assessment of pediatric malnutrition and …...assessment of pediatric malnutrition and household...
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Assessment of pediatric malnutrition and household food insecurity in Kisii and Nyamira, Kenya
Kevin Forey, MD-MBA Health Administration, Class of 2018
Blair Gifford, PhD Professor of Management and Health Administration
University of Colorado Denver
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Objectives
1. To determine the prevalence of moderate and severe acute malnutrition among schoolchildren
2. Characterize household food insecurity and dietary diversity
3. Determine the proportion of schools that provide lunch to students and have access to a kitchen
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Setting
• Kisii and Nyamira are among the most fertile land in Kenya
• Predominantly rural communities
• High access to fruits and vegetables
• However, Vitamin A deficiencies remain prevalent among children
• Minimal clinical information about this population otherwise
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Subjects
• Male and female children
• Ages < 5 • Height < 120 cm
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Prevalence of Acute MalnutritionNo School
Lunch Provided
84.9%(n=674)
15.1%(n=105)
n = 794
MAM or SAMNormalMAM: moderate acute malnutritionSAM: severe acute malnutrition
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Prevalence of Acute MalnutritionNo School
Lunch Provided
84.9%(n=674)
15.1%(n=105)
School Lunch Provided
98.8%(n=15)
1.2%(n=1)
n = 85n = 794
MAM or SAMNormalMAM: moderate acute malnutritionSAM: severe acute malnutrition
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Prevalence of Acute MalnutritionNo School
Lunch Provided
84.9%(n=674)
15.1%(n=105)
n = 794
MAM or SAMNormal
WHO Crisis Classification of Acute Malnutrition
Acceptable < 5%
Poor 5 - 9%
Serious 10 - 14%
Critical > 15%
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Prevalence of Acute MalnutritionNo School
Lunch Provided
84.9%(n=674)
15.1%(n=105)
n = 794
MAM or SAMNormal
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School Lunches and Kitchens
Do children ages 2-6 receive a school lunch?
70%No
Yes30%
n = 43 schools
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School Lunches and Kitchens
Do children ages 2-6 receive a school lunch?
Is a kitchen available at your school?
70%No
Yes30%
Yes91%
9%No
n = 43 schools
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School Lunches and Kitchens
Do children ages 2-6 receive a school lunch?
Is a kitchen available at your school?
Do older students receive food?
70%No
Yes30%
Yes91%
9%No
70%Yes
No30%
n = 43 schools
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Proportion of Families That Have Eaten Each Food Group In the Past 24 Hours
Staple Foods 100%
Root Crops 59%
Vegetables 97%
Fruits 89%
Beef, Goat, Lamb, Pork, Poultry 24%
Eggs 37%
Fish 11%
Beans, lentils 62%
Milk, Cheese, Other dairy 68%
Butter, Fats, Oil 90%
Sugar, Honey, Sweetener 84%
Tea, Coffee 95%
Household Dietary
Diversity
N = 96
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Proportion of Families That Have Eaten Each Food Group In the Past 24 Hours
Staple Foods 100%
Root Crops 59%
Vegetables 97%
Fruits 89%
Beef, Goat, Lamb, Pork, Poultry 24%
Eggs 37%
Fish 11%
Beans, lentils 62%
Milk, Cheese, Other dairy 68%
Butter, Fats, Oil 90%
Sugar, Honey, Sweetener 84%
Tea, Coffee 95%
Household Dietary
Diversity
N = 96
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Proportion of Families That Have Eaten Each Food Group In the Past 24 Hours
Staple Foods 100%
Root Crops 59%
Vegetables 97%
Fruits 89%
Beef, Goat, Lamb, Pork, Poultry 24%
Eggs 37%
Fish 11%
Beans, lentils 62%
Milk, Cheese, Other dairy 68%
Butter, Fats, Oil 90%
Sugar, Honey, Sweetener 84%
Tea, Coffee 95%
Household Dietary
Diversity
N = 96
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Proportion of Families That Have Eaten Each Food Group In the Past 24 Hours
Staple Foods 100%
Root Crops 59%
Vegetables 97%
Fruits 89%
Beef, Goat, Lamb, Pork, Poultry 24%
Eggs 37%
Fish 11%
Beans, lentils 62%
Milk, Cheese, Other dairy 68%
Butter, Fats, Oil 90%
Sugar, Honey, Sweetener 84%
Tea, Coffee 95%
Household Dietary
Diversity
N = 96
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Proportion of Families That Have Eaten Each Food Group In the Past 24 Hours
Staple Foods 100%
Root Crops 59%
Vegetables 97%
Fruits 89%
Beef, Goat, Lamb, Pork, Poultry 24%
Eggs 37%
Fish 11%
Beans, lentils 62%
Milk, Cheese, Other dairy 68%
Butter, Fats, Oil 90%
Sugar, Honey, Sweetener 84%
Tea, Coffee 95%
Household Dietary
Diversity
N = 96
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Proportion of Families That Have Eaten Each Food Group In the Past 24 Hours
Staple Foods 100%
Root Crops 59%
Vegetables 97%
Fruits 89%
Beef, Goat, Lamb, Pork, Poultry 24%
Eggs 37%
Fish 11%
Beans, lentils 62%
Milk, Cheese, Other dairy 68%
Butter, Fats, Oil 90%
Sugar, Honey, Sweetener 84%
Tea, Coffee 95%
Household Dietary
Diversity
N = 96
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Household Dietary DiversityResponses Separated Into
Bottom, Upper, and Middle Thirds Range Mean Response
Mean HDDS P-value
Weekly Income (N=45)
Bottom 1/3 0 – 1000 KSH 627 KSH 8.2
Middle 1/3 1050 – 2100 KSH 1438 KSH 8.2 0.882
Upper 1/3 2160 – 15000 KSH 4258 KSH 7.8
Percent of Weekly Income Spent on Food
(N=45)
Bottom 1/3 7 – 47% 30% 7.9
Middle 1/3 50 – 95% 67% 8.3 0.547
Upper 1/3 100 – 362% 159% 8.6
Number of People Living In Household
(N=45)
Bottom 1/3 3 – 4 people 3.8 7.8
Middle 1/3 5 – 6 people 5.6 7.8 0.549
Upper 1/3 7 – 10 people 8.1 7.7
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Household Dietary DiversityResponses Separated Into
Bottom, Upper, and Middle Thirds Range Mean Response
Mean HDDS P-value
Weekly Income (N=45)
Bottom 1/3 0 – 1000 KSH 627 KSH 8.2
Middle 1/3 1050 – 2100 KSH 1438 KSH 8.2 0.882
Upper 1/3 2160 – 15000 KSH 4258 KSH 7.8
Percent of Weekly Income Spent on Food
(N=45)
Bottom 1/3 7 – 47% 30% 7.9
Middle 1/3 50 – 95% 67% 8.3 0.547
Upper 1/3 100 – 362% 159% 8.6
Number of People Living In Household
(N=45)
Bottom 1/3 3 – 4 people 3.8 7.8
Middle 1/3 5 – 6 people 5.6 7.8 0.549
Upper 1/3 7 – 10 people 8.1 7.7No Statistical
Significance
No Statistical
Significance
No Statistical
Significance
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In the past one month …Yes
NoRarely (1-2)
Sometimes (3-10 times)
Often (10+)
… did you worry that your household would not have enough food? 14.6% 71.9% 5.2% 8.3%
… did you or a household member have to eat a limited variety of foods? 16.8% 54.7% 15.8% 12.6%
… eat fewer meals because there was not enough food? 26.0% 47.9% 8.3% 17.7%
… was there ever no food to eat? 9.4% 30.2% 1.0% 59.4%
… did you or any household member go to sleep at night hungry? 15.6% 29.2% 1.0% 54.2%
Household Food InsecurityFood Secure Mildly
Food InsecureModerately
Food InsecureSeverely
Food InsecureProportion of
Caregivers Surveyed7.3% (7/96)
11.5% (11/96)
32.3% (31/96)
49.0% (47/96)
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Conclusions
- Acute malnutrition is present among schools without lunch
- High diversity and availability of foods
- Animal proteins less common
- Malnutrition not simply a matter of poverty
- Evidence of cultural, social, and behavioral components
- Parents more willing to provide food for older children
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Limitations
- Study limited to children attending school
- Selection bias
- Most important age group not included (< 2 yrs)
- Community health likely worse than our results
- Unable to accurately determine chronic malnutrition
- No access to dates of birth
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Solutions
- Short-term:Community based management of acute malnutrition (CMAM) with RUTF (eg. Plumpy’Nut)
- Long-term: (1) Better understand feeding practices (eg. research) (2) Public health campaign (eg. parents -> contribute to school lunches) (3) Education among parents of affected children
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What To Do
- Short-term:Community based management of acute malnutrition (CMAM) with RUTF (eg. Plumpy’Nut)
- Long-term: (1) Better understand feeding practices (eg. research) (2) Public health campaign (eg. parents -> contribute to school lunches) (3) Education among parents of affected children
Spring 2018
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Thank You! Thank You!
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