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Cross-Sectional Association of Food Source with Food Insecurity, Dietary Diversity and Body Mass Index in Western Kenya.

ABSTRACT: The triple burden of malnutrition in many low- and middle-income countries (LMICs) is partly a result of changing food environments and a shift from traditional diets to high-calorie Western-style diets. Exploring the relationship between food sources and food- and nutrition-related outcomes is important to understanding how changes in food environments may affect nutrition in LMICs. This study examined associations of household food source with household food insecurity, individual dietary diversity and individual body mass index in Western Kenya. Interview-administered questionnaire and anthropometric data from 493 adults living in 376 randomly-selected households were collected in 2019. Adjusted regression analyses were used to assess the association of food source with measures of food insecurity, dietary diversity and body mass index. Notably, participants that reported rearing domesticated animals for consumption ('own livestock') had lower odds of moderate or severe household food insecurity (odds ratio (OR) = 0.29 (95% CI: 0.09, 0.96)) and those that reported buying food from supermarkets had lower odds of moderate or severe household food insecurity (borderline significant, OR = 0.37 (95% CI: 0.14, 1.00)), increased dietary diversity scores (Poisson coefficient = 0.17 (95% CI: 0.10, 0.24)) and higher odds of achieving minimum dietary diversity (OR = 2.84 (95% CI: 1.79, 4.49)). Our findings provide insight into the relationship between food environments, dietary patterns and nutrition in Kenya, and suggest that interventions that influence household food source may impact the malnutrition burden in this context.

SUBMITTER: Olatunji E

PROVIDER: S-EPMC8747304 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo investigate whether reported fast-food consumption over the previous year is associated with higher childhood or adolescent body mass index (BMI).DesignSecondary analysis from a multicentre, multicountry cross-sectional study (International Study of Asthma and Allergies in Children (ISAAC) Phase Three).Subjects and methodsParents/guardians of children aged 6-7 completed questionnaires which included questions about their children's asthma and allergies, fast-food consumption, height and weight. Adolescents aged 13-14 completed the same questionnaire. The questionnaire asked "In the past 12 months, how often on average did you (your child) eat fast-food/burgers?" The responses were infrequent (never/only occasionally), frequent (once/twice a week) or very frequent (three or more times per week). A general linear mixed model was used to determine the association between BMI and fast-food consumption, adjusting for Gross National Income per capita by country, measurement type (whether heights/weights were reported or measured), age and sex.Results72,900 children (17 countries) and 199,135 adolescents (36 countries) provided data. Frequent and very frequent fast-food consumption was reported in 23% and 4% of children, and 39% and 13% of adolescents, respectively. Children in the frequent and very frequent groups had a BMI that was 0.15 and 0.22 kg/m(2) higher than those in the infrequent group (p<0.001). Male adolescents in the frequent and very frequent groups had a BMI that was 0.14 and 0.28 kg/m(2) lower than those in the infrequent group (p<0.001). Female adolescents in the frequent and very frequent groups had a BMI that was 0.19 kg/m(2) lower than those in the infrequent group (p<0.001).ConclusionsReported fast-food consumption is high in childhood and increases in adolescence. Compared with infrequent fast-food consumption, frequent and very frequent consumption is associated with a higher BMI in children. Owing to residual confounding, reverse causation and likely misreporting, the reverse association observed in adolescents should be interpreted with caution.

Project description:BackgroundAlthough the relationship between residential food environments and health outcomes have been extensively studied, the relationship between body mass index (BMI) and multiple food environments have not been fully explored. We examined the relationship between characteristics of three distinct food environments and BMI among elementary school employees in the metropolitan area of New Orleans, LA. We assessed the food environments around the residential and worksite neighborhoods and the commuting corridors.Research methodology/principal findingsThis study combined data from three different sources: individual and worksite data (ACTION), food retailer database (Dunn and Bradstreet), and the U.S. Census TIGER/Line Files. Spatial and hierarchical analyses were performed to explore the impact of predictors at the individual and environmental levels on BMI. When the three food environments were combined, the number of supermarkets and the number of grocery stores at residential food environment had a significant association with BMI (β = 0.56 and β = 0.24, p < 0.01), whereas the number of full-service restaurants showed an inverse relationship with BMI (β = -0.15, p < 0.001). For the commute corridor food environment, it was found that each additional fast-food restaurant in a vicinity of one kilometer traveled contributed to a higher BMI (β = 0.80, p <0.05), while adjusting for other factors. No statistical associations were found between BMI and worksite food environment.ConclusionsThe current study was the first to examine the relationship between BMI and food environments around residential neighborhoods, work neighborhoods, and the commuting corridor. Significant results were found between BMI and the availability of food stores around residential neighborhoods and the commuting corridor, adjusted for individual-level factors. This study expands the analysis beyond residential neighborhoods, illustrating the importance of multiple environmental factors in relation to BMI.

Project description:BackgroundAdolescents who receive an adequate amount of sleep benefit from a positive health status. Previous studies have documented several health consequences connected with obesity as well as short sleep duration among adolescents. Poor sleep quality with obesity and uncontrolled diet can lead to chronic diseases in the future. This study aimed to examine the link between eating habits, sleep duration, and body mass index (BMI) among King Saud University (KSU) students.MethodsThe study was cross-sectional and conducted from February to May 2021 on 311 recruited students (male and female) of KSU premises. Pittsburgh Sleep Quality Index questionnaire was used to describe sleep duration linked with a dietary pattern that included fruit and vegetable intake. The questionnaire consists of two sections of 15 and 10 questions each. The questionnaire was created using the Google Forms tool and distributed through social media platforms like Twitter and WhatsApp. The obtained data was transferred into excel to perform the statistical analysis.ResultsThe mean total of students who participated in this study was 21.45 ± 23.11. Female students (72.3%) were actively involved in this study. About 30.2% of students were found to be overweight and obese. Around 67.8% of students had insufficient sleep, 32.2% had adequate sleep, and over 70% of students fell asleep within 30 min of going to bed. A total of 71.7% of students showed good sleep quality, whereas 28.3% reported poor sleep quality. BMI was categorized into four groups: 17.7% of individuals were underweight, 52.1% were of normal weight threshold, 20.6% were overweight, and 9.6% were obese. On a regular basis, 12.5% of students consume vegetables and 6.4% fruits daily. The results of this study show that only 8% of students eat breakfast, whereas 62.1% eat lunch, and 29.9% eat dinner.ConclusionThis study concludes that short sleep duration was associated with obesity among KSU students. This association was also found between sleep duration and dietary factors, specifically in the consumption of fruits and vegetables in terms of eating behaviour.

Project description:To investigate the association between the neighborhood food environment and body mass index (BMI) among Chinese older adults. A multi-stage stratified random sampling method was used to recruit participants from 12 communities in Beijing, China, in 2019. Participants (n = 1764, 1034 women) in this study were older adults aged 65 to 80. We collected the participants' basic information, measured their height and weight, and calculated their BMI. Neighborhood food environments were measured by the density of and proximity to different food outlets using the Baidu Map Application Programming Interface. Adjusted multiple linear regression was performed to estimate the association between the food environment and BMI. Participants had a mean age of 69.7 ± 4.32 years old and an average BMI of 26.3 ± 3.50 kg/m2. Among the three types of stores, convenience stores had the easiest access, followed by greengrocers and supermarkets. Sit-down restaurants had the best access among different restaurants, followed by Chinese fast-food restaurants, and western fast-food restaurants had the worst access. Easier access to greengrocers (β = 0.281, p < 0.001) and sit-down restaurants (β = 0.304, p < 0.001) was associated with higher BMI in the 250 m buffer zone. More supermarkets were associated with higher BMI in the 500 m buffer zone (β = 0.593, p < 0.001). Access to convenience stores was positively associated with BMI in the 800 m buffer zone (β = 0.057, p < 0.001). Better access to Chinese fast-food restaurants was associated with higher BMI (β = 0.071, p = 0.001), and better access to western fast- food restaurants was associated with lower BMI (β = -0.400, p < 0.001) in the 1000 m buffer zone. There was a negative association between the nearest distance to greengrocers and BMI (β = -0.004, p < 0.001). Although we found some significant associations between the neighborhood food environment and obesity, the current results are not strong enough to draw specific conclusions. Policymakers will need to rely on more evidence to derive concrete policy recommendations.

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Cross-Sectional Association of Food Source with Food Insecurity, Dietary Diversity and Body Mass Index in Western Kenya.

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