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A socio-economic survey of the role of fisheries in rural

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									                      Food Security and Nutrition Report
   A Component of the BioOkavango Socio-economic Survey Report on the Role of
Fisheries in Rural Livelihoods Diversification in the Upper Panhandle, Okavango Delta:




                                 Dr. M. S. Nnyepi
                         Department of Home Economics, UB




                                                                                         1
                                        Food Security and Nutrition Report
     A Component of the BioOkavango Socio-economic Survey Report on the Role of
  Fisheries in Rural Livelihoods Diversification in the Upper Panhandle, Okavango Delta:




Table Of Contents


Table Of Contents ........................................................................................................................... 2
Introduction ..................................................................................................................................... 3
Methodology ................................................................................................................................... 3
Food Security And Dietary Diversity Modules .............................................................................. 3
   Assessment Of Food Security And Dietary Diversity: . ............................................................. 3
   Household Food Insecurity: ....................................................................................................... 4
   Dietary Diversity of Adults: . ..................................................................................................... 4
Nutritional Status Of Adults ........................................................................................................... 6
   Nutritional Status Of Children ≤ 5 Years Old: ............................................................................ 7
      Wasting (Acute Malnutrition) ................................................................................................ 11
      Stunting (Chronic Malnutrition) ............................................................................................ 13
      Underweight: (Low Weight-For-Age) ................................................................................... 13
      Feeding Practices.................................................................................................................... 14
      Role Of Fish In Children’ Diet ............................................................................................... 15
      Diversity Of Children’s Diets ................................................................................................ 15
Discussion ..................................................................................................................................... 16
Research And Policy Implications ................................................................................................ 18




                                                                                                                                                  2
Introduction
This report focuses on the food security and nutrition components of the Bio-Okavango Socio-
economic survey on the role of fisheries in rural livelihoods diversification. The discussion and
recommendation are based on survey observations from modules relating to household food
insecurity, dietary diversity and the nutritional status of children and adults.


Methodology
In this cross sectional descriptive study, we used systematic random sampling methodology to
enroll households in each of the five study villages. We used the 2001 population census maps
and household tags to identify village boundaries and facilitate the construction of the sampling
frames. Thereafter all dwelling units were listed, and a random sample of dwelling units was
drawn using a skip pattern of 3 units. Vacant / disserted dwelling units were replaced with other
units within the sampling frame. This resulted in a total sampling size of 296 households in the
five villages.

Data analysis for the food security, dietary diversity, and adult nutritional status was based on a
sample of 296 households. In each household, information was obtained from the oldest adult
with responsibility over household food. With respect to the nutritional status of children,
observations were available from 161 households. Some household did not have children within
the preferred age range (0-5 years).

Trained research assistants administered the survey instruments (Socio-demographics data) and
the Food insecurity and Dietary Diversity instruments under the supervision of one Research
Associate. While in the field, the team was paid a supervisory visit by a member of the
investigators every two weeks. Field work was started on the third week of October and carried
on until the third week of November.


Food security and dietary diversity modules
Assessment of food security and dietary diversity: Two instruments, the Household Food
Insecurity Access Scale (HFIAS) (Coates et al., 2006) and the Dietary Diversity (DDS)
Questionnaires (Swindale and Bilinsky, 2006) were applied to an adult with responsibility over
household food to assess household access to food and dietary diversity respectively. Food
security is a state where each household has access to adequate amounts of wholesome food for
all members at all times. Thus in assessing household food insecurity, indicators that determine
households’ access to food were used. The Household Food Insecurity Access Scale is one such
tool. This tool assesses households food insecurity through a set of questions that examines
households experience of conditions in the three domains of food insecurity; anxiety about the
sufficiency of households food, intake of food of insufficient quality and reduced food intake.
The instrument also assesses the severity of households experience and the prevalence of food
insecurity.

Household Dietary Diversity: In addition to assessing household access to food (food security),
there is need to also assess the nutritional adequacy of the diet. The Dietary Diversity
Questionnaires assesses the quality of the diet by examining the number of food groups


                                                                                                    3
represented in the 24-hour dietary intake of household members. The more food groups
represented (the more diverse the diet) the higher the likelihood that the diet meets the
recommended macronutrient and micronutrient intake and is therefore considered to be of high
quality. Both the HFIAS and the DDS instruments have been validated in African settings (Webb
et al., 2002).

 Household Food Insecurity: The assessment of households’ access to food revealed that most
households experienced food insecurity conditions that fell in the three domains of food
insecurity, as displayed in the Table 1. Five of the nine undesirable food insecurity conditions
were very common with over 90% of households having experienced them in the past 30 days.
Not only did households report ever being anxious about their food supply (98.7%) in the past
month, but quite significant proportion of households also reported having slept hungry because
there was no food(75.7%) or having gone for the whole night and day without food (40.9%).
Although some households reported experiencing these conditions 1-2 times in the past month,
the proportion of households who reported experiencing them more often (10 or more times per
month) were in the double digits, ranging from 14.5% for those who spent the whole night and
day without food to 64.6% for those who were worried about their food supply, suggesting that
food insecurity was a major problem in this population.
       Further, the household food insecurity access scale score (HFIASS) was calculated for
this population as described by Coates et al. (2006) and households were assigned into four
categories (food secure, mildly food insecure, moderately food in-secure or severely food in-
secure) based on their score. The results revealed that only 2% of households were classified as
food secure, while the prevalence of mild and moderate food in-security were estimated at 12.5%
and 85.5% respectively. Fortunately, no households were found to be severely food in-secure.

 Dietary Diversity: Dietary Diversity Score was computed from twelve food groups shown in
Table 3. The mean DDS observed for households in this study was 5.2 out of a possible score of
12 and the mode was 5. A higher DDS score is desirable as it reflects that a large number of
different types of foods are consumed. Such a diverse diet is associated with a diet of high
quality. Household with more diversified diets are also less likely to have diets inadequate in
macronutrient and micronutrient. In regions where dietary diversity has been studied extensively
the minimum dietary diversity scores associated with good nutritional status are established.
There are no previously established cut off points that are associated with improved nutrition
indicators in Botswana. Thus, the Dietary Diversity Scores in this study were divided into
terciles and the proportion of household at different terciles were computed to establish the
proportion of household with DDS below the lower tercile which may, as a result, be associated
with a higher risk of poor nutrition. This analysis revealed that 34% of households had dietary
diversity scores below the lower tercile (i.e. a DDS score of 4) while 23.2 % had scores at or
above the upper tercile (DDS score of 6). The upper tercile was therefore assumed to be
reflective of a more diversified diet in this population group.




                                                                                              4
                       Table 1: Domains and frequency of food in-security conditions

Domains of Food Insecurity     Food Insecurity Conditions      % Households   Frequency of   %
                                                                              Occurrence     Households
Anxiety and uncertainty of     Worry that food is not enough   98.7           Rare            6.1
food supply                                                                   Sometimes      27.6
                                                                              Often          64.6
Insufficient quality           Not able to eat kinds of food   96             Rare           5.7
                               you like                                       Sometimes      31.6
                                                                              Often          58.6
                               Eat limited variety of Foods    93.9           Rare           11.1
                                                                              Sometimes      46.1
                                                                              Often          36.7
                               Eat food not wanted             45.1           Rare           11.1
                                                                              Sometimes      12.8
                                                                              Often          21.5
Insufficient food intake       Eat smaller meals               93.3           Rare           11.8
                                                                              Sometimes      41.1
                                                                              Often          40.4
                               Eat fewer meals                 93.3           Rare           12.1
                                                                              Sometimes      43.8
                                                                              Often          37.4
                               Had no food of any kind         75.8           Rare           27.6
                                                                              Sometimes      20.9
                                                                              Often          26.9
                               Slept hungry                    75.7           Rare           25.3
                                                                              Sometimes      26.9
                                                                              Often          22.9
                               Went whole day and night        40.9           Rare           15.5
                               without food                                   Sometimes      10.1
                                                                              Often          14.5



        The examination of households’ food intake revealed huge variability in the proportion of
households with intakes of foods from the twelve food groups (Table 2). Consistent with the low
DDS in this population group the intake of foods from some groups was reported by very few
households. In addition, three of the most frequently consumed foods were foods that add less
nutritive (especially micronutrients) value to the diet. These were miscellaneous items like spices
and condiments (87.2%), oils/fats (72.2%) and sugar (63.6%). Excluding sugars, fats and oils
and spices left the cereals group as the only food group from which foods were consumed by a
large (97.2%) percentage of households. This group was followed by vegetables, milk and dairy
products, meats and fish which were reported to have been consumed by 30-38% of the
households. The green leafy vegetables were the most frequently consumed of all vegetables,
with 37.7% of households consuming them compared to root vegetables. Very few households
reported intake of fruits, pulses, root/tubers, and eggs. The large difference (97% versus 30-38%)
between the proportion of households who reported intakes of foods from the cereal groups and
other food groups suggest that at the time of the study all that some households had to eat were
foods from cereals only. Such diets would surely fail to supply adequate micronutrients and
protein. However, given the large proportion of households who reported using fats and oils, the



                                                                                                      5
calorie content may have been within recommended levels, although this can only be ascertained
by subsequent studies. The high proportion of households reporting oils and fats and simple
sugars was rather surprising for rural areas but could be indicative of nutrition transition.

   Table 2. Household Reporting intakes of Foods from the 12 Food Groups in the past 24 hrs
 Food Groups in the Dietary Diversity Questionnaire                          % Households
 Cereals                                                                     97.3
 Miscellaneous (spices, condiments, tea, coffee, alcoholic beverages)        87.2
 Oils/fats                                                                   72.7
 Sugar/honey                                                                 63.6
 Milk and milk products                                                      37.7
 Vegetables                                                                   37.0
 Fish and sea food                                                           31.3
 Meat, poultry, offal                                                        30.0
 Fruits                                                                       17.8
 Pulses, legumes/ nuts                                                       16.1
 Roots and tubers                                                            8.4
 Eggs                                                                        1.7



Despite the vast resources that the Okavango Delta is renowned for, food insecurity in villages in
the panhandle remains a tremendous challenge. Not only are most (64.5%) households frequently
worried about their food supply, many have repeatedly resorted to eating foods of insufficient
variety (36.7%), quality, or have had to eat food that they would not eat if they had a choice (
(21.1%). As is indicative of the seriousness of the situation, a sizeable proportion of households
have slept hungry (22%) or spent the whole day and night without food (14.5%) several times a
month. Anxiety about the adequacy of food supply, and experiences of intake of food of
insufficient quality and quantity are common strands in food insecure households across cultures
(Coates et al 2006), and that these experiences are observed in the Okavango panhandle at such
high proportions only serves to confirm the gravity of the problem. The disparity between
households who worry about their food supply and those experiencing insufficient (quality and
quantity) food may be indicative of a combination of transient and chronic food insecurity.
Frequently households employ food insecurity-triggered behaviors such as bartering, selling of
assets for food and reducing food intake to avoid or delay having to go without food (Nnyepi,
2007; Oldewage-Theron, et al, 2005). Thus it is logical that there would be more households who
worry about their food supply than those who eventually go without food.


Nutritional Status Of Adults

Adults and children’s body measurements taken were used to compute several indices important
in describing the nutritional status. For children, the indices were weight-for-height z-score,
weight-for-age and height-for-age z-score which reflect the extent of wasting, underweight and
stunting respectively. These indices were compared to the WHO reference standards for healthy
children (WHO Anthro, 2001). Furthermore the prevalence of the underweight in the study
villages was compared to the national prevalence to fully appreciate how well children in this
area fare compared to other children the country.



                                                                                                6
In adults the nutritional indicators and health risks were described using the following
anthropometric parameters; Body Mass Index (BMI), Waist Circumference (WC), Waist-Hip-
Ratio and Mid-Upper-Arm Circumference (MUAC). These parameters aid in the description of
underweight, overweight and obesity and health risk for non communicable diseases, most
notably cardiovascular diseases and diabetes.


Figure 1 Waist Circumference, BMI and WHR cutoff points
BMI categories
≤ 18.49          undernourished
18.50 – 24.99    normal
25.00 – 29.99    overweight
 ≥ 30.00         obese

WC categories
Women                                      Me n
≤88              low health risk           ≤102
88              increased health risk      102

WHR categories
Women                                       Me n
≤0.80            low health risk           ≤ .90
≥0.85            high health risk          .90




Consistent with the sample size for this study, data available for analyses were obtained from
295 adults, one from each household. The total number of adults included in the nutritional
analysis per locality is displayed in Table 3. Most adults were women (65.1%)

Table 3. Distribution of adults per locality.
Locality               N             %             Gender    N         %
Ngarange               41           13.9           male     102       34.9
Shakawe               107           36.3           female   190       65.1
Mohembo West           68           23.1           Total    292
Mohembo East           39           13.2
Samochima              40           13.6
Total                 295

Three nutrition indicators, the Body Mass Index (BMI), Waist Circumference (WC), and Waist-
Hip-Ratio (WHR) were used to describe the nutritional status of adults. Body Mass Index is
correlated with fatness and is thus commonly used to distinguish people with underweight
(BMI< 18.5), overweight BMI > 24.9 and varying degrees of obesity (BMI > 30.0). While the
mean Body Mass Index of this population was estimated at 22.2 ± 4.8) and fell within normal
limits overall, about one (1) in five adults were either underweight (22.1%) or overweight
(20.7%). Significant gender differences were observed as displayed in the Table 4, with more
women being either underweight or overweight compared to men.




                                                                                                 7
                              Table 4: BMI * Gender Distribution

BMI                                      Gender                             Total
                            male                  female
underweight                 17 ( 16.7)                 47(25.1)                      64(22.2)
normal                       72(70.6)                  92(49.2)                     164(56.7)
overweight                   13( 12.7)                 48(25.7)                      61(21.1)
Count                       102(35.3)                 187(64.7)                     289(100)
X2 12.680 p< .002

There was some indication that Samochima (31.5), Ngarange (36.6) and Mohembo east (31.6)
had higher prevalence of underweight above the four village average of 21.9%, while at 31%
and 25% the prevalence of overweight in Mohembo west and Shakawe respectively were much
higher than the four village average of overweight of 21.1%. While significant (X 2; 24.732; df
8, p< .002), these observations should be interpreted with caution because the cells were rather
small (although the minimum expected cell count was not less than 5 (8.07 per cell).

Both underweight and overweight increase the risk of morbidity and mortality although the
causes may be very different. These conditions are also known to coexist in low SES population
groups. Hence the almost equal prevalence of underweight and overweight in the study villages
as is evident in Table 5 is not surprising.

Table 5. BMI * District Code Distribution

REC_BMI                                             District Code                                  Total
                    NGARANG        SHAKAWE          MOHEMBO          MOHEMBO           72107
                        E                             WEST             EAST
underweight          15 (36.6)      19 (17.9)              5 (7.5)      12 (31.6)      13 (32.5)    64 (21.9)
normal                22 (53.7)     60 (56.6)          41 (61.2)        22 (57.9)      21 (52.5)   166 (56.8)
overweight              4 (9.80    279 (25.9)          21 (31.3)         4 (10.5)       6 (15.0)    62 (21.2)


 In addition to BMI, the waist hip ratio (WHR) and Mid Upper Arm Circumference were used to
further describe the nutritional risk for non communicable diseases in adults. The WHR gives an
indication of central obesity and ratios greater than .80 for women or .9 for men are correlated
with a high risk of non communicable diseases especially cardiovascular diseases. Based on this
indicator, 84.3% and 74.2% of men (Table 6a) and women (Table 6b) respectively were found
have higher WHR ratios than recommended and clearly indicated that central adiposity was a
serious problem in this population groups. Given that the higher WHR ratios are associated with
non communicable diseases, the prevalence of diabetes and high blood pressure were
investigated. Subjects were asked about their history of diabetes and perceptions of body weight.




                                                                                                            8
Table 6a. WHR_males
                                         Valid            Cumulative
WHR           N         Percent         Percent            Percent
WHR < 0.9
               16              5.4            15.7               15.7
WHR > 0.9
               86             29.2            84.3              100.0
Total
              102             34.6           100.0
(Women )
              193             65.4
Total
              295            100.0



Table 6b. WHR_females
                                              Valid         Cumulative
 WHR                N          Percent       Percent         Percent
 WHR < 0.80
                        49            16.6         25.8           25.8
 WHR > 0.80
                    141               47.8         74.2          100.0
 Total
                    190               64.4        100.0
 (men)
                    105               35.6
 Total
                    295              100.0




Despite the high risk for diet related non communicable illnesses observed in this population,
very few adults reported positive history of high blood pressure and diabetes (Table 7).
Fortunately, most of those who were ever told by health providers that they have diabetes or high
blood pressure were on treatment. With regard to body weight, very few adults were ever told by
health providers that they are overweight.

 A sizeable percent of adults 46.2% were not happy with their body weight and 44.9% thought
that their body weight fell outside the healthy range. This was not followed up to determine
whether concerns were that weight was lower or higher than desired. However given the almost
equal proportions of overweight or underweight adults, concerns could mean any of these
conditions. This is further supported by the observation that about one third (33.4%) of adults
reported having been had an illness that lasted longer than 3 months in the past year, which also
led to hospitalization in 63.4% of the cases. This is clearly an issue that needs to be followed up
in subsequent studies.




                                                                                                 9
Table 7. Reported history of body weight, high blood pressure and other illnesses
                                                N     %      On treatment                              N    %
Did health providers ever tell that your body                Are you on treatment for overweight?
weight is too high?                             9     3.1                     Yes                      1    14.3
                  Yes                           285   96.9                    No                       7    85.7
                  No
Are you happy with your current body
weight?
                  Yes                           157   53.8
                  No                            135   46.2
Do you think your weight is within healthy
range?
                  Yes                           161   55.1
                  No                            131   44.9
Did health providers ever tell you that you                  Are you on Treatment for high blood
have high blood pressure?                                    pressure?
                  Yes                           18    6.2                    Yes                       14   77.8
                  No                            270   93.7                   No                        4    22.2
Did health providers ever tell you that you                  Are you on treatment for diabetes?
have diabetes?
                 Yes                            6     2.0                         Yes                  3    50
                 No                             287   98.0                        No                   3    50
Have you ever been ill for a period longer                   Did      this      illness   lead    to
than 3 months                                                hospitalization?                          63   64.3
                 Yes                            98    33.4                       Yes                   35   35.7
                 No                             195   66.6                       No




Nutritional Status Of Children ≤ 5 Years Old:
Anthropometric measurements required for the determination of malnutrition in children were
available for 161 children. However in the estimation of the various indices the sample size
varied from 129 to 139. The WHO Anthro Software used in the analysis rejected data from
children whose measurement yielded indicators that differed enough from others and flagged
them as outliers.

The age and gender distributions of the children are displayed in Table 8. Most (68%) children
fell between 0 and 3 years of age, but the age distribution of the children was fair enough to
allow for the estimation of the prevalence of malnutrition for each year under five years for some
indicators except for children under 3 years.




                                                                                                             10
Table 8. Age distribution of children
Age                        N                  % of   Gender        N          % of subjects
                                          subjects
0                         18                  11.3   Male         75                   46.6
1                         29                  18.1   Female       86                   53.4
2                         34                  21.3   Total        161                 100.0
3                         28                  17.5
4                         35                  21.9
5                         16                  10.0
Total                     160               100.0
Age-groups
<= 1 year                 47                 29.4
2 - 3 yrs                 62                 38.8
4 - 5 yrs                 51                 31.9
Total                     160               100.0
Further Age-groups
<= 3 years                109                68.1
> 3 years                 51                 31.9
Total                     160               100.0



Wasting (Acute malnutrition)
Of the 161 children whose anthropometric observations were available, estimates for
malnutrition were made using 139 observations. The observations for the remaining 22 children
were excluded because the WHO Anthro software is programmed to flag and exclude indices
that are too extreme as they are potentially erroneous. Compared to the WHO growth reference
standards children, the prevalence of wasting in children in this population were very high. The
prevalence of moderate and severe wasting was 15.9% and 10.6%, respectively. Children aged 0-
5 months and 6-11 months were the most affected. The deviation in the growth of children from
the growth references is clearer in Figure 2 below, which clearly shows that fewer study
children’s indicators fell within the 1- to 1 z-score range (normal nutritional status) compared to
the reference standards, while more fell in the tails of the curve (beyond -2 and +2) compared to
the reference graph. This distribution is also provided by age groups in Table 9, where it is clear
that children are born with adequate weight for height, only to slow down in growth between 6
and 35 months, and recover after 36 months of age. The decline in z-scores coincides with the
time (about 6 months) when infants are introduced to foods. Wasting reflects acute nutritional
insults, and thus suggest that children nutrient intake in the recent past was inadequate.

Despite the high prevalence of wasting, some children were at risk for overweight. The risk of
overweight, defined as weight-for-height Z-score ≥2 was estimated at 1.4% while the prevalence
of overweight (weight-for-height Z-score ≥3) was about 6.8%. Wasting and excessive body
weight co-exits in this population group and this is typical of most poor households worldwide.




                                                                                                11
                                                                                           Study
                                                                                           Children

                                                                    Cut off for at risk for overweight
                                                                    (2) & over weight (-3)
                        Cut off for moderate (-2)
                        & severe (-3) wasting




Figure 2. Distribution of Weight-for-age z-score and cut off points for malnutritin




Table 9. Characterization of Weight-for-height Z-scores and occurrence of wasting and
risk of overweight in children

Age groups     N        Percent children at various Weight-for-length/height Z-scores cut off         Mean
(months)                points%                                                                       Z-score
                        ≤ -3SD         ≤-2SD           ≥+1SD         ≥+2SD        ≥+3SD               Mean       SD
                        Severe         Moderate                      At risk for  At risk for
                        wasting        wasting                       overweight   obesity
Total (0-60)   139              10.6             15.9        19.7            11.4           6.8          -0.39        2.02
(0-5)               8           28.6                28.6     57.1           42.9             28.6         0.7         3.39
(6-11)             12           41.7                41.7     33.3             8.3              8.3       -0.92        2.76
(12-23)            37             8.8               11.8      5.9             5.9              5.9       -0.67        1.91
(24-35)            33             3.4                3.4     20.7             6.9              3.4       -0.24        1.57
(36-47)            22             4.5               18.2     22.7           13.6                 0        -0.6        1.67
(48-60)            27             3.8               15.4     19.2           15.4             11.5        0.08         2.02




                                                                                                                             12
Stunting (Chronic Malnutrition)
Stunting reflects chronic exposure to adverse nutrition and / or health factors with a bearing on
nutritional status. Children are considered to be stunted if their weight-for-age z-scores fell
below -2 (moderate stunting) or -3 (severe stunting). Observations show that 25.6% and 10.9%
of children in this study were moderately or severely stunted respectively (10). The prevalence of
moderate and severe stunting were higher in children 12 months and older. While stunting
seemed most prevalent in children 0-5 months, this cell had too few cases to be reliable. As was
the case with wasting, more boys were both severely and moderately stunted than girls. The
prevalence of stunting peaked in children aged 12- 23 months. Compared to wasting, stunting
was more common in older children, possibly reflective of the cumulative effect of nutrient
deficits over time. Stunting was also the most common form of malnutrition in children, clearly
indicating that children are chronically experiencing deficits in nutrients (Table 10) status.

Table 10: Prevalence of stunting in children
Age          N     Length/height-for-age (% children)
groups
(months)
                       < -3SD (severe)   < -2SD ( moderate)      Mean        SD
Total:       129                  10.9                   25.6        -0.91        2.13
(0-5)          6                  33.3                   33.3        -1.98        2.14
(6-11)        12                  16.7                   16.7        -0.28        3.08
(12-23)       33                  12.1                   33.3        -0.85        2.44
(24-35)       31                   6.5                   25.8           -1        1.95
(36-47)       21                   9.5                   23.8        -0.59        2.08
(48-60)       26                   7.7                   19.2        -1.16        1.34



Underweight: (low weight-for-age)

Weight-for-age z-scores compare children’s weight, with the weight of reference children of the
same age. It is a composite indicator of both acute and chronic malnutrition. In this study, the
prevalence of moderate and severe weight underweight was 18.7% and 7.2%, respectively for
both sexes. Underweight was widespread across most age groups, although children 48-60 and
24-35 years of age had higher prevalence than the sample average (Table 11). With the exception
of children 12-23 and 36-47 months, the prevalence of underweight increased with children’s
age. Between sexes, more males than females were underweight as in other parameters.

Table 11 Prevalence of moderate and severe underweight
Age groups         N       Percent children with Weight-for-age (%)
(months)
                           % < -3SD                   % < -2SD                    Mean           SD
                           ( severe underweight)      ( moderate underweight      z-scores
                                                      )
Total:             139                          7.2                      18.7             -0.9    1.51
(0-5)                8                            0                      12.5            -0.17     1.5
(6-11)              12                          8.3                      16.7             -1.1    1.06
(12-23)             37                          5.4                      13.5            -0.65     1.7
(24-35)             33                         12.1                      24.2            -1.25     1.5
(36-47)             22                          4.5                      13.6            -0.91    1.23



                                                                                                         13
(48-60)            27                         7.4                    25.9      -0.91   1.63


The Botswana National Nutrition Surveillance Program (BNNSS) provides monthly estimates
for underweight in children 0-5 years of age. These estimates are available for each region and
nationally. Compared to the national estimates of underweight of 5.1% (moderate and severe
underweight), children in the study villages fared worse. Furthermore, our estimates are also
higher when compared to the regional estimates provided by BNNSS for Okavango (2.3%) and
Ngami (1.7%) for the month of April (MOH, 2007). This pattern has persisted over the years
across several studies (Nnyepi, 2007: Maghoub unpublished). There are concerns that the
BNNSS may not be providing data that is reflective of all children in country in that BNNSS
data is clinic based. Thus it misses children who do not attend monthly growth monitoring; who
may different is ways that impact nutritional status from the regular attendees.


Feeding practices

Reasons for the high prevalence rates of malnutrition in Okavango region are not clear. Feeding
practices do not seem to differ much with the patterns observed in other parts of the country.
With regard to feeding, there were a considerable percentage of children who had never been
breastfed (17.6%), even among breastfed children about 3 out of 5 chidlren (64.4%) were
breastfed for less than the recommended duration for breastfeeding (2 years) and while 3.8%
were breastfed for 2 to 3 years.

Early introduction of fluids and supplementary feeds was common. The proportions of children
who were first introduced to other liquids (79.7%, i.e. n=114) and porridge/other cereals (61.3%,
n = 98) before 6 months (the recommended time for weaning a child) were high. Early
introduction of fluids and supplementary feeds may have influenced the nutritional status of
children. It is well known that early introduction of supplementary fluids/foods, often replace
nutrient-dense breast milk with foods/ fluids or low nutritive value.


Table 12: Age at first introduction fluids and supplementary foods

    Introduced to Liquids Other                  Introduced to Porridge/other
       than Infant Formula                                 cereals
age (months)      N             %                        N                  %

             0-1      16               12.6               7                  4.4
             2-3      42               29.4               5                  3.1
               4      52               36.4              73                 45.6
               5       4                2.8              13                  8.1
               6      26               18.2              56                 35.0
            7-12       3                2.1               6                  3.8
Total                143                100             160                  100




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Table 13: Child Feeding Practices
Who feeds the child?                                          N          %
 Childs feeds self
  self -feeds (not sharing plate)                            99        61.5
  self- feeds (sharing plate) with other children            17        10.6
  self- feeds (sharing plate) with mother/adult               2          1.2
Mother/adult (not sharing plate)                             28        17.4
N/A (not introduced to food yet)                              3          1.9
system missing                                               12          7.5
Total                                                       161         100




All but three children were already receiving supplementary foods. Most of the children 61.5 %(
n = 99) fed themselves and did not share a plate while some children fed themselves and also
shared a plate with other children (10.6%) or adults (1.2%). In addition to eating at household
meal times, children were also served foods from previous eating times. Very rarely were
children served food prepared specifically for them in between household eating times.

Role of fish in Children’ diet
The role of fish in children’ diet was assessed through a set of question designed to establish the
frequency with which children were fed fish and whether there were traditional fish dishes that
were specifically prepared for children. The results showed that fish was routinely used in
children’s meals. Parents reported that 88.2% of children had ever been fed fish. A large
proportion of the few children (9.6%) who had never been fed fish 40% had not been introduced
to solid foods. As expected fish consumption varied by season. Almost all children were reported
to have been fed a meal with fish at least weekly (42% everyday; 49% 3x/week and 48% once a
week) during low floods. During high floods the proportion of children reported to have had fish
at least once a week reduced to 79%. Despite seasonal variation in access to fish, most
respondents (82.9%) reported that fish contributed a lot to their household food supply. Given
that almost of the children were fed fish frequently, we could not evaluate the impact on the
nutritional status of children using data from this study. Rather it is recommended that a similar
nutrition assessment be carried out during the high flood season to establish the nutritional status
of children then and compare that with data obtained during the fishing season.


Diversity of Children’s Diets
The diets of most children were largely constituted of cereals. In the 24 hours preceding the
study the proportion of children fed sorghum porridge (86.7%), other porridges (44.0%) and
tsabana (30.6%) were very high. Tea and or coffee consumption was also common with 59.1%
of children reported to have taken it during the same period. The proportion of children fed tea
and or coffee were higher than that of children fed breastmilk (14.4%), or infant formula (1.9%).

Children’s fruits and vegetables intake was very low. Less than a third ( 31.3%) of children were
reported to have taken dark green leafy vegetables, followed by root vegetables (13.8%) and
fruits (7%) in the past 24 hours. Amongst protein foods, legumes were the most commonly
consumed food, with 33% of children reported to have eaten legumes in the past day followed by


                                                                                                 15
milk and other dairy products (30.6%), meats (29%), eggs (22.5%), and fish (4.4%). The low
intake of fish by children was rather surprising because children’s intake often mirrors that of
adults, and in this study 33% of households reported fish intake during the same period. Other
foods which were reported to have been consumed by large proportions of children include
sugary foods (68.1%) and fats and oil (40.0%).

 Overall there was low representation of fruits and vegetables, milk, and other dairy foods and
other protein foods in the children’s diet. While recommendations require that children should
consume several servings of milk and dairy products and fruits and vegetables daily, in this study
about 70% of children did not consume foods from any of these food groups in at least 24hours.
Given that fruits and vegetables are vehicles for numerous micronutrients, the low intake of
fruits and vegetables put children at risk for micronutrient deficiencies.



Discussion
Despite the vast resources that the Okavango Delta is renowned for, food insecurity in villages in
the panhandle remains a tremendous challenge. Not only are most (64.5%) households frequently
worried about their food supply, many have repeatedly resorted to eating foods of insufficient
variety (36.7%), quality, or have had to eat food that they would not eat if they had a choice
(21.1%). As is indicative of the seriousness of the situation, a sizeable proportion of households
have slept hungry (22%) or spent the whole day and night without food (14.5%) several times a
month. Anxiety about the adequacy of food supply, and experiences of intake of food of
insufficient quality and quantity are common strands in food insecure households across cultures
(Coates et al 2006), and that these experiences are observed in the Okavango panhandle at such
high proportions only serves to confirm the gravity of the problem. The disparity between
households who worry about their food supply and those experiencing insufficient (quality and
quantity) food may be indicative of a combination of transient and chronic food insecurity.
Frequently households employ food insecurity-triggered behaviors such as bartering, selling of
assets for food and reducing food intake to avoid or delay having to go without food (Nnyepi,
2007; Oldewage-Theron, et al, 2005). Thus it is logical that there would be more households who
worry about their food supply than those who eventually go without food.

Consistent with the high prevalence of moderately food insecure households, the quality of diets
in the Okavango is low. With more households reporting high intakes of cereals, condiments,
fats and oils and simple sugars, compared to fruits and vegetables, eggs, milk and dairy products,
meats and fish, the nutritive values of diets are likely to be poor in proteins and micronutrients.
Given the high intakes of cereals and fats and oils, it is possible that the diets may be adequate in
energy. Diets high in starchy foods and low in proteins, and micronutrients are not unique to the
Okavango area. Rather this is a problem that affects other regions in the country and some
subsets of the population as well (Aplogan et al., 1996; Clausen et al., 1996). The intake of foods
high in energy but low in other nutrients; such as fats and oils and simple sugars (as observed in
this study, is a known concern in food insecure households (Basiotis and Lino, 2003), which if
not addressed can lead to high prevalence of overweight and obesity and associated co-
morbidities amongst the food insecure (Nicholas et al., 2003).




                                                                                                  16
 Perhaps the one factor that pleasantly sets apart the Okavango Delta from other regions in the
country and is also reflective of households’ access to some riverine resources is the higher
consumption of fish in households. The value of fish in food insecure riparian households cannot
be understated, as some studies show that riparian households not only fish more to cope with
food shortages but also consider fish as their main coping strategy (Nnyepi et al, 2007).

A rather troubling situation that requires further scrutiny is the prevalence of food insecurity and
diets of low quality in households along a river system renowned for diverse indigenous foods
and non-food resources (Kgathi et al., 2006; Mbaiwa, 2004). With numerous edible indigenous
plants that are well accepted by the community (Paya, 2005) and of good nutritional value
(Medisa and Tshamekang, 1995; Taylor, 1981; Roodt, 1994), it is unclear whether the prevailing
food insecurity in the Okavango panhandle suggests that the extent of poverty in the Delta is so
grave that it renders the available indigenous food resources inadequate or there is lack of
concerted efforts to develop and weave indigenous foods into mainstream foods supply
mechanisms or both. Though not detailed, as data were collected only at village level,
households use of wild foods underscores their recognition of the contribution of wild foods to
their food supply. This was particularly evident in their characterization of some wild foods as
contributing more to their diets than others. This is further supported by household’s efforts in
preserving indigenous foods for use off season as reported in this study. Even though the impact
of storage methods such as the burying of tubers in shallower wet pits for easier access during
high floods, on their nutritive value still requires further study, these methods show that
households work hard to store foods for use off season. Observations of this nature suggest that
household would use simpler and possibly more effective methods of food preservation if they
are developed. And as such, the optimization of households’ methods of food preservation is a
development opportunity that must be exploited if readily available indigenous foods are to
feature more prominently in local diets. The development of such methods can also be coupled
with the improvement of local trade on indigenous food plants because observations show that
surplus home preserved foods are currently sold on the local markets. To support these
development opportunities there is need for studies that ascertain the direct use values of veldt
food products, the local markets for veldt foods, and the training needs of veldt food traders.

Consistent with the high rates of food insecurity in this region, was the high prevalence of
malnutrition in children and adults. There was strong evidence of the occurrence of acute and
chronic malnutrition in children. At 25.6% and 10.9% the prevalence of moderate and severe
chronic malnutrition in children in this area attests to the grave nature of chronic nutritional
insults in children. The social and economic impact of such high rates of chronic malnutrition
are known to include poor cognitive development and low school performance in children and
high risk of diet-related non-communicable diseases later in the children’s adult lives. Amongst
adults, chronic malnutrition is linked to low work output and poor pregnancy outcomes in
women of children bearing age.

Acute malnutrition that has been observed in this study at rates that are about five times higher
than the national rates are a serious concern too. That acute malnutrition (underweight) rates of
this magnitude (25 % (18.7% moderate underweight and 7.2% severe underweight) are observed
in children during the fishing season clearly indicates that children in this region face profound
nutrition and health challenges that must be addressed urgently. With the prevalence of acute



                                                                                                 17
malnutrition being more serious in children at the age when complimentary foods are introduced
(6-11 months) and when children should meet most of their nutrient needs through solid foods
(24-35 months), there is some indication that the quality of complementary food may be
inadequate. Amongst the different forms of malnutrition, underweight (low weight-for-age z-
scores) is one of the first indicators to recover when nutrition and health conditions improve.
With the assumption that during the fishing season the scarcity of fish and other wild produce is
reduced, the rates of underweight are expected to correspondingly expect. But in this study the
rates remained high. We are not aware of other potentiating factors but cannot exclude the
impact of factors such as HIV seropositivity and malarial infestations. These factors may also
have influenced the high rates (21.9 %) of underweight in adults, the percentage of adults with
illnesses lasting longer than 3 months (33.4%) and that of adults with prolonged illnesses who
were eventually hospitalized (64.3%).


Research and Policy Implications

Despite the availability of veldt food resources, most households in the Okavango are food
insecure and rely on inadequate diets for their survival and for feeding children. More research is
needed to identity ways in which rural households can be assisted to exploit the indigenous food
recourses to prevent food insecurity and improve the quality of their diets. Emphasis should
focus on the development of programs that increase access to diets with adequate protein foods,
fruits and vegetables and yet low in fats and oils. Given that households are already showing
interest in preserving indigenous foods for use off seasons, one important development
opportunity that is likely to bear fruit is the optimization of household methods of food
preservation and skills transfer to locals. Also, appropriate interventions which would involve
increased utilization of edible indigenous plant foods and year round supply of fish may be
useful towards alleviating the burden of food insecurity in this locality.

Programs should be coupled with a strong nutrition education component for the purposes of
addressing infant and young children feeding concerns. The large proportion of children fed tea
and coffee and cereal only complimentary foods is evidence to the fact that caregivers lack infant
and young children feeding knowledge and skills. Alongside this education should be the
transfer of skills for using locally available foods (including fish) to enhance the nutrient quality
of cereal-based porridges ( motogo).

It is common for many development programs to focus on undernutrition and infectious disease
as they are seen to be more urgent; however evidence from this study also suggests that
overweight is also a concern in both adults and children. As previously mentioned, stunting
(shortness in children) is known to be associated with overweight and obesity, diabetes and other
diet related non-communicable diseases later in the adult life. Thus given the high prevalence of
stunting in this population (children) failure to address issues of non-communicable diseases now
will be a big mistake because once established these conditions are difficult to reverse.




                                                                                                  18
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