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Urbanisation in Ghana could be negatively impacting the state of food security, especially in economically vulnerable groups. Food supply, safety, and quality are all aspects of food security which could be impacted.
Study | Region | Design | Population/Sample | Methods (Data Collection) | Key Findings | Evidence Mapped with the Food Security Domains |
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King et al., 2000) [22] | Greater Accra | Cross sectional Survey | Chop bar operators (n = 160) | Observation and interviews | Street food vendors not compliant to safety standards. About 66% of proprietors surveyed did not obtain their meat supply from an approved source: suggestive of food safety issue | Food safety and quality |
Kroll et al., 2019) [18] | Ashanti | Cross sectional Survey | Urban households (n = 309) | Interviews using food frequency questionnaires | Widespread prevalence of low-protection diets, with a fairly even distribution of low risk and high risk diets. | Food access |
Abass et al. 2016) [17] | Ashanti | Cross sectional Survey | Vegetable farms (n = 18) | Analysis of randomly selected vegetable samples, followed by interviews with consumers | Vegetable cultivated highly contaminated with feacal microorganisms (fecal coliforms, E coli). Level of fecal coliforms is function of distance to a river. Influencers of accessing food from the street were cost saving, convenience and eating on credit. | Food access, safety and quality |
Hiamey, et al., 2013) [13] | Western | Cross sectional Survey | Random consumers (n = 220) | Interviews using stanardard structured questionnaires | Street food consumed frequently; particularly carbohydrate-rich foods. Affordability, convenience and access by credit were important drivers | Food access and utilisation |
Karg et al., 2016) [21] | Northern | Cross sectional Survey | Food flow records (n = 14,000) | Traffic surveys of food flows on access roads | Food supply to urban areas depends highly on food type and seasonality and arrive from multiple sources. Small-scale suppliers bring in most urban food. | Food supply |
Mensah, et al. 2017) [20] | Volta | Cross sectional Survey | Hotel Caterers (n = 199) | Interviews using self-administered questionnaires. | Influencers of food access are cleanliness of the place, sanitation and hygiene, cleanliness of staff, quality of food, service staff behaviour. Quantity and price were the least important factors. | Food access |
Pobee et al., 2020) [50] | Eastern | Cross sectional Survey | Household (women, n = 95) | Interviews using the 18-item Household Food Insecurity Access Scale (HFIAS) | Food insecurity was reported prevalent among 23% of the households. Compared to married women, more unmarried women were food insecure | Perceived food in security |
Sackey et al., 2018) [45] | G. Accra | Cross sectional Survey | Households (Men/women, n = 152) | Food insecurity was measured using the validated Household Food Insecurity Access Scale (HFIAS) | Consumption patterns of individual food groups did not change over time except within the meat and fish groups. Meat consumption decreased from 30% (baseline) to 23% (3-months) and increased to 43% (6-month visit). Fish consumption increased from 83% (baseline) to 92% (3-months) and decreased to 81% (6-months). | Food utilisation and perceieved food insecurity |
Tuholske et al., 2020) [49] | G. Accra | Cross sectional Survey | Household consumers (Men/women, n = 668) | Household Food Insecurity was measured using the HFIAS, alongside Household Food Insecurity Access Prevalence (HFIAP) and the Food Consumption Score. | Food insecurity was prevalent among 70% of households. Only one household reported sourcing food from modern supermarkets and fewer than 3% produce food for consumption through gardening, farming, or fishing. | Perceieved food insecurity |
Gyasi, et al. 2020) [48] | N.S. | Cross sectional Survey | Household consumers (focusing on adults aged >50 yrs) (n = 1219) | Scondary data drawn from the AgeHeaPsyWel-HeaSeeB Study dataset | Skipping breakfast reported as severe food insecurity issue among people 50–64 years. 36% of participants reported being hungry because there was not food at home. | Food utilisation and perceieved food insecurity |
Nagai et al., 2009) [16] | G. Accra | Cross sectional Survey | Companies, Retailers, Millers consumers, (n = 73) | Interviews using structured Questionnaires | Reason for the lack of availability of weanimix to mothers from lower-income families include low awareness of the product. Processing and retail price also margins wean mix availability. | Food access and supply |
Codjoe, et al. 2016) [14] | G. Accra | Cross sectional Survey | Urban poor households (men and women) (n = 452) | Secondary data drawn from second round of the Regional Institute for Population Studies (RIPS) EDULINK urban poverty and health study | Households consuming seven different food groups within a week, with a mean diversity score of 6.8. Fruits, milk and dietary produce had low dietary diversity due to high prices, lack of nutritional knowledge (taste and preference). | Food access, and utilisation |
Dake et al., 2016) [15] | G. Accra | Cross sectional Survey | Urban poor households (females) (N.S) | Data on the local food environment collected and analysed using geographic positioning system (GPS) technology | The local food environment (convenience stores, abundance of out-of-home cooked foods and limited fruits and vegetables options) suggestive of an obesogenic food environment. | Food access and utilisation |
Darko, et al. 2016) [39] | Ashanti | Cross sectional Survey | Raw food samples (n = 40) | Interviews using semi-structured questionnaire | Foods tested were above the acceptable levels and could be sources of food borne pathogens, attributed to poor food hygiene and inadequate processing. | Food Safety and quality |
Kortei et al., 2020) [43] | Western | Cross sectional Survey | Fish samples (n = 16) | Analysis of mandomly purchased fish samples | All the examined fish species had toxic mineral concentrations within the E.U quality standard limits except for Mercury (Hg) which exceeded the set limits of WHO. | Food Safety and quality |
Kudah, et al. 2018) [44] | Eastern | Cross sectional Survey | Vegetable salad sample (n = 360) | Analysis of randomly purchased fresh vegetables samples | 58% of the food tested (vegetables, spring onion and tomatoes) were found to be contaminated with at least one type of parasite. | Food Safety and quality |
Kunadu et al., 2019) [52] | G. Accra | Cross sectional Survey | Consumers (n = 176), farmers (n = 21) & diary product (n = 140) | Analysis of randomly purchased samples of diary milk and milk products, followed by questionnaires interviews with consumers | Fecal coliforms in dairy products, such as brukina, wagashi, and yogurt exceeded the specified limit of 10 CFU/mL, while the prevalence of E. coli and K. pneumoniae were 70 and 65%, respectively. Generally, respondents perceived indigenous dairy as unsafe. | Food Safety and quality |
Abubakari et al., 2015) [36] | Ashanti | Cross sectional Survey | Cooked food sample (n = 170) | Analysis of purchased ready prepared fruit-salad samples | Ready to be eaten salad foods was a food concern. Three samples tested showed positive to E. coli O157:H7. Mean logcfu/g of total coliforms and E. coli were found to be 6.35 ± 0.09 and 5.1 ± 0.1. | Food Safety and quality |
Adam, et al. 2014) [19] | Central | Cross sectional Survey | University students (n = 1106) | Interviews using structured questionnaires | Students’ concern on food temperature as a food safety issue. Clean and hygienic eating tables as a key food safety concern and predictor of choice of eating place. | Food access, Food Safety and quality |
Addo et al., 2007) [23] | G. Accra | Cross sectional Survey | Cooked food sample (n = 10) | Analysis of randomly purchased cooked food samples | Food samples contaminated with Bacteria. 35% of food tested were positive for other coliform bacteria. Almost all (70 %) of the swabs positive for coliforms were from either a cutting board or a working surface | Food Safety and quality |
Adzitey, et al. 2020) [41] | Northern | Cross sectional Survey | Food sample (n = 200) | Analysis of randomly purchased food and diary milk and milk products | Milk products and other food samples tested were found to be contaminated with Salmonella enterica. | Food Safety and quality |
(Adzitey, et al., 2018) [24] | G. Accra | Cross sectional Survey | Meat sample (n = 32) | Analysis of selected beef and other food samples | Heavy metals were found present in varying concentrations in foods sample, but were below the maximum limit, and so less harmful for consumption | Food Safety and quality |
Akoto et al., 2015) [37] | Ashanti | Cross sectional Survey | Vegetable sample (n = 20) | Fresh vegetable samples were randomly purchased and analysed using standard methods | Varying degrees of contamination found in Vegetables. Overall risk index for combined pesticides due to consumption of all vegetables was >1 which pose as a health risk. | Food Safety and quality |
Egbon 2013) [25] | G. Accra | Cross sectional Survey | Food sellers (n = 148) | Fresh legumes samples were randomly purchased and analysed using standard methods. | Cowpea was found to be infested with callosobruchus macculatus and sitophilus oryzae. | Food Safety and quality |
Feglo 2012) [40] | Ashanti | Cross sectional Survey | Raw food samples (n = 6) | Raw foods were selected randomly and analysed using standard methods | High levels of bacterial contamination at varying degrees detected in food types tested (higher levels of contamination than acceptable reference) | Food Safety and quality |
Ayroe et al., 2016) [38] | Ashanti | Cross sectional Survey | Consumers (n = 200), and meat samples (n = 105) | Analysis of meat samples, followed by questionnaire interviews with meat sellers sampled randonly | High proportion of offals sold in Kumasi contained lesions (abscesses, metazoan parasites and granuloma). | Food Safety and quality |
Fosu et al., 2017) [26] | G. Accra | Cross sectional Survey | Fruits & vegetables samples (n = 3483) | Fresh fruits and vegetable sampled randomly and analysed using standard methods | Pesticides residues were detected fruits and vegetables tested. Samples tested contained levels above the MRL levels. | Food Safety and quality |
(Nyarko, et al., 2011) [27] | G. Accra | Cross sectional Survey | Fish sample (smoked salmon) (N.S) | Smoked fish samples randomly selected and analysed using standard methods | Microbial counts for samples collected from the smoking sites were within acceptable limits of Ghana Standard Board (GSB), while those from marketing centres were not. | Food Safety and quality |
(Nyarko, et al., 2011) [42] | Central | Cross sectional Survey | Food sample (tiger nuts) (n = 24) | Fresh fruits samples were randomly selected and analysed using standard methods | Tiger nuts (non-sterile) sold in markets in cape coast are contaminated with high bacteria loads that are implicated in both food spoilage and food-borne diseases. | Food Safety and quality |
(Obeng et al., 2018) [28] | G. Accra | Cross sectional Survey | Vegetable sample (tomatoes) (n = 120) | Raw vegetables samples were randomly selected and analysed using standard methods. | Varying levels of antibiotic resistance bacteria found in tomatoes sold at various markets centres in Ghana. | Food Safety and quality |
(Omari, 2018) [53] | G. Accra | Cross sectional Survey | Fast foods sellers (n = 425) | Interviews using structured questionnaires | Respondents expressed concerns about food hazards and other food safety issues: pesticide residue in vegetables, excessive use of artificial flavour enhancers and colouring substances, bacterial contamination, leaked harmful substances from plastic packages and general unhygienic conditions under which food is prepared and sold. | Food Safety and quality |
(Omari, 2017) [54] | G. Accra | Cross sectional Survey | Fast foods consumers (n = 425) | Interviews using structured questionnaires | Consumer concerns about safety of fast foods. Consumers’ perception of safety of fast food influenced by components of trust (institutional competence and openness). | Food Safety and quality |
(Mahami 2014) [55] | G. Accra | Cross sectional Survey | Probiotic yoghourts samples (n = 20) | Milk and milk products were sampled randomly and analysed using standard methods | About a quarter of imported and local yoghurt samples were below the recommended standard of ≥ 106 CFU/ml. PH values of samples were within the recommended standard of ≤4.5. | Food Safety and quality |
(Mensah, 2014) [56] | Ashanti | Cross sectional Survey | Consumers (n = 200) | Interviews using structured questionnaires | Consumers concerns about safety and quality of leafy vegetables in the retail market due to excessive use of chemicals and contaminated water for vegetables production. Further concerns expressed regarding mishandling of leafy vegetables in the retail market, which was viewed as a health risk. | Food Safety and quality |
(Mensah et al., 2002) [29] | G. Accra | Cross sectional Survey | Food samples (n = 117) | Food samples were selected randomly and analysed using standard methods | Mesophilic bacteria were detected in 356 foods (69.7%): 28 contained Bacillus cereus (5.5%), 163 contained Staphylococcus aureus (31.9%) and 172 contained Enterobacteriaceae (33.7%). Most of the foods sample (salads, macaroni, fufu, omo tuo and red pepper) were contaminated with Mesophilic bacteria (Bacillus cereus, Staphylococcus aureus and Enterobacteriaceae) above acceptable levels. | Food Safety and quality |
(Otoo 2013) [57] | B. Ahafo | Cross sectional Survey | Mothers/caregivers (n = 246) | Interviews using food frequency questionnaires | Children consumed from at least four food groups and Orphans had a higher dietary diversity than non-orphans did. | Food utilisation |
(Pesewu et al., 2014) [30] | G. Accra | Cross sectional Survey | Vegetable samples (N.S) | Vegetables were sampled randomly and analysed using standard methods | Food sample tested have high bacterial contamination. | Food Safety and quality |
(Sinayobye 2011) [31] | G. Accra | Cross sectional Survey | Food mill operators (n = 21) and food samples (n = 36) | Food samples were found to be contaminated with microorganisms. The contamination load increased with the milling time | Food Safety and quality | |
(Soriyi, 2008) [32] | G. Accra | Cross sectional Survey | Beef sample (n = 128) | Meat samples were selected randomly and analysed using standard methods | Beef samples were contaminated with Aerobic mesophiles (189-23000 cfu/g), Staphylococcus aureus (22–59 cfu/g), Bacillus cereus (17–41 cfu/g), Clostridium perfringens (21–48 cfu/g) and Escherichia coli (31–2200 cfu/g). | Food Safety and quality |
(Quansah et al., 2018) [33] | G. Accra | Cross sectional Survey | Vegetable sample (n = 50) | Vegetables were sampled randomly and analysed using standard methods | Food sample tested positive for enterococci and fecal coliform. | Food Safety and quality |
(Yeboah-Manu et al., 2010) [34] | G. Accra | Cross sectional Survey | Food samples (n = 27) | Foods were sampled randomly and analysed using standard methods. | Slightly above half of the food tested had E. coli values within the acceptable limits whiles 40.7% were outside the limit—unsafe for consumption. | Food Safety and quality |
(Kortei et al. 2021) [58] | Multiple urban settings | Cross sectional Survey | Food sample (n = 80) |
Raw foods sampls selected randomly and analysed using standard methods. | 61.25 % of the food sample tested positive for AFB1 and ranged from 0.38 ± 0.04–230.21 ± 22.14 μg/kg, of which 41.25 % of the samples were above the Europeam amd Ghana food safety standards limits. | Food Safety and quality |
Olu-Taiwo et al. 2021) [35] | G. Accra | Cross sectional Survey | Meat samples (from n = 6 open markets) | Beef samples selected randomly and analysed using standard methods. | Bacterial contamination of retailed beef sold in different Accra markets. Beef samples mostly contaminated with Staphylococcus spp. (34%), Klebsiella oxytoca (17%), Enterobacter spp. (15%), and Proteus vulgaris (3%). | Food Safety and quality |
(Saaka et al. 2021) [46] | Northern region | Cross sectional Survey | Women (n = 423) | 24hr dietary recall of dietary intake/food consumption. | Results showed that women of low household wealth index were 48% less likely meet the minimum dietary diversity for women (MDD-W), whiles those from households of poor food insecurity were 88 % less likely to achieve the MDD-W. | Food utilisation |
(Bannor et al. 2020) [47] | G. Accra, Bono, Ahafo and Bono East | Cross sectional Survey | Farmers (n = 400) | Food security status of urban households was assessed using the HFIA Scale and Food Insecurity Experience Scale (HFIES) | Households food insecure in Ghana were reportely mildly, with an average food security score of 4.05 for each household | Perceived food security |