The Influence of Food Environments on Food Security Resilience during the COVID-19 Pandemic: An Examination of Urban and Rural Difference in Kenya

Ethnicity, social connectedness, and the rural-urban food continuum: Food security among urban informal settlement dwellers in Kenya

Rapid urbanization in developing countries is increasingly becoming an important development issue due to its negative effects on poverty and food insecurity in cities. This study investigated the determinants of the food insecurity gap among urban households living in informal settlements in Nairobi, Kenya, and the role of social connectedness and the rural-urban food continuum. Using panel data collected from 385 households using a two-stage cluster sample design, the study applied panel data regression and decomposition models to understand the factors affecting food insecurity access scores and weekly household food consumption expenditure. Descriptive results showed a score of 8.00 for the pooled sample on the household food access scale, with households from other regions having a lower score (7.94) than those from the Western region (8.32). 43 % of households from Western Kenya engaged in farming in rural areas (43 %) and had higher social connectedness (45 %) than households from other regions. The results indicate that dependency ratio, income, savings, social connectedness, rural visits, and dietary knowledge are significant factors impacting food security. Decomposition of levels and change in food insecurity revealed that endowments from the random effects model contributed to reducing the food insecurity gap between households originating from the Western region and those from other regions. The study highlights the importance of considering regional factors and promoting social connectedness and rural-urban linkages in addressing food insecurity in informal urban settlements.

Convenience as a dimension of food environments: A systematic scoping review of its definition and measurement

Convenience is a major driver of food choice throughout the world, yet it is often inconsistently conceptualised, defined and measured. This limits the scope for food systems policy and interventions to leverage convenience to improve diet and nutrition outcomes. We conducted a systematic literature review to determine how convenience is both defined and measured in food environment and nutrition research. Six databases were systematically searched and studies were screened by two independent reviewers based on pre-defined eligibility criteria, yielding 243 studies for inclusion in the final review. 77% of studies did not explicitly define convenience. Among those that did, the dimensions and components within definitions varied. 83% of studies used perceived measures of convenience rather than objective measures. Convenience was most commonly measured in high income countries (64%) and in relation to the home food environment (53%), followed by formal retail (40%). Very few studies measured convenience in relation to the informal retail or cultivated food environments, and no studies considered convenience in relation to wild food environments. The vast majority of studies did not consider the validity or reliability of the measures of convenience. Based on our findings we propose a definition of convenience as a characteristic that results in reduced requirement for resources including time, physical effort, mental effort and skills by the consumer in relation to the planning, acquisition, preparation, storage, transport, consumption or clean-up of food. This definition can be used to help guide the development of measurement tools that can be used to assess convenience across different dimensions and contexts in a more comprehensive way. We also propose a framework for considering convenience as an entry point in food systems to improve diets and nutrition outcomes.

Centering context when characterizing food environments: the potential of participatory mapping to inform food environment research

Food environments are a critical place within the food system to implement interventions aimed at enabling sustainable diets. In this perspective article, we argue for the need for food environment research to more comprehensively examine the different types of food environments that people access within their communities to ensure that interventions and programs are better aligned with people's lived experiences. We highlight the potential ways in which participatory mapping (PM) can be leveraged to better design food environment research by: (1) identifying the different food environment types that are accessed within a given community; (2) providing insight into the timing for data collection; (3) informing the prioritization of where to conduct food environment assessments; and (4) highlighting the dynamism of food environments over time (e.g., across a given day or across seasons). We provide a case study example of the application of PM and the lessons learned from it in Cambodia. By conceptualizing food environments in a more comprehensive way, from the perspective of the people living within a given community, we will be able to measure food environments in a way that more closely aligns with people's lived experiences.

Seasonal variation in pesticide residue occurrences in surface waters found in Narok and Bomet Counties, Kenya

Narok and Bomet are agricultural counties in Kenya which depend on flowing surface waters for farming activities. Agrochemicals have frequently been used to increase agricultural produce in this region. Occasionally, appropriate pesticide utilization measures are not followed. These surface waters are also consumed domestically by humans, livestock, and wild animals thus posing safety concerns to them. The current study sought to evaluate the levels and nature of pesticide residues found in surface waters in the dry and wet seasons of these counties. Eight water samples were collected in July (dry season) and October (wet season) at four different river sites in each of the two counties predetermined by the agricultural activity of its proximate environs. Pesticides extracted by solid phase extraction were analyzed by gas chromatography-mass spectrometry. At least 38 different pesticides were detected in the two counties with the highest concentration being recorded for chlorpyrifos and piperidine in Narok and Bomet counties, respectively. The pesticides chlorpyrifos, cypermethrin, cyfluthrin, and cyhalothrin were more prevalent in Narok County while triazine, semicarbazone, and epinephrine were more prevalent in Bomet County. There were significantly more pesticides detected during the wet season (P ≤ 0.05). Out of the nine prevalent pesticides detected, four of them posed serious ecotoxicology concerns with risk quotients above 1.0 (high risk); thus, there is a need for more government policy interventions in deterring farming near riparian lands and in training of famers regarding best practice for pesticide applications.

Weight Change Following Switch to Dolutegravir for HIV Treatment in Rural Kenya During Country Roll-Out

INTRODUCTION

Switch to dolutegravir (DTG) in treatment-experienced people living with HIV (PLH) is associated with excess weight gain in some settings; data are limited from rural low-income settings with low obesity prevalence.

METHODS

In rural Kenya, we conducted a retrospective cohort study at 8 HIV clinics and a single-site prospective cohort study including adults switching to DTG during countrywide transition to DTG/tenofovir DF(TDF)/emtricitabine as first-line HIV treatment. In the retrospective analysis, we used preswitch data to model postswitch weight trajectory had each participant not switched to DTG and contrasted observed vs. predicted postswitch weight. In the prospective analysis, we measured weight post-DTG switch and evaluated predictors of 6-month weight change.

RESULTS

Our retrospective cohort included 4445 PLH who switched to DTG between 2018 and 2020. Mean 12-month weight change was 0.6 kg preswitch and 0.8 kg postswitch. Among those on TDF throughout (n = 3374; 83% on efavirenz preswitch), 12-month postswitch weight was 0.7 kg more than predicted for women (95% CI: 0.4, 1.0) and similar among men (0.04 kg; 95% CI -0.3, 0.4). In our prospective cohort (n = 135, 100% female), mean 6-month weight change was +0.4 kg (IQR -1.1, 2.0 kg). Predicted gain varied by baseline food insecurity: +1.1 kg (95% CI: 0.34, 1.87) among food secure, -0.09 kg (95% CI -0.71, 0.54) among moderate insecure, and +0.27 kg (95% CI -0.82, 1.36) among severe insecurity.

CONCLUSION

In contrast to some reports of large weight gain following switch to DTG, we observed small weight increases in women and no weight change in men following DTG switch when on TDF throughout. Weight gain may be attenuated by food insecurity, though was modest even among food secure.