Consumer preferences, and willingness to pay for safe pork products in rural Kenya

Designing interventions to support the safe development of rapidly growing livestock value chains in sub-Saharan Africa requires a clear understanding of consumer demands. This study aimed to determine purchase patterns, consumers' preferences, and willingness to pay for safe pork attributes; specifically, the presence of a veterinary inspection stamp and the cleanliness of the butchery.A discrete choice experiment-based survey was used to investigate the purchasing behavior of 401 pork consumers: 253 buying raw pork for household consumption, and 148 buying cooked pork for out-of-home consumption. The study findings indicate that the average quantity of pork purchased by consumers was approximately 0.4 Kg per transaction, with the majority of consumers making several purchases per week.The average price per Kg of pork was KES 310 (Approx. 2.60 USD) at the time of the study. Data from the choice experiment showed that consumers were willing to pay a price premium of KES 245 (Approx. 2.1 USD) and KES 164 (Approx. 1.4 USD) per Kg for evidence of better veterinary meat inspection and higher butchery hygiene respectively; further, these were the two most important attributes they considered while making a pork purchase decision.These findings highlight the potential to leverage consumers' willingness to pay to improve the food safety within pork value chains in this context. Investing to increase consumer awareness on food safety issues should be considered to generate an effective market demand, especially in rural areas with relatively lower literacy levels

Prevalence of gross lesions and handling practices in pigs and their association with pork quality, Kiambu, Kenya.

Pre-slaughter handling of pigs has been documented to affect the quality of meat though no studies have investigated this relationship in the Kenyan context. This study aimed to determine the prevalence of gross lesions and practices related to sub-optimal welfare in pigs presented for slaughter while analyzing the relationship between occurrence of these lesions and meat quality. A cross-sectional study was conducted at a medium scale, non-integrated pig abattoir supplying to the Nairobi market, with a capacity to slaughter approximately 40 pigs a day. Data on welfare-associated lesions and handling practices were obtained from 529 pig carcasses and traders respectively. 387 pork samples were collected, and their quality evaluated by measuring their pH, meat color and drip loss. These three parameters were used to classify pork into four recognized categories namely: Red, Firm, Non-exudative (RFN), Pale Soft Exudative (PSE), Dark Firm Dry (DFD) and Red Soft Exudative (RSE). Almost all pigs were inefficiently stunned as evidenced by the presence of consciousness post-stunning. The majority of pigs (82.97%) having one or more welfare-associated gross lesions. Other animal welfare malpractices observed were high loading density and inadequate rest periods between transport and slaughter. A quarter of the pork samples were of sub-optimal quality including: RSE (11.36%), PSE (2.58%) and DFD (2.58%). Multinomial logistic regression revealed that pork originating from pigs transported at a high loading density had increased odds of being classified as DFD (OR 13.41, 95% CI 2.59-69.46). The findings indicate the need to educate stakeholders in the pork value chains on improved pig handling before and during slaughter to enhance pig welfare pre-slaughter and pork quality post-slaughter. Animal welfare legislation enforcement and implementation was observed to be insufficient. There is a need to educate key stakeholders on its importance of being put into practice both from economic and welfare perspectives

Challenges of camel production in Samburu District, Kenya

Abstract The objective of the study was to identify the challenges to camel production in Kenya's Samburu district. The data was collected through administration of structured and semi-structured questionnaire to a representative sample of the pastoralist household heads. The major causes of camel loss in the district were identified as predation (50.9%), drought (28.7%) and camel diseases (20.4%). Severe drought was reported to have occurred in the years; 1984 (12.4%), 1995 (9%), 2005 (42.1%), and 2006 (37.6%), and the livestock species most affected by the drought were cattle (98.1%), sheep (63.9%), donkeys (57.5%), goats (50.8%) and camels (31.2%). Water was reported to be inadequate in the district by 54.6% and 62.1% of the respondents respectively for livestock and human use. Herdsmen reported watering their camels from; rivers (24.6%), dry river beds (40%) and spring (7.7%). The livestock grazing area was reported to be getting smaller (45.7%), overgrazed (21.7%), and destroyed (13%), while only 13% believed that the grazing area had increased. Amongst the pastoralist who responded to the question on their source of income, 78.8% had no alternative source of income apart from livestock keeping. Conclusion: More resources should be allocated by the governments for improvement of camel production and the carrying capacity in pastoral production systems needs to be re-evaluated to ensure optimal productivity

Identification of production challenges and benefits using value chain mapping of egg food systems in Nairobi, Kenya

Commercial layer and indigenous chicken farming in Nairobi and associated activities in the egg value chains are a source of livelihood for urban families. A value chain mapping framework was used to describe types of inputs and outputs from chicken farms, challenges faced by producers and their disease control strategies. Commercial layer farms were defined as farms keeping exotic breeds of chicken, whereas indigenous chicken farms kept different cross breeds of indigenous chicken. Four focus group discussions were held with producers of these chickens in peri-urban area: Dagoretti, and one informal settlement: Kibera. Qualitative data were collected on interactions between farmers, sources of farm inputs and buyers of poultry products, simple ranking of production challenges, farmers' perception on diseases affecting chicken and strategies for management of sick chicken and waste products. Value chain profiles were drawn showing sources of inputs and channels for distribution of chicken products. Production challenges and chicken disease management strategies were presented as qualitative summaries. Commercial layer farms in Dagoretti kept an average of 250 chickens (range 50–500); while flock sizes in Kibera were 12 chickens (range 5–20). Farms keeping indigenous chicken had an average of 23 chickens (range 8–40) in Dagoretti, and 10 chickens (range 5–16) in Kibera. Commercial layer farms in Dagoretti obtained chicks from distributors of commercial hatcheries, but farms in Kibera obtained chicks from hawkers who in turn sourced them from distributors of commercial hatcheries. Indigenous chicken farms from Dagoretti relied on natural hatching of fertilised eggs, but indigenous chicken farms in Kibera obtained chicks from their social connection with communities living in rural areas. Outlets for eggs from commercial layer farms included local shops, brokers, restaurants and hawkers, while eggs from indigenous chicken farms were sold to neighbours and restaurants. Sieved chicken manure from Dagoretti area was fed to dairy cattle; whereas non-sieved manure was used as fertilizer on crops. Production challenges included poor feed quality, lack of space for expansion, insecurity, occurrence of diseases and lack of sources of information on chicken management. In Kibera, sick and dead chickens were slaughtered and consumed by households; this practice was not reported in Dagoretti. The chicken layer systems contribute to food security of urban households, yet they have vulnerabilities and deficiencies with regard to disease management and food safety that need to be addressed with support on research and extension

Investigation of the governance structure of Nairobi dairy value chain and its influence on food safety

The dairy value chain of Nairobi is comprised, in its majority, of small-scale independent enterprises that operate within a complex interlinked system. In this complexity, the coordination and power structures of the system may have major influences on the management of dairy food safety. Therefore, the aim of this study was to investigate the governance and challenges issues faced by stakeholders throughout the Nairobi dairy value chain and assess their potential implications on food safety. Qualitative data was collected through focus group discussions and key informant interviews based on a dairy value chain mapping framework previously developed. Thematic analysis enabled identification of governance themes, key challenges and their implication on food safety. Themes were organized depending on their association with farmers (informal settlement or peri-urban), dairy cooperatives, dairy traders, processing companies, retailers or government officers. The identified governance themes included: i) weak linkage between government and farmers, ii) inadequate compliance with government regulations by traders and retailers, iii) emphasis on business licenses and permits for revenue rather than for food safety, iv) multiple licensing resulting in high business cost and lack of compliance, v) fragmented regulation, vi) unfair competition and vii) sanctions that do not always result in compliance. The key challenges identified included, amongst others: i) inadequate farmer support, ii) harassment of traders and retailers and iii) high business costs by traders, retailers, dairy cooperatives and large processors. The implication of governance and challenges of food safety were, amongst others: i) inadequate extension services, ii) insufficient cold chain, iii) delivery of adulterated and low milk quality to bulking centres, iv) inadequate food safety training and v) lack of policies for management of waste milk. The range of issues highlighted are based on stakeholders’ perceptions and reflects the complexity of the relationships between them. Many of the governance themes demonstrate the linkages that are both beneficial or confrontational between the formal and informal sectors, and between industry and regulatory authorities, with possible direct food safety consequences. Findings obtained provide indications to decision-makers of potential governance areas that could help improve efficiency and food safety along the dairy value chain

Acute Poisonings at a Regional Referral Hospital in Western Kenya

The emergency department (ED) of the Jaramogi Oginga Odinga Teaching and Referral Hospital (JOOTRH) handles many cases of poisoning. However, there is scant information on the factors, agents, and outcomes of poisoning at the hospital. The aim of this work was to determine the factors, agents, and outcomes of poisoning at JOOTRH. Records of patients who presented to JOOTRH with symptoms of poisoning between January 2011 and December 2016 were retrieved. Data on age, gender, offending agents, time, and season of exposure were collected. Information on the route of exposure, motive, and clinical symptoms of poisoning was also included. Other information included the laboratory evaluation, first aid measures, period of hospitalization, and outcome of poisoning. Mean, standard deviation, frequencies and bar graphs were used to describe the demographic factors of the study population. Multivariate logistic regression was used to determine the strength of association between risk factors and outcome of poisoning among patients. The level of significance for inferential analysis was set at 5%. There were 385 cases of poisoning: 57.9% (223/385) were male, 31.9% (123/385) were 13–24 years of age, and 83.9% (323/385) of exposures were in Kisumu County. The peak time of exposure was 6:00–00:00, and 23.6% (91/385) presented 1–4 h after exposure. About 62.9% (242/385) of the cases were due to accidental poisoning. Snakebites and organophosphates (OPPs) contributed to 33.0% (127/385) and 22.1% (85/385) of all cases, respectively. About 62.1% (239/385) of exposures were oral, and 63.9% (246/385) of all cases occurred in the rainy season. Additionally, 49.2% (60/122) of intentional poisoning was due to family disputes, and 16.1% (10/62) of pre-hospital first aid involved the use of tourniquets and herbal medicine. About 28.6% (110/385) of the victims were subjected to laboratory evaluation and 83.9% (323/385) were hospitalized for between 1–5 days. Other results indicated that 80.0% (308/385) responded well to therapy, while 7.3% (28/385) died, 68% (19/28) of whom were male. Furthermore, 39.3% (11/28) of the deaths were related to OPPs. Our findings suggest that the earlier the victims of poisoning get to the hospital, the more likely they are to survive after treatment is initiated. Similarly, victims of poisoning due to parental negligence are more likely to survive after treatment compared to other causes of poisoning, including family disputes, love affairs, snakebites, and psychiatric disorders. The management of JOOTRH should consider allocating resources to support the development of poison management and control

Developing and validating a rapid assessment tool for small ruminant reproduction and production in pastoralist flocks in Kajiado, Kenya

The collection of production performance data in small ruminants pastoralists flocks is essential to evaluate their efficiency and assess how different challenges, such as diseases, droughts or changes in land use, affect their sustainability. Although different methodologies exist, capturing these data is difficult, particularly in nomadic pastoral flocks. In this study, a method for rapid assessment of flock production performance based on farmer recall was designed, implemented and tested.Through literature review and consultation with pastoralists and key informants, a questionnaire was developed to capture small ruminant flock data disaggregated by age (≤2 years old and >2 years old), species and sex. Data on flock dynamics and on reproduction parameters were collected for a period of 12 months. A survey of 130 pastoralists with medium to large flocks was then conducted in Kajiado County (Kenya). Values were calculated for 12 reproduction performance indicators and 7 additional production performance indicators. In addition, a flock efficiency indicator (FEI) is proposed that classifies mixed flocks (i.e., with sheep and goats) into low, medium or high efficiency.Results showed that in flocks with low efficiency, the median value for net fecundity rate was 0.43 lambs/ewe (range 0.08–1.00) and 0.41 kids/doe (range 0.07–0.73), and the median production rate was 6% (range [−47%] to 20%) for sheep and 11% (range [−38%] to 0.21%) for goats. In flocks with high efficiency the median net fecundity rate was 0.77 lambs/ewe (range 0.48–2.73) and 0.88 kids/doe (range 0.49–1.80), and the median production rate was 25% (range 11–47) for sheep and 28% (range 15–46) for goats. Sixty-two (47.7%) of the pastoralists surveyed reported usually buying animals into their flocks, and, consequently were considered as ‘pastoralists and traders’. Their flocks had significantly lower FEI scores (median = 7.5, interquartile range [IQR] 6–9), compared with “pastoralists only” flocks (median = 8, IQR 6–10, Kruskal–Wallis rank sum test, p-value <0.001).Since this method is based on pastoralist recall, values obtained should be considered as approximations. Nonetheless, the proposed assessment tool can be used by individuals with low resources or recording capacity, and in large scale programmes to monitor pastoralist flock dynamics, set-up benchmarking programmes, estimate the impact of diseases and shocks, identify those flocks which are most vulnerable to these shocks and evaluate the effectiveness of policies and interventions on herd performance

Assessment of Milk Quality and Food Safety Challenges in the Complex Nairobi Dairy Value Chain

Food networks present varying food safety concerns because of the complexity of interactions, production, and handling practices. We investigated total bacteria counts (TBCs) and total coliform counts (TCCs) in various nodes of a Nairobi dairy value chain and identified practices that influence food safety. A value chain analysis framework facilitated qualitative data collection through 23 key informant interviews and 20 focus group discussions. Content thematic analysis identified food safety challenges. Cow milk products (N = 290) were collected from farms (N = 63), collection centers (N = 5), shops/kiosks (N = 37), milk bars (N = 17), roadside vendors (N = 14), restaurants (N = 3), milk vending machines (N = 2), mobile traders (N = 2) and a supermarket (N = 1). Mean values of colony-forming units for TBC and TCC were referenced to East African Standards (EAS). Logistic regression analysis assessed differences in milk acceptability based on EAS. The raw milk from farms and collection centers was relatively within acceptable EAS limits in terms of TBC (3.5 × 105 and 1.4 × 106 respectively) but TCC in the milk from farms was 3 times higher than EAS limits (1.5 × 105). Compared to farms, the odds ratio of milk acceptability based on TBC was lower on milk bars (0.02), restaurants (0.02), roadside vendors (0.03), shops/kiosks (0.07), and supermarkets (0.17). For TCC, the odds that milk samples from collection centers, milk bars, restaurants, roadside vendors, and shops/kiosks were acceptable was less than the odds of samples collected from farms (0.18, 0.03, 0.06, 0.02, and 0.12, respectively). Comparison of raw milk across the nodes showed that the odds of milk samples from restaurants, roadside vendors, and shops/kiosks being acceptable were less than the odds of samples collected the farm for TBC (0.03, 0.04, and 0.04, respectively). For TCC, the odds of raw milk from collection centers, restaurants, roadside vendors, milk bars, and shops/kiosks being acceptable were lower than the odds of acceptability for the farm samples (0.18, 0.12, 0.02, 0.04, and 0.05, respectively). Practices with possible influence on milk bacterial quality included muddy cowsheds, unconventional animal feed sources, re-use of spoilt raw milk, milk adulteration, acceptance of low-quality milk for processing, and lack of cold chain. Therefore, milk contamination occurs at various points, and the designing of interventions should focus on every node.</jats:p