) Study Design, method Country Income level Sample characteristics Sample size SamplingQualitative studies Gender Age (range) n/households Batnitzky(18) Field study, semi- structured interviews, observation Morocco Lower middle Mixed 20þ years (adult) 1789 Unclear – individuals then households Boatemaa et al.(19) Cross-sectional, interviews Ghana Lower middle Mixed 15–35 years and 35þ years (adolescent and adult) 30 Purposive sampling Brown et al.(20) Cross-sectional, focus groups Botswana Upper middle Mixed 12–18 years (adolescent) and adult (age range not specified) 72–132 (adolescents) parents unknown Sampling of schools with differing tuition status Craveiro et al.(21) Observational, focus groups Cape Verde Lower middle Mixed 18–41 years (adult) 48 Opportunistic sampling using probabilistic sampling with random selection Draper et al.(22) Observational, focus groups South Africa Upper middle Female 24–51 years (adult) 21 Convenience sampling Legwegoh(23) and Legwegoh & Hovorka(24) Case-study, interview Botswana Upper middle Mixed 20–65 years (adult) 40 households Purposive sample, stratified based on household- head gender and socio-economic status Rguibi & Behalsen(25) Cross-sectional, questionnaire via interview Morocco Lower middle Female 15–70 years (adolescent and adult) 249 Convenience. Women visiting primary care centres Sedibe et al.(26) and Voorend et al.(27) Observational, duo- interviews South Africa Upper middle Female 15–21 years (adolescent) 58 Voluntary participation following researcher involvement in school Quantitative studies Agbozo et al.(28) Cross-sectional, questionnaire Ghana Lower middle Mixed 60–70 years (adult) 120 Purposive sample from four peri-urban communities Amenyah & Michels((29) Cross-sectional, questionnaire Ghana Lower middle Mixed 11–18 years (adolescent) 370 Random selection, five secondary schools Aounallah-Skhiri et al.(30) Cross-sectional, questionnaire Tunisia Lower middle Mixed 15–19 years (adolescent and adult) 1019 Clustered random sampling from three regions of Tunisia Becquey et al.(31) Cross-sectional, questionnaire Burkina Faso Low Mixed 15–65 years (adolescent and adult) 1072 Purposive random sampling Cisse-Egbuonye et al.(32) Quantitative, cross- sectional Niger Low income Female 15–49 years (adolescent and adult) 3360 Randomly selected household heads in purposive sample Codjoe et al.(33) Cross-sectional Ghana Lower middle income Mixed 15–59 years (adolescent and adult males), 15–49 years (adolescent and adult) 452 households Purposive sampling according to age from a larger data set El Ansari & Berg- Beckhoff(34) Cross-sectional, questionnaire Egypt Lower middle Mixed 16–30 years (adolescent and adults) 2810 Voluntary questionnaire distributed to students attending lectures of randomly selected courses Feeley et al.(35) Cohort, questionnaire South Africa Upper middle Mixed 13–17 years (adolescent) 1298 Cohort selection sampling-recruitment of all singleton births that occurred over a 7-week period in public delivery centres from all population groups 2588 H O sei-K w asiet a l. Table 1 Continued Study Design, method Country Income level Sample characteristics Sample size SamplingQualitative studies Gender Age (range) n/households Fokeena & Jeewon(36) Cross-sectional, self-reported questionnaires Mauritius Upper middle Mixed 12–15 years (adolescent) 200 Multistage sampling, schools randomly selected from four educational zones of Mauritius and sample taken from three of these schools Glozah & Pevalin(37) Cross-sectional, self-reported questionnaires Ghana Lower middle income Mixed 14–21 years (adolescent and adult) 770 Participants selected at random from four senior high schools that were purposively selected in Accra Gitau et al.(38) Longitudinal, self- reported questionnaire South Africa Upper middle Males 13–17 years (adolescent) 391 Stratified convenience sample Hattingh et al.(39,40,41) Cross-sectional, questionnaire South Africa Upper middle Female 25–44 years (adult) 488 Stratified random according to number of plots in each settlement Jafri et al.(42) Cross-sectional, questionnaire Morocco Lower middle Female 18þ years (adult) 401 Multistage cluster. Households randomly selected within clusters Kiboi et al.(43) Cross-sectional, structured interviews, questionnaire Kenya Lower middle Female 16–49 years (adolescent and adult) 254 Purposive sampling at antenatal clinic in a hospital over 1month Landais(44) and Landais et al.(45) Cross-sectional, questionnaire Morocco Lower middle Female 20–49 years (adult) 894 Multistage cluster. Households then addresses randomly selected from enumeration areas López et al.(46) Observational, 3 × 24 h dietary recalls Morocco Lower middle Mixed 15–20 years (adolescent and adult) 327 All students enrolled in high schools year 2007– 2008 completed survey Mayén et al.(47) Cross-sectional, survey Seychelles High Mixed 25–64 years (adult) 2004 National surveys, random sample drawn from entire population Mbochi et al.(48) Cross-sectional, questionnaire Kenya Lower middle Female 25–54 years (adult) 365 Stratified random according to number of women in each socio-economic stratum Mogre et al.(49) Cross-sectional, questionnaire Ghana Lower middle Mixed 20–60 years (adult) 235 Stratified random based on number of employees in each department Njelekela et al.(50) Cross-sectional, questionnaire Tanzania Low Mixed 45–66 years (adult) 209 Random stratified selection from list of adult residents, strata: gender Onyiriuka et al.(51) Cross-sectional, structured questionnaire Nigeria Lower middle Female 12–19 years (adolescent and adult) 2097 Random selection by ballot from four all-girls schools, no sampling performed as designed to include all students Peltzer & Phaswana- Mafuya(52) Cross-sectional, survey South Africa Upper middle Mixed >50 years (adult) 3840 National population based sample, from original study (SAGE; two-stage probability sample) Savy et al.(53) Cross-sectional, questionnaire Burkina Faso Low Female 29–50 years (adult) 481 Random, from a database containing an exhaustive list of inhabitants Sodjinou et al.(54,55) Cross-sectional, questionnaire Benin Low Mixed 25–60 years (adult) 200 Multistage cluster. Neighbourhoods, households, then individuals randomly selected Soualem et al.(56) Cross-sectional, questionnaires Morocco Lower middle Mixed 12–16 years (adolescent) 190 Random selection from five schools in Gharb region Steyn et al.(57) Cross-sectional, structured interview South Africa Upper middle Mixed ≥16 years (adolescent and adult) 3287 Stratified sampling of annual survey data Van Zyl et al.(58) Cross-sectional, questionnaire South Africa Upper middle Mixed 19–30 years (adult) 341 Convenience, residents of Johannesburg visiting a mall D ietary b eh avio u rs in A frican fo o d en viro n m en ts 2589 Cognitions. Taste and hunger were cognition-related fac- tors only found within adult studies(26,27,32,58,61). For instance, one quantitative study(58) in Johannesburg found that 52·5 % of participants believed taste influenced fast- food intake. Higher perceived stress levels were found to significantly decrease the amount of fruit and vegetable consumption in a mixed adult population in Egypt, with a more pronouned effect in men(34). Food knowledge and subjective health status was more commonly reported in the studies of adults(28,46,59). Preferences, mood and per- ception of diet quality and quantity were reported in both qualitative and quantitative studies of both adolescents and adults(19,26,27,31,59). A small number of factors emerged on the relationship between body satisfaction and dietary behaviours. An asso- ciation was identified between decreased self-esteem and body satisfaction with disordered eating in South African adolescents, as measured by the Eating Attitudes Tests 26(38). No significant association was found between body image perception and food intake in a quantitative study of female adults(59). Lifestyle/behaviours. A third of individual-level factors identified for adults were categorised under the lifestyle/ behaviours sub-level. Time limitation was found to be an important factor in five studies encompassing qualita- tive and quantitative data conducted in Botswana, Cape Verde, Ghana and South Africa(20,21,23,24,49,58). In the quali- tative study conducted in Cape Verde(21), reduced time availability was associated with the intake of unhealthy street foods. Other important lifestyle-related factors iden- tified in a quantitative study related to lack of fruit and veg- etable intake(52) were tobacco use, alcohol use, physical inactivity and low quality of life. Spoken language was found to be significantly associated with dietary quality in one quantitative study conducted in Morocco, as ado- lescents who only spoke Arabic had a poorer quality of diet than those who spoke both Arabic and French(56). Biological. Evidence from quantitative studies was found for the role of biological factors, which were associated with dietary behaviours in adults, that is, morbidity(43), age(31,39–42,44,45,51,53,56) and having multiple children (parity)(44,45,54). For instance, increased morbidity was significantly associated with minimum dietary diversity among pregnant women in Kenya(43). More diverse biological factors were investigated for adolescents than for adults. However, only age(51), BMI and fat mass(35) were significantly associated with dietary behaviours. For instance, increasing age was signifi- cantly associated with skipping meals among schoolgirls in Nigeria(51) and fat mass was negatively associated with poor eating behaviour(35). Demographic. More demographic factors were identi- fied in adult women than in mixed adult studies. In one quantitative study of adults conducted in Burkina Faso, males of higher SES, as measured by income and education were significantly aggregated in the ‘urban’ diet cluster,T ab le 1 C on tin ue d S tu dy D es ig n, m et ho d C ou nt ry In co m e le ve l S am pl e ch ar ac te ris tic s S am pl e si ze S am pl in g Q ua lit at iv e st ud ie s G en de r A ge (r an ge ) n/ ho us eh ol ds W as w a( 59 ) C ro ss -s ec tio na l, qu es tio nn ai re K en ya Lo w er m id dl e F em al e 20 – 25 ye ar s (a du lt) 26 0 S tr at ifi ed ra nd om ac co rd in g to un iv er si ty de pa rt m en ts iz e in cl ud in g ea ch ye ar Z eb a et al .(6 0) C ro ss -s ec tio na l, qu es tio nn ai re s B ur ki na F as o Lo w M ix ed 25 – 60 ye ar s (a du lt) 11 0 S tr at ifi ed ra nd om sa m pl in g, st ra tif ic at io n by in co m e M ix ed -m et ho ds C ha rlt on et al .(6 1) C ro ss -s ec tio na l, qu es tio nn ai re ; fo cu s gr ou ps S ou th A fr ic a U pp er m id dl e F em al e Q ue st io nn ai re :1 7– 50 ye ar s (a du lt an d ad ol es ce nt ); F oc us gr ou ps :1 8– 49 ye ar s (a du lt an d ad ol es ce nt ) Q ue st io nn ai re : 39 4; fo cu s gr ou ps :3 9 C on ve ni en ce , ac co rd in g to ag e an d ge nd er P ra de ill es (6 2) C ro ss -s ec tio na l, qu es tio nn ai re s; fo cu s gr ou ps S ou th A fr ic a U pp er m id dl e M ix ed Q ue st io nn ai re :1 7– 19 ye ar s (a du lt an d ad ol es ce nt ); F oc us gr ou ps :1 8 ye ar sþ (a du lt) Q ue st io nn ai re : 63 1; fo cu s gr ou ps :5 1 C oh or ts el ec tio n sa m pl in g- re cr ui tm en to fa ll si ng le to n bi rt hs th at oc cu rr ed ov er a 7- w ee k pe rio d in pu bl ic de liv er y ce nt re s fr om al l po pu la tio n gr ou ps ;S no w ba ll sa m pl in g 2590 H Osei-Kwasi et al. Table 2 Factors in urban African food environments influencing dietary behaviours in the included studies (n 39) Level Sub-level Factor (no. of studies) Dietary behaviour Evidence Population Individual and household (45) Cognitions (12) Taste (4) Dietary intake Pradeilles(62)MM, Sedibe et al.(26)QL and Voorend et al.(27)QL Mixed adolescent adult; Female adolescent Fast-food intake Van Zyl et al.(58)QN* Mixed adult Food choice Charlton et al.(61)MM Female adolescent and adult Preferences (1) Food choice Boatemma et al.(19)QL Mixed adolescent and adult; female adolescent Hunger/not hungry/lack of appetite (6) Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN* Mixed adult Food intake Agbozo et al.(28)QN*, Mogre et al.(49)QN* and Waswa(59)QN* Mixed adult; Mixed adult; Female adult Dietary diversity Cisse-Egbuonye et al.(32)QN† Female adolescent and adult Skipping meals Onyiriuka et al.(51)QN† Female adolescent Mood (1) Food intake Waswa(59)QN* Female adult Subjective health status (4) Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN‡ and Mogre et al.(49)QN* Mixed adult; Mixed adult Food choice Agbozo et al.(28)QN* Mixed adult Dietary intake/Disordered eating Amenyah & Michels(29)QN* Mixed adolescent Perceived stress (1) Dietary intake El Ansari & Berg-Beckhoff(34)QN† Mixed adolescent and adult Self-esteem (1) Disordered eating Gitau et al.(38)QN‡ Males adolescent Body satisfaction (1) Disordered eating Gitau et al.(38)QN‡ Males adolescent Body image perception (1) Food intake Waswa(59)QN* Female adult Food knowledge (3) Fruit and vegetable intake Landais(44)/Landais et al.(45)QN† Mixed adult Food choice Agbozo et al.(28)QN‡ Mixed adult Food intake Waswa(59)QN* Female adult Perception of diet quality (1) Dietary diversity Becquey et al.(31)QN† Mixed adolescent and adult Perception of diet quantity (1) Dietary diversity Becquey et al.(31)QN† Mixed adolescent and adult Lifestyle/behaviours (15) Dieting (1) Dietary habits Sedibe et al.(26)/Voorend et al.(27)QL Female adolescent Skipping meals (1) Fruit and vegetable intake Landais(44)/Landais et al.(45)QN* Female adult Snacking (1) Dietary diversity Becquey et al.(31)QN† Mixed adolescent and adult Habit/routine (1) Food choice Charlton et al.(61)MM Female adolescent and adult Household dietary diversity (1) Dietary diversity Cisse-Egbuonye et al.(32)QN† Female adolescent and adult Processed food consumption (1) Fruit and vegetable intake Landais(44)/Landais et al.(45)QN* Female adult Eating out occasions (1) Fruit and vegetable intake Landais(44)/Landais et al.(45)QN* Female adult Eating three daily meals (1) Fruit and vegetable intake Landais(44)/Landais et al.(45)QN* Female adult Overall lifestyle (1) Diet quality Sodjinou et al.(54)/Sodjinou et al.(55)QN† Mixed adult Spoken language (1) Food quality Soualem et al.(56)QN† Mixed Adolescent Time limitations (5) Dietary intake Legwegoh(23)/Legwegoh & Hovorka(24)QN Mixed adult Fast-food intake Van Zyl et al.(58)QN* Mixed adult Food choice Brown et al.(20)QL Mixed adolescent and adult Unhealthy food intake Craveiro et al.(21)QL Mixed adult Skipping meal Mogre et al.(49)QN* Mixed adult Quality of life (1) Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN‡ Mixed adult Tobacco use (2) Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN† Mixed adult Diet quality Sodjinou et al.(54)/Sodjinou et al.(55)QN† Mixed adult Alcohol use (2) Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN* Mixed adult Diet quality Sodjinou et al.(54)/Sodjinou et al.(55)QN† Mixed adult Physical activity (5) Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN* Mixed adult Energy intake Hattingh et al.(39)*,(40)*,(41)QN* Female adult Dietary intake Becquey et al.(31)QN† Mixed adolescent and adult D ietary b eh avio u rs in A frican fo o d en viro n m en ts 2591 Table 2 Continued Level Sub-level Factor (no. of studies) Dietary behaviour Evidence Population Dietary patterns Zeba et al.(60)QN* Mixed adult Dietary quality Sodjinou et al.(54)/Sodjinou et al.(55)QN* Mixed adult Biological (9) Morbidity (1) Dietary diversity Kiboi et al.(43)QN† Female adolescent and adult Age (11) Fruit and vegetable intake Landais(44)/Landais et al.(45)QN‡ Female adult Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN‡ Mixed adult Dietary quality Soualem et al.(56)QN* Mixed adolescent Dietary diversity Becquey et al.(31)QN*, Savy et al.(53)QN*, Codjoe et al.(33)QN‡ and Cisse-Egbuonye et al.(32)QN‡ Mixed adolescent and adult; Adult women; Mixed adolescent and adult; Female adolescent and adult Meal skipping Onyiriuka et al.(51)QN† Female adolescent Food choice Onyiriuka et al.(51)QN Female adolescent Dietary patterns Zeba et al.(53)QN* Mixed adult Energy intake Hattingh et al.(39)/Hattingh et al.(40)/Hattingh et al.(41)QN* Female adult Fattening practices Jafri et al.(42)QN* Adult women Parity (2) Dietary patterns Zeba et al.(54)QN* Mixed adult Fruit and vegetable intake Landais(42)/Landais et al.(45)QN‡ Adult women Gender (5) Dietary quality Soualem et al.(56)QN* Mixed adolescent Dietary diversity Codjoe et al.(33)QN† Mixed adolescent and adult Dietary intake Aounallah-Skhiri et al.(30)QN* Mixed adolescent and adult Fast-food intake Van zyl et al.(58)QN† Mixed adult Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN‡ Mixed adult Body composition (2) Dietary intake Pradeilles(62)MM‡ Mixed adolescent and adult Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN‡ Mixed adult Pubertal development (1) Dietary intake Pradeilles(62)MM Mixed adolescent and adult BMI z-score (1) Dietary intake/Snacking Feeley et al.(35)QN† Mixed adolescent Fat mass (1) Dietary intake/Snacking Feeley et al.(35)QN† Mixed adolescent Health (2) Food intake Waswa(59)QN* Female adult Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN* Mixed adult Demographic (9) Income (individual/household) (6) Dietary diversity Codjoe et al.(33)QN* and Kiboi et al.(43)QN† Female adolescent and adult Dietary intake Legwegoh et al.(23)/Legwegoh et al.(24)QL and Steyn et al.(57)QN† Mixed adult; Mixed adolescent and adult Dietary patterns Zeba et al.(54)QN‡ Mixed adult Dietary quality Soualem et al.(56)QN† Mixed adolescent Socio-economic status (individual/ household) (13) Dietary diversity Becquey et al.(31)QN† and Savy et al.(53)QN* Mixed adolescent and adult; Female adult Dietary intake Aounallah-Skhiri et al.(30)QN†, Legwegoh et al.(23)/Legwegoh et al.(24)QL, Hattingh et al.(39)/Hattingh et al.(40)/Hattingh et al.(41)QN‡, Mbochi et al.(48)QN†, Njelekela et al.(50)QN‡, Pradeilles(62)MM‡ and Steyn et al.(57)QN† Mixed adolescent and adult; Mixed adult; Female adult; Female adult; Mixed adult; Mixed adolescent and adult; Mixed adolescent and adult; Fruit and vegetable intake Landais(44)/Landais et al.(45)QN* Female adult Dietary quality Fokeena & Jeewon(36)QN* Mixed adolescent Meal skipping /Food choices Onyiriuka et al.(51)QN* Female adolescent and adult Fast-food intake Van zyl et al.(58)QN† Mixed adult 2592 H O sei-K w asiet a l. Table 2 Continued Level Sub-level Factor (no. of studies) Dietary behaviour Evidence Population Employment (individual/parent/ household head) (7) Dietary diversity Kiboi et al.(43)QN†, Cisse-Egbuonye et al.(32) QN† and Codjoe et al.(33)QN* Female adolescent and adult; Female adolescent and adult; Mixed adult and adolescent Fruit and vegetable intake Landais(44)/Landais et al.(45)QN† Female adult Dietary intake Aounallah-Skhiri et al.(30)QN† and Steyn et al.(57)QN† Mixed adolescent and adult; Mixed adolescent and adult Dietary quality Soualem et al.(56)QN† Mixed adolescent Education (individual/parent) (9) Dietary diversity Kiboi et al.(43)QN† Female adolescent and adult Dietary intake Aounallah-Skhiri et al.(30)QN†, Glozah & Pevalin(37)QN† and Lopez et al.(46)QN* Mixed adolescent and adult; Mixed adolescent and adult; Mixed adolescent and adult Dietary quality Soualem et al.(56)QN‡ Mixed adolescent Dietary patterns Zeba et al.(54)QN‡ Mixed adult Fruit and vegetable intake Landais(44)/Landais et al.(45)QN and Peltzer & Phaswana-Mafuya(52)QN† Female adult ; Mixed adult Household dietary diversity Codjoe et al.(33)QN† Mixed adolescent and adult Wealth (individual/household) (3) Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN* Mixed adult Dietary diversity Codjoe et al.(33)QN† Mixed adult and adolescent Food choice Agbozo et al.(28)QN* Mixed adult Land ownership (1) Dietary diversity Kiboi et al.(43)QN† Female adolescent and adult Ethnicity (5) Dietary intake Steyn et al.(57)QN‡ Mixed adolescent and adult Disordered eating Gitau et al.(38)QN‡ Male adolescent Meal skipping/Food choice Onyiriuka et al.(51)QN* Female adolescent and adult Fruit and vegetable consumption Peltzer & Phaswana-Mafuya(52)QN† Mixed adult Dietary diversity Codjoe et al.(33)QN‡ Mixed adult and adolescent Household food expenditure (2) Dietary diversity Becquey et al.(31)QN† and Codjoe et al.(33) QN‡ Mixed adolescent and adult; Mixed adult and adolescent Financial insecurity (1) Unhealthy eating choice Draper et al.(22)QL Female adult Social environment (11) Family (9) Marital status (6) Fruit and vegetable intake and diversity Landais(44)/Landais et al.(45)QN‡ and Peltzer & Phaswana-Mafuya(52)QN* Female adult; Mixed adult Fattening practices Rguibi & Behalsen(25)QL and Jafri et al.(42) QN* Female adolescent and adult; Adult women Dietary diversity Becquey et al.(31)QN† and Savy et al.(53)QN* Mixed adolescent and adult; Female adult Household social roles (1) Snacking Batnitzky(18)QL Mixed adult Household composition (4) Meal skipping Onyiriuka et al.(51)QN* Female adolescent and adult Food intake Batnitzky(18)QL Mixed adult Dietary diversity Codjoe et al.(33)QN‡ and Cisse-Egbuonye et al.(32)QN‡ Mixed adult and adolescent; Female adolescent and adult Eating companions (2) Meal skipping Onyiriuka et al.(51)QN* Female adolescent and adult Food choice Brown et al.(20)QL Mixed adolescent and adult Shared bowl (1) Fruit and vegetable intake and diversity Landais(43)/Landais et al.(45)QN‡ Female adult D ietary b eh avio u rs in A frican fo o d en viro n m en ts 2593 Table 2 Continued Level Sub-level Factor (no. of studies) Dietary behaviour Evidence Population What rest of family eat (2) Food choice Charlton et al.(61)MM and Boatemma et al.(19) QL Female adolescent and adult; Mixed adolescent and adult Number of children (1) Fruit and vegetable intake and diversity Landais(44)/Landais et al.(45)QN* Female adult Parental influence (1) Adequacy of food intake Waswa(59)QN* Female adult Support in the household (3) Food choice Boatemma et al.(19)QL, Becquey et al.(31)QN† and Savy et al.(53)QN* Mixed adolescent and adult; Mixed adolescent and adult; Female adult Dietary intake Glozah & Pevalin(37)QN† Mixed adolescent and adult Friends and peers (n 2) Friendship (4) Fruit and vegetable consumption Peltzer & Phaswana-Mafuya(52)QN* Mixed adult Dietary intakes Sedibe et al.(26)*/Voorend et al.(27)QL* Female adolescent Food choice Boatemma et al.(19)QL Mixed adolescent and adult Adequacy of food intake Waswa(59)QN* Female adult Fast-food intake Van zyl et al.(58)QN* Mixed adult Religious groups (1) Dietary intake Pradeilles(62)MM Mixed adolescent and adult Physical environment (12) Home (4) Household food stocks (1) Dietary diversity Becquey et al.(31)QN†, Kiboi et al.(43)QN† and Codjoe et al.(33)QN‡ Mixed adolescent and adult; Female adolescent and adult; Mixed adult and adolescent Food availability (3) Adequacy of food intake Waswa(59)QN* Female adult Dietary diversity Codjoe et al.(33)QN† Mixed adult and adolescent Food choice Agbozo et al.(28)QN* Mixed adult Living area (3) Fruit and vegetable intake/ diversity Landais(44)/Landais et al.(45)QN* Female adult Fruit and vegetable intake Peltzer & Phaswana-Mafuya(52)QN* Mixed adult Food choice Mayen et al.(47)QN† Mixed adult Housing conditions (2) Dietary intake Steyn et al.(57)QN† Mixed adolescent and adult Meal skipping Onyiriuka et al.(51)QN* Female adolescent and adult Neighbourhoods (7) Household sanitation (1) Dietary diversity Becquey et al.(31)QN† and Savy et al.(53)QN* Mixed adolescent and adult; Female adult Neighbourhood SES (2) Dietary intake Pradeilles(62)MM‡ Mixed adolescent and adult Dietary intake/Snacking Feeley et al.(35)QN* Mixed adolescent Affordability (2) Food choice Boatemma et al.(19)QL and Sedibe et al.(26)/ Voorend et al.(27)QL Mixed adolescent and adult; Female adolescent Eating outside of home (2) Fruit and vegetable consumption Landais(43)/Landais et al.(45)QN* Female adult Dietary diversity Codjoe et al.(33)QN† Mixed adult and adolescent Where food is bought (1) Dietary intake Steyn et al.(57)QN† Mixed adolescent and adult Convenience (2) Dietary intake Sedibe et al.(26)QL/Voorend et al.(27)QL Female adolescent Fast-food intake Van Zyl et al.(58)QN* Mixed adult Availability (3) Fast-food intake Van Zyl et al.(58)QN* Mixed adult Fruit and vegetable intake Peltzer et al.(52)QN* Food choices Boatemma et al.(19)QL Mixed adolescent and adult School (2) School attendance (1) Dietary habits Sedibe et al.(26)/Voorend et al.(27) Female adolescent Dietary intake Aounallah-Skhiri et al.(30)QN† Mixed adolescent and adult Macro-level environment (9) Food marketing and media (3) Advertising (1) Dietary intake Legwegoh et al.(23)/Legwegoh et al.(23)QL Mixed adults Media (3) Fast-food intake Van Zyl et al.(58)QN* Mixed adult Dietary intake/Disordered eating Amenyah & Michels(29)QN* Mixed adolescent 2594 H O sei-K w asiet a l. Table 2 Continued Level Sub-level Factor (no. of studies) Dietary behaviour Evidence Population Food intake Waswa(59)QN* Female adult Ideal body size (2) Dietary intake/Disordered eating Amenyah & Michels(29)QN* Mixed adolescent Disordered eating Gitau et al.(38)QN‡ Male adolescent Societal and cultural norms/values (2) Religion (5) Fruit and vegetable intake Peltzer et al.(52)QN‡ Mixed adult Skipping meal Mogre et al.(49)QN* Mixed adult Dietary diversity Becquey et al.(31)QN†, Savy et al.(53)QN* and Codjoe et al.(33)QN‡ Mixed adolescent and adult; Female adult; Mixed adult and adolescent Food intake Waswa(59)QN* Female adult Cultural beliefs (4) Food intake Waswa(59)QN* Female adult Fattening practices Rguibi & Behalsen(25)QL Female adolescent and adult Dietary diversity Codjoe et al.(33)QN‡ Mixed adult and adolescent Dietary intake Legwegoh et al.(23)/ Legwegoh et al.(23)QL Mixed adults Food and beverage industry (4) Food prices (5) Dietary intake Legwegoh et al.(23)/Legwegoh et al.(23)QL and Sedibe et al.(26)/Voorend et al.(27)QL Mixed adults; Female adolescent Food choice Charlton et al.(61)MM Female adolescent and adult Food intake Waswa(59)QN* Female adult Unhealthy eating choice Draper et al.(22)QL Female adult Quality/freshness of food (1) Food choice Charlton et al.(61)QN* Female adolescent and adult Quick/easy to make foods (1) Food choice Charlton et al.(61)MM Female adolescent and adult Presentation and packaging (1) Food choice Charlton et al.(61)MM Female adolescent and adult MM, mixed methods; QN, quantitative study; QL, qualitative study. *Association not assessed/reported. †Significant association. ‡Association assessed but NS. D ietary b eh avio u rs in A frican fo o d en viro n m en ts 2595 while there were proportionally more lower income, non-educated and female subjects in the ‘traditional’ diet cluster(54). Other factors that were investigated were house- hold composition and family profession, but their relationship with dietary behaviours was NS. Adolescents with high SES adhered to more aspects of dietary guidelines than those of low SES in one quantitative study in Mauritius(36). Qualitative and quantitative studies have found that the importance of household SES was apparent across a range of SES indicators including household income or wealth(23,24,33,43,50,54,57), employment(32,43,45,56,57), land ownership(43) and financial insecurity(22). Educational level of individuals or parents was also found to play a role in dietary behaviours in several quantitative studies(30,33,37,43–46,52,54,56). Higher parental education level was associated with better dietary intake in four quantita- tive studies among adolescents(30,33,37,46), resulting in a higher modern dietary diversity score for adolescents in Tunisia,(30) higher household dietary diversity score in Ghana(33) and better healthy eating behaviours in Ghana(37) and Morocco(46) than those whose parents had average or low educational attainment. Dietary behaviours were associated with ethnicity in South African adults(38,52) and adolescents in South Africa(38) and Nigeria(51). Social environment Eleven factors emerged that related to the social environ- ment, eleven studies (both qualitative and quantitative) explored family influences(18–20,25,31,42,44,45,51,53,59,61) and four studies investigated friendship(19,26,27,52,59) (Fig. 2). Family. The social environment was particularly inves- tigated in adolescent studies; nine factors related to the family including marital status, with evidence coming from both qualitative and quantitative studies(25,31,42,44,53), what the rest of the family eats(19,61) and support in the household(19,31,53). Friends. Two qualitative studies examined the role of friendship on dietary habits and reported that friendship was associated with dietary habits in South African adoles- cents(26,27), stating that ‘participants often ate the same food as their friends’ and that shared food consumption between friends was common. In another qualitative study in Ghana, some participants mentioned friends as influencing food choice; foods recommended among peerswere usually proc- essed foods such as savoury snacks, soda and instant noo- dles(19). A quantitative study conducted among South African adults(52) did not find a significant association between social cohesion and fruit and vegetable consumption. Physical environment Fourteen studies (qualitative and quantitative) investigated the role of the physical environment on dietary behaviours, of which nine included adolescents(19,26,27,31,33,35,43,51,57,62). Twelve factors emerged in the physical food environment that influenced dietary behaviours. Seven of these were in the neighbourhood, four in the home environment and one in the school environment (Fig. 2). Convenience and availability of food were the most investigated factors in the physical environment. For instance, convenience was identified as a factor influencing fast-food intake with one quantitative study in South Africa Macro-level environment (n 9) Physical environment (n 12) Social environment (n 11) Individual & household (n 45) Sc ho ol (1 ) Lifestyle/behaviours (15) Demographic (9) Biological (9) Cognitions (12) Family (9) Friends (9 ) Home (4 ) Foo d m ark eti ng & m ed ia (3) So cie ta l & cu ltu ra l n or m s/ va lue s ( 2) Neighbourhood (7) Food & beverage industry (4) Fig. 2 A summary of factors (n 77) emerging from the included studies at different environmental levels 2596 H Osei-Kwasi et al. noting that 58·1 % of participants believed it influenced their food choices(58). Significant associations were found between housing conditions andwhere food is bought with dietary behaviours in South Africa(57). Two studies found an association between eating outside the home and dietary behaviours(33,44,45). Eating outside the home was associated with higher household dietary diversity in a quantitative study in Ghana, while food eaten at home was associated with lower household dietary diversity scores(33). The influence of school on dietary habits was investi- gated by only one qualitative study(26), which found that availability of food within schools, as well as sharing food within school, influenced dietary habits in South Africa. Macro-environment Nine factors emerged as influencing dietary behaviours that were on the macro-environment level. Three of these fac- tors related to the food marketing and media environment, two related to societal and cultural values and four related to the role of the food and beverage industry. Food prices were associated with fast-food intake in one South African quantitative study of young adults(58). Media and advertising were found to be associated with dietary intake of adults in both qualitative and quantitative studies in Botswana(23,24) and South Africa(58). About 49% of partici- pants in one study in South Africa stated that they believed media messages influenced their decision to purchase fast food(58). In a quantitative study conducted in South Africa, ideal body size was related to dietary behaviours(38). A quantitative study conducted in Ghana(29) identified that larger ideal body size was associated with a changed Eating Attitudes Tests 26 score. Lack of religious involvement was associated with dietary behaviour in one quantitative study of adults in South Africa(52), and one quantitative study of adults and adolescents in Ghana but was not associated with meal skipping or food choices in adults(49). Discussion This systematic mapping review mapped the factors influ- encing dietary behaviours of adolescents and adults in African urban food environments and identified areas for future research. Thirty-nine studies (forty-five records) were included in the final data synthesis. In total, seventy- seven factors influencing dietary behaviours were identified, with two-thirds at the individual level (45/77). Factors in the social (11/77), physical (12/77) and macro (9/77) environments were investigated less. The inclusion of two additional population groups (adult men and ado- lescents), in comparison to the original review, expands the generalisability of findings to the general population in urban Africa. Studies included in this review were from fifteen African countries, encompassing a range of low-, middle- and high-income African countries, reflecting the heterogeneity of urban African contexts. However, over half (22/39) were conducted in Ghana, Morocco or South Africa. This updates and extends a previous review, which was restricted to women(8). The current review updated and extended the demographic scope to include men and adolescents, as well as women. Findings synthesised from included studies indicate that the most investigated factors for adults and adolescents were the individual and household environment of the socio-ecological model as described by Story et al.(15). This finding is consistent with our previous review(8). Dietary behaviour was significantly associated with a range of individual and household environmental factors: house- hold income, educational level, employment, land owner- ship, socio-economic status (SES), ethnicity and financial insecurity. Low self-esteem, high levels of stress and lack of time were associated with unhealthy dietary behaviours. The focus on individual-level factors might be attributable to the fact that promoting healthy eating and preventing obesity have predominantly focused on changing behav- iour through interventions such as nutrition education, although such interventions alone have met with little success(63). Studies involving adolescents investigated factors in their social environments and were less focused on the role of the physical food environment on dietary behaviours, than for adults. This bias is unsurprising given that adoles- cence is defined as a transient formative period where many life patterns are learnt(64), particularly through the social environment. Shared food consumption between adolescent friends was common. Evidence from the wider literature outlines the social transmission of eating behav- iours, whereby a strong relationship exists between the social environment and amount or types of food eaten(65). This implies individuals tend to eat according to the usual social group they find themselves, either in terms of quan- tity or types of food eaten(66). Thus, understanding the role of the social environment among adults and adolescents as a modifiable factor influencing dietary behaviours offers an opportunity for developing nutrition interventions that har- ness social relationships. Convenience and availability of food were the most investigated factors in the physical environment. Significant associations were found between housing conditions and dietary intake, and where food was purchased and dietary intake. In contrast to the socio-ecological model(15), our map lacks evidence for the role of several factors in the physi- cal environment such as workplaces, schools (one study), supermarkets and convenience stores. In contrast to studies conducted in high-income coun- tries, factors influencing dietary behaviours in the macro- environment were rarely investigated in our review for adults or adolescents. Only food/drink advertising and reli- gion (adolescents only) and food prices were associated with unhealthy dietary behaviours, but many macro-level factors are known to influence diet, such as the political context, economic systems, health care systems and Dietary behaviours in African food environments 2597 behavioural regulations(67) that were not studied. One pos- sible explanationmay be that because Story’smodelwas gen- erated following research within high-income counties, some of the sub-levels may be less relevant to the African context. Factors that have been shown to influence dietary behaviours in high-income countries and were investigated in studies included in this review include food prices, social networks (friendship), time constraints and convenience. However, in high-income countries these factors are often reported in low-income groups(68). Another important finding from this review is the consistent association between SES and dietary behaviours as expected. SES is a global concern, and several studies have shown that lower SES restricts food choices, thus compelling the consumption of unhealthy foods(69–71). Of the thirty-nine studies identified, none specifically investigated adult men, as they were only included in mixed adult population studies. Adult men and women studies identified during this review showed similar types of factors associated with dietary behaviour across the dif- ferent environments, suggesting that similar interventions could be targeted at both men andwomen. However, dem- ographic factors were identified more in adult women than inmixed adult studies. This implies that the household is an important setting in which to reach women. The findings for women from this review went beyond that of the pre- vious review. Three more factors (stress, self-esteem and body satisfaction) were identified in the updated review. Furthermore, the expanded review identified evidence of more physical-level dietary factors including housing, living area, convenience and where food is bought. As the most common study methodology of included studies was cross-sectional, it is not possible to conclude on causality of the factors in different components of the food environment on dietary behaviours. Limitations regarding the use of the socio-ecological model(68) became evident during the review, as there is overlap between the different environmental levels for factors such as SES, spo- ken language and religious group. For instance, SES crosses multiple levels of the model, particularly in adolescents, as SES is often measured via physical or household/family- related factors. Another example is religious groups, which do not fit within the current sub-categories defined by Story’s ecological model(15). Although religion may broadly be classified as a factor in the macro-environment, religious groups may best fit in the social environment. While the socio-ecological model depicts reality as artificially separat- ing individual and social experiences(68), it is still a useful tool to communicate with policy makers and practitioners, unlike systems-based approaches, which are better at rep- resenting reality but rely on data on causality and mecha- nisms that are often lacking in cross-sectional and quantitative studies(72) and are harder to communicate to a non-expert audience. This review revealed considerable heterogeneity in the design of quantitative studies and the outcome measures used for assessing dietary behaviours. Future quantitative studies should ensure that outcome measures are clearly defined and report the direction of association between the factors examined and whether dietary behaviours are healthy or unhealthy. Quantitative studies should enhance the control of confounding variables to prevent them from introducing bias into the findings, and longitudinal quantitative studies are needed to be able to measure how factors influencing dietary behaviours are changing with the transformation of food environments. Qualitative studies are useful for understanding the complex rela- tionships between determinants of dietary behaviours. Qualitative studies need to have a rigorous design and improve the reporting of reflexivity by considering the impact of the role of researcher characteristics on the data collected to improve their quality. This review highlights the need for robust mixed meth- ods studies to gain a better understanding of the drivers of dietary behaviours in urban food environments in Africa. This is the first systematic mapping review that focuses on environmental factors of dietary behaviour for all pop- ulation groups in an urban African context. The nutrition transition has been associated with changes in dietary pat- terns globally with concomitant increases in obesity and NR-NCD, now among the leading causes of death(73). In African countries, NR-NCD risk is increasing at a faster rate and at a lower economic threshold than seen in high-income countries(74), hence the need for this review that identifies context specific factors that influence dietary behaviours. The recent focus on good health and well-being as part of the Sustainable Development Goals (SDG3)(75) also reflects this review’s aim to identify the underlying determinants of dietary behaviour in the urban African context to identify ave- nues for interventions. Conclusion The relatively small number of appropriate studies iden- tified, following an extensive literature search, indicates a significant gap in research into understanding of the factors influencing diets in food environments in urban Africa. Due to the increasing presence of multiple bur- dens of malnutrition in urban Africa, secondary to the nutrition transition(6), more studies should be directed at investigating how food environments are changing and driving this complex nutritional landscape. In par- ticular, future research could emphasise the investiga- tion of adult men and adolescents. The evidence from this review will contribute towards developing a socio- ecological framework of factors influencing dietary behaviours adapted to urban African food environments. Acknowledgements Acknowledgements: Emmanuel Cohen was supported by the South African DST/NRF Centre of Excellence in Human 2598 H Osei-Kwasi et al. development. Financial support: This research was funded by a Global Challenges Research Fund Foundation Award led by the MRC, and supported by AHRC, BBSRC, ESRC and NERC, with the aim of improving the health and prosperity of low- and middle-income countries. The TACLED (Transitions in African Cities Leveraging Evidence for Diet-related non-communicable diseases) project code is MR/P025153/1. The funders had no role in the design, analysis or writing of this article. Conflict of interest: There are no conflicts of interest. Authorship: All authors designed the review. A.M. conducted the searches and screening. H.O.-K. checked 10% of excluded records at title/abstract and full-text screening stages. A.M., F.G. and H.O.-K. extracted data and conducted analyses and quality assessment. M.W. checked data extraction and quality assessment. H.O.-K. drafted the manuscript. All authors reviewed draft versions of the manuscript and provided suggestions and critical feedback. All authors have made a significant contribution to this manuscript and approved the final manuscript. Ethics of human subject participation: Not applicable. Supplementary material For supplementary material accompanying this paper visit https://doi.org/10.1017/S1368980019005305 References 1. Holdsworth M & Landais E (2019) Urban food environments in Africa: implications for policy and research. Proc Nutr Soc 78, 513–525. 2. Popkin BM & Gordon-Larsen P (2006) The nutrition transi- tion: worldwide obesity dynamics and their determinants. Int J Obes 28, S2–S9. 3. Holmes MD, Dalal S, Sewram V et al. (2018) Consumption of processed food dietary patterns in four African populations. Public Health Nutr 21, 1529–1537. 4. Imamura F, Micha R, Khatibzadeh S et al. (2015) Dietary quality among men and women in 187 countries in 1990 and 2010: a systematic assessment. Lancet Glob Heal 3, e132–e142. 5. Kelly T, Yang W, Chen CS et al. (2008) Global burden of obesity in 2005 and projections to 2030. Int J Obes 32, 1431–1437. 6. Popkin BM (2004) The nutrition transition: an overview of world patterns of change. Nutr Rev 62, S140–S143. 7. de Onis M, Blössner M & Borghi E (2010) Global prevalence and trends of overweight and obesity among preschool chil- dren. Am J Clin Nutr 92, 1257–1264. 8. Gissing SC, Pradeilles R, Osei-Kwasi HA et al. (2017) Drivers of dietary behaviours in women living in urban Africa: a sys- tematic mapping review. Public Health Nutr 20, 2104–2113. 9. Grant MJ & Booth A (2009) A typology of reviews: an analysis of 14 review types and associated methodologies. Heal Info Libr J 26, 91–108. 10. Cooke A, Smith D & Booth A (2012) Beyond PICO: the SPIDER tool for qualitative evidence synthesis. Qual Health Res 22, 1435–1443. 11. Olshansky SJ & Ault AB (1986) The fourth stage of the epidemiologic transition: the age of delayed degenerative diseases. Milbank Q 64, 355–391. 12. Cooper C, Booth A, Britten N et al. (2017) A comparison of results of empirical studies of supplementary search tech- niques and recommendations in review methodology hand- books: a methodological review. Syst Rev 6, 1–16. 13. Kmet LM, Lee RC, Cook LS et al. (2004) Standard quality assessment criteria for evaluating primary research from a variety of fields. Alberta Herit Found Med Res AHFMR HTA Initiat 13, 1–28. 14. Booth A, Sutton A & Papaioannou D (2016) Systematic Approaches to a Successful Literature Review. London, UK: Sage. 15. Story M, Kaphingst KM, Robinson-O’Brien R et al. (2008) Creating healthy food and eating environments: policy and environmental approaches. Annu Rev Public Health 29, 253–272. 16. Moher D, Liberati A, Tetzlaff J et al. (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Br Med J 339, b2535. 17. Data.worldbank.org (2019) Low & middle income | Data. https://data.worldbank.org/income-level/low-and-middle- income (accessed November 2018). 18. Batnitzky A (2008) Obesity and household roles: gender and social class in Morocco. Sociol Heal Illn 30, 445–462. 19. Boatemaa S, Badasu DM & De-Graft Aikins A (2018) Food beliefs and practices in urban poor communities in Accra: implications for health interventions. BMC Public Health 18, 1–12. 20. Brown C, Shaibu S, Maruapula S et al. (2015) Perceptions and attitudes towards food choice in adolescents in Gaborone, Botswana. Appetite 95, 29–35. 21. Craveiro I, Alves D, Amado M et al. (2016) Determinants, health problems, and food insecurity in urban areas of the larg- est city inCapeVerde. Int J EnvironRes PublicHealth13, 1155– 1169. 22. Draper CE, Davidowitz KJ & Goedecke JH (2015) Perceptions relating to body size, weight loss andweight-loss interventions in black South African women: a qualitative study. Public Health Nutr 19, 548–556. 23. Legwegoh AF (2012) Urban food security in Gaborone, Botswana, p. 130. PhD Thesis, University of Guelph. 24. Legwegoh AF & Hovorka AJ (2016) Exploring food choices within the context of nutritional security in Gaborone, Botswana. Singap J Trop Geogr 37, 76–93. 25. Rguibi M & Belahsen R (2006) Fattening practices among Moroccan Saharawi women. East Mediterr Heal J 12, 619–624. 26. Sedibe MH, Feeley AB, Voorend C et al. (2014) Narratives of urban female adolescents in South Africa: dietary and physi- cal activity practices in an obesogenic environment. South Afr J Clin Nutr 27, 114–119. 27. Voorend CGN, Norris SA, Griffiths PL et al. (2013) ‘We eat together; Today she buys, tomorrow Iwill buy the food’: ado- lescent best friends’ food choices and dietary practices in Soweto, South Africa. Public Health Nutr 16, 559–567. 28. Agbozo F, Amardi-Mfoafo J, Dwase H et al. (2018) Nutrition knowledge, dietary patterns and anthropometric indices of older persons in four peri-urban communities in Ga West municipality, Ghana. Afr Health Sci 18, 743–755. 29. Amenyah SD & Michels N (2016) Role of diet, physical activ- ity and media in body size and dissatisfaction in Ghanaian adolescents. Ann Nutr Metab 67, 402. http://linker2.worldcat. org/?rft.institution_id=132347&spage=402&pkgName= customer.131416.13&issn=0250-6807&linkclass=to_article& jKey=1421-9697&provider=karger&date=2015-10&aulast= AmenyahþS.D.%3BþMichelsþN.&atitle=Roleþofþdiet% 2Cþphysicalþactivityþandþmedi (accessed November 2018). 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Aounallah-Skhiri H, Trasissac P, El-Ati JA et al. (2011) Nutrition transition among adolescents of a south- Mediterranean country: dietary patterns, association with socio-economic factors, overweight and blood pressure. A cross-sectional study in Tunisia. Nutr J 10, 1–17. 31. Becquey E, Savy M, Danel P et al. (2010) Dietary patterns of adults living in Ouagadougou and their association with overweight. Nutr J 9, 13. 32. Cisse-Egbuonye N, Ishdorj A, McKyer ELJ et al. (2017) Examining nutritional adequacy and dietary diversity among women in Niger. Matern Child Health J 21, 1408–1416. 33. Codjoe SNA, Okutu D & Abu M (2016) Urban household characteristics and dietary diversity. Food Nutr Bull 37, 202–218. 34. El Ansari W & Berg-Beckhoff G (2015) Nutritional correlates of perceived stress among university students in Egypt. Int J Environ Res Public Health 12, 14164–14176. 35. Feeley AB, Musenge E, Pettifor JM et al. (2013) Investigation into longitudinal dietary behaviours and household socio- economic indicators and their association with BMI Z-score and fatmass in South African adolescents: the Birth to Twenty (Bt20) cohort. Public Health Nutr 16, 693–703. 36. Fokeena WB & Jeewon R (2012) Is there an association between socioeconomic status and body mass index among adolescents in Mauritius? Sci World J 2012, 1–9. 37. Glozah FN & Pevalin DJ (2015) Perceived social support and parental education as determinants of adolescents’ physical activity and eating behaviour: a cross-sectional survey. Int J Adolesc Med Health 27, 253–259. 38. Gitau TM,Micklesfield LK, Pettifor JM et al. (2014) Eating atti- tudes, body image satisfaction and self-esteem of South African Black and White male adolescents and their percep- tion of female body silhouettes. J Child Adolesc Ment Health 26, 193–205. 39. Hattingh Z, Walsh CM, Veldman FJ et al. (2006) Macronutrient intake of HIV-seropositive women in Mangaung, South Africa. Nutr Res 26, 53–58. 40. Hattingh Z, Walsh C & Bester CJ (2011) Anthropometric profile of HIV-uninfected and HIV-infected women aged 25–44 years in Mangaung, Free State. South Afr Fam Pract 53, 474–480. 41. Hattingh Z, Le Roux M, Nel M et al. (2014) Assessment of the physical activity, body mass index and energy intake of HIV-uninfected and HIV-infected women in Mangaung, Free State province. South Afr Fam Pract 56, 196–200. 42. Jafri A, Jabari M & Dahhak M (2013) Obesity and its related factors among women from popular neighborhoods in Casablanca, Morocco. Ethn Dis 23, 369–373. 43. Kiboi W, Kimiywe J & Chege P (2017) Determinants of dietary diversity among pregnant women in Laikipia County, Kenya: a cross-sectional study. BMC Nutr 3, 1–8. 44. Landais E (2012) Fruit and vegetable consumption and its determinants amongst Moroccan women in the context of nutrition transition. PhD Thesis, University of Nottingham. 45. Landais E, Bour A, Gartner A et al. (2014) Socio-economic and behavioural determinants of fruit and vegetable intake in Moroccan women. Public Health Nutr 18, 809–816. 46. López PM, Anzid K, Cherkaoui M et al. (2012) Nutritional status of adolescents in the context of the Moroccan nutri- tional transition: the role of parental education. J Biosoc Sci 44, 481–494. 47. Mayén AL, Bovet P, Marti-Soler H et al. (2016) Socioeconomic differences in dietary patterns in an East African country: evi- dence from the Republic of Seychelles. PLoS One 11, 1–13. 48. Mbochi RW, Kuria E, Kimiywe J et al. (2012) Predictors of overweight and obesity in adult women in Nairobi Province, Kenya. BMC Public Health 12, 1. 49. Mogre V, Atibilla J & Kandoh B (2013) Association between breakfast skipping and adiposity status among civil servants in the Tamale metropolis. J Biomed Sci 2, 1–7. 50. Njelekela MA, Liu E, Mpembeni R et al. (2011) Socio-economic status, urbanization, and cardiometabolic risk factors among middle-aged adults in Tanzania. East Afr J Public Health 8, 216–223. 51. Onyiriuka AN, Umoru DD & Ibeawuchi AN (2013) Weight status and eating habits of adolescent Nigerian urban secon- dary school girls. South Afr J Child Heal 7, 108–112. 52. Peltzer K & Phaswana-Mafuya N (2012) Fruit and vegetable intake and associated factors in older adults in South Africa. Glob Health Action 5, e18668. 53. Savy M, Martin-Prével Y, Danel P et al. (2008) Are dietary diversity scores related to the socio-economic and anthropo- metric status of women living in an urban area in Burkina Faso? Public Health Nutr 11, 132–141. 54. Sodjinou R, Agueh V & Fayomi B (2008) Obesity and cardio- metabolic risk factors in urban adults of Benin: relationship with socio-economic status, urbanisation, and lifestyle pat- terns. BMC Public Health 8, 84–97. 55. Sodjinou R, Agueh V, Fayomi B et al. (2009) Dietary patterns of urban adults in Benin: relationship with overall diet quality and socio-demographic characteristics. Eur J Clin Nutr 63, 222–228. 56. Soualem A, Ahami AOT, Aboussaleh Y et al. (2012) Eating behavior of young adolescents in urban area in northwestern Morocco. Med J Nutr Metab 5, 157–161. 57. Steyn NP, Labadarios D & Nel JH (2011) Factors which influ- ence the consumption of street foods and fast foods in South Africa: a national survey. Nutr J 10, 1–10. 58. Van Zyl M, Steyn N & Marais M (2010) Characteristics and fac- tors influencing fast food intake of young adult consumers in Johannesburg, South Africa. South Afr J Clin Nutr 23, 124–130. 59. Waswa J (2011) Influence of perceived body image on nutrient intake and nutritional health of female students of Moi University. East Afr J Public Heal 8, 132–141. 60. Zeba AN, Delisle HF & Renier G (2014) Dietary patterns and physical inactivity, two contributing factors to the double burden of malnutrition among adults in Burkina Faso, West Africa. J Nutr Sci 3, 1–14. 61. Charlton K, Brewitt P & Bourne L (2004) Sources and cred- ibility of nutrition information among black urban South African women, with a focus on messages related to obesity. Public Health Nutr 7, 801–811. 62. Pradeilles R (2015) Neighbourhood and household socio- economic influences on diet and anthropometric status in urban South African adolescents. PhD Thesis, Loughborough University. 63. Delormier T, Frohlich K & Potvin L (2009) Food and eating as social practice-understanding eating patterns as social phe- nomena and implications for public health. Sociol Heal Illn 31, 215–228. 64. Rees J & ChristineM (1989) Nutritional influences on physical growth and behavior in adolescence. In Biology of Adolescent Behavior and Development, pp. 195–222 [G Adams, editor]. California: Sage. 65. Robinson E, Thomas J & Aveyard P (2014) What everyone else is eating: a systematic review and meta-analysis of the effect of informational eating norms on eating behavior. J Acad Nutr Diet 114, 414–429. 66. Powell K, Wilcox J & Clonan A (2015) The role of social net- works in the development of overweight and obesity among adults: a scoping review. BMC Public Health 15, 996–1009. 67. Sleddens E, Kroeze W & Kohl L (2015) Correlates of dietary behavior in adults: an umbrella review. Nutr Rev 73, 477–499. 68. Osei-Kwasi H, Nicolaou M & Powell K (2016) Systematic mapping review of the factors influencing dietary behaviour in ethnic minority groups living in Europe: a DEDIPAC study. Int J Behav Nutr Phys Act 13, 85–102. 69. Powell LM, Zhao Z & Wang Y (2009) Food prices and fruit and vegetable consumption among young American adults. Health Place 15, 1064–1070. 2600 H Osei-Kwasi et al. 70. Roberts K, Cavill N, Hancock C et al. (2013) Social and Economic Inequalities in Diet and Physical Activity. London: Public Health England. 71. Vogel C, Ntani G, Inskip H et al. (2016) Education and the relationship between supermarket environment and diet. Am J Prev Med 51, e27–e34. 72. Holdsworth M, Nicolaou M & Langoien L (2017) Developing a systems-based framework of the factors influencing dietary and physical activity behaviours in ethnic minority popula- tions living in Europe: a DEDIPAC study. Int J Behav Nutr Phys Act 14, 154–169. 73. Institute for Health Metrics and Evaluation (2019) Global Burden of Disease (GBD). http://www.healthdata.org/gbd (accessed October 2019). 74. Popkin BM (2002) Part II. What is unique about the experience in lower- and middle-income less-industrialised countries compared with the very-high-income industrial- ised countries? Public Health Nutr 5, 205–214. 75. Sustainabledevelopment.un.org (2019) Goal 3 Sustainable Development Knowledge Platform. https://sustainable development.un.org/sdg3 (accessed October 2019). Dietary behaviours in African food environments 2601 http://www.healthdata.org/gbd https://sustainabledevelopment.un.org/sdg3 https://sustainabledevelopment.un.org/sdg3 Factors influencing dietary behaviours in urban food environments in Africa: a systematic mapping review Methods Inclusion and exclusion criteria Search strategy Study selection Quality assessment Data extraction Data synthesis Results Search results Description of included studies Quality assessment Factors influencing diet or dietary behaviour in urban Africa Dietary factors in adult women, adult men and adolescents Individual level Cognitions Cognitions Lifestyle/behaviours Biological Demographic Social environment Family Friends Physical environment Macro-environment Discussion Conclusion Acknowledgements Supplementary material References