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This study investigated associations between types and food sources of protein with overweight/obesity and underweight in Ethiopia.
We conducted a cross-sectional dietary survey using a non-quantitative FFQ. Linear regression models were used to assess associations between percentage energy intake from total, animal and plant protein and BMI. Logistic regression models were used to examine the associations of percentage energy intake from total, animal and plant protein and specific protein food sources with underweight and overweight/obesity.
Addis Ababa, Ethiopia.
1624 Ethiopian adults (992 women and 632 men) aged 18–49 years in selected households sampled using multi-stage random sampling from five sub-cities of Addis Ababa.
Of the surveyed adults, 31 % were overweight or obese. The majority of energy intake was from carbohydrate with only 3 % from animal protein. In multivariable-adjusted linear models, BMI was not associated with percentage energy from total, plant or animal protein. Total and animal protein intake were both associated with lower odds of overweight/obesity (OR per 1 % energy increment of total protein 0·92; 95 % CI: 0·86, 0·99; P = 0·02; OR per 1 % energy increment of animal protein 0·89; 95 % CI: 0·82, 0·96; P = 0·004) when substituted for carbohydrate and adjusted for socio-demographic covariates.
Increasing proportion of energy intake from total protein or animal protein in place of carbohydrate could be a strategy to address overweight and obesity in Addis Ababa; longitudinal studies are needed to further examine this potential association.
To examine the prevalence of and factors associated with different forms of household-level double burden of malnutrition (DBM) in Ethiopia.
We defined DBM using anthropometric measures for adult overweight (BMI ≥ 25 kg/m2), child stunting (height-for-age Z-score <-2 sd) and overweight (weight-for-height Z-score ≥2 sd). We considered sixteen biological, environmental, behavioural and socio-demographic factors. Their association with DBM forms was assessed using generalised linear models.
We used data from two cross-sectional studies in an urban (Addis Ababa, January–February 2018), and rural setting (Kersa District, June–September 2019).
Five hundred ninety-two urban and 862 rural households with an adult man, adult woman and child <5 years.
In Addis Ababa, overweight adult and stunted child was the most prevalent DBM form (9 % (95 % CI 7, 12)). Duration of residence in Addis Ababa (adjusted OR (aOR) 1·03 (95 % CI 1·00, 1·06)), Orthodox Christianity (aOR 1·97 (95 % CI 1·01, 3·85)) and household size (aOR 1·24 (95 % CI 1·01, 1·54)) were associated factors. In Kersa, concurrent child overweight and stunting was the most prevalent DBM form (11 % (95 % CI 9, 14)). Housing quality (aOR 0·33 (95 % CI 0·20, 0·53)), household wealth (aOR 1·92 (95 % CI 1·18, 3·11) and sanitation (aOR 2·08 (95 % CI 1·07, 4·04)) were associated factors. After adjusting for multiple comparisons, only housing quality remained a significant factor.
DBM prevalence was low among urban and rural Ethiopian households. Environmental, socio-economic and demographic factors emerged as potential associated factors. However, we observed no common associated factors among urban and rural households.
In Ethiopia, women’s dietary diversity is low, primarily due to poor food availability and access, both at home and market level. The present study aimed to describe market access using a new definition called market food diversity (MFD) and estimate the impact of MFD, crop and livestock diversity on dietary diversity among women enrolled in the Agriculture to Nutrition (ATONU) trial.
Baseline cross-sectional data collected from November 2016 to January 2017 were used for the analysis. Availability of foods in markets was assessed at the village level and categorized into nine food groups similar to the dietary diversity index for women. Bivariate and multivariate mixed-effects regression analyses were conducted, adjusted for clustering at the village level.
Chicken-producing farmers in rural Ethiopia.
Women (n 2117) aged 15–49 years.
Overall, less than 6 % of women met the minimum dietary diversity (≥5 food groups) and the most commonly consumed food groups were staples and legumes. Median MFD was 4 food groups (interquartile range: 2–8). Multivariate models indicated that women’s dietary diversity differed by livestock diversity, food crop diversity and agroecology, with significant interaction effects between agroecology and MFD.
Women’s dietary diversity is poor in Ethiopia. Local markets are variable in food availability across seasons and agroecological zones. The MFD indicator captures this variability, and women who have access to higher MFD in the highland agroecological zone have better dietary diversity. Thus, MFD has the potential to mitigate the effects of environment on women’s dietary diversity.
The present study’s aim was to assess the impact of a nutrition-sensitive intervention on dietary diversity and home gardening among non-participants residing within intervention communities.
The study was a cross-sectional risk factor analysis using linear and logistic multivariate models.
In Tanzania, women and children often consume monotonous diets of poor nutritional value primarily because of physical or financial inaccessibility or low awareness of healthy foods.
Participants were women of reproductive age (18–49 years) in rural Tanzania.
Mean dietary diversity was low with women consuming three out of ten possible food groups. Only 23·4 % of respondents achieved the recommended minimum dietary diversity of five or more food groups out of ten per day. Compared with those who did not, respondents who had a neighbour who grew crops in their home garden were 2·71 times more likely to achieve minimum dietary diversity (95 % CI 1·60, 4·59; P=0·0004) and 1·91 times more likely to grow a home garden themselves (95 % CI 1·10, 3·33; P=0·02). Other significant predictors of higher dietary diversity were respondent age, education and wealth, and number of crops grown.
These results suggest that there are substantial positive externalities of home garden interventions beyond those attained by the people who own and grow the vegetables. Cost-effectiveness assessments of nutrition-sensitive agriculture, including home garden interventions, should factor in the effects on the community, and not just on the individual households receiving the intervention.
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