NUTRITIONAL STATUS OF UNDERFIVE CHILDREN AND THEIR … · 2000-06-29 · TROPMED Regional Training...

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Draft version NUTRITIONAL STATUS OF UNDERFIVE CHILDREN AND THEIR MOTHERS IN SELECTED VILLAGES IN SUMBAWA AND DOMPU DISTRICT WEST NUSA TENGGARA A study carried out in the 12 IDT villages Ir. Maria C. Phan Ju Lan, MSc. Ir. Juliawati, MSc. Dr. Werner Schultink Dr. Rainer Gross Prof. Soemilah Sastroamidjojo SEAMEO-TROPMED Regional Center for Community Nutrition University of Indonesia Jakarta, June 1995

Transcript of NUTRITIONAL STATUS OF UNDERFIVE CHILDREN AND THEIR … · 2000-06-29 · TROPMED Regional Training...

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Draft version

NUTRITIONAL STATUS OF UNDERFIVE CHILDREN AND THEIR MOTHERS IN SELECTED VILLAGES IN SUMBAWA AND DOMPU DISTRICT WEST NUSA TENGGARA A study carried out in the 12 IDT villages Ir. Maria C. Phan Ju Lan, MSc. Ir. Juliawati, MSc. Dr. Werner Schultink Dr. Rainer Gross Prof. Soemilah Sastroamidjojo SEAMEO-TROPMED Regional Center for Community Nutrition University of Indonesia Jakarta, June 1995

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INTRODUCTION

This report presents the results of the cross-sectional nutrition survey conducted in 12 selected IDT-listed villages of Sumbawa and Dompu districts, West Nusa Tenggara on March 20 to April 5, 1995. This baseline survey was conducted by the MSc students and staff of the SEAMEO-TROPMED Regional Training Center for Community Nutrition at the University of Indonesia, Jakarta, in cooperation with PMD (SFDM, Support for Decentralized Measure), PPSTN (Program Pengembangan Swadaya Masyrakat Tani dan Nelayan/ Program to Promote Self-Help among Groups of Farmers and Fishermen), Selong, East lombok and GTZ. The main objective of the survey were as follows:

- to determine the nutritional status of the population specifically the children 0-59

months (underfive) and their mothers;

- to analyze the determinant factors of nutritional status of both children and mother; and

- to provide learning experience for the students on how to plan, carry out a field

survey, and analyzed a baseline data and recommend appropriate intervention programs.

Furthermore, the results of the fieldsurvey will serve as baseline for future planning of " Self-

help Promotion in Food Production and Land Conservation in Critical Rural Areas of Nusa Tenggara Barat and Nusa Tenggara Timur Project".

The nutritional status of a population can be used as an indicator of poverty situation of an area. Poverty can not be defined solely as a lack of financial income, but rather as a lack of access to basic resources such as food, water, health care, a good living environment, education and cultural life. As can be shown in the causal model (Figure 1), nutritional status is directly influenced by food intake and infectious diseases which in turn is influenced by poverty-related factors such as access to safe water, health care, educational level, living environment, etc. Poor population groups will therefore have an inadequate nutritional status. In this context a baseline survey is useful in identifying target groups for poverty alleviation measures.

To determine the nutritional situation in communities, it is not necessary to measure all members of the community, but it is possible to measure only an indicative sub-group which can be used as indicator of the whole population of a community. In this survey, the nutritional status of the children underfive years of age was used as an indicator of the health and nutritional situation of the villages. Children in this age category are most vulnerable to an insufficient diet and/or bad environment leading to poor health and nutritional status.

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Exposed to these conditions, growth of children are retarded which are easy to determine or measure. Therefore, the nutritional status of young children specifically the 0-59 months is considered a good indicator of the health and nutritional situation of the whole population.

West Nusa Tenggara province consists of six districts. The health and nutritional situation in West Nusa Tenggara is described by following: the prevalence rate of underweight (<80 % median Weight-for-age) of 0-60 months is 52.1 % for boys and 45.1 % for girls. Stunting (<90% median Height-for-age) is 31.6 % for boys and 26.9 % for girls. TGR and VGR is 38.8 % and 15.4 % respectively. Anemia in pregnant women is 71.3 % and 67.6 % for underfive. Infant mortality rate is 123/1000 alive birth (SUSENAS, 1992).

The study was carried out in 2 districts; Sumbawa and Dompu district. In Sumbawa, from the total 128 villages, 31 are categorized as poor villages with 28,975 people as poor villagers. While In Dompu, 11 villages from 43 villages in the whole, were categorized as poor with 7,908 as poor villagers.

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MATERIALS AND METHODS

Data collection was conducted on March 20-April 5, 1995 in the 12 villages of Sumbawa and Dompu. The villages were selected after consultation with PMD office and the selection of the villages were based on :

* villages (farming and coastal villages) included in the list of IDT villages which was

determined by Bappenas and Ministry of Interior * policy from Directorate General of PMD, Ministry of Interior * future planning of "Self-help Promotion in Food Production and Land Conservation

in Critical Rural Areas Project"

The villages selected to be surveyed and their classification are the following: District/Sub-district Village Classification 1. Sumbawa

1.1 Seteluk Mantar farming 1.2 Batulanteh Batudulang farming

Tepal farming 1.3 Plampang Teluk Santong fishing�

Sepayung farming 1.4 Alas Pulau Bungin fishing

2. Dompu

2.1 Kilo Tropo farming Pali farming and fishing Lasi farming Kiwu farming and fishing

2.2 Kempo Pulau Bajo fishing Tolokalo farming and fishing

� Not included in the list of IDT village in 1995

In each village, 30 households with children underfive were randomly selected using a complete listing of households with children underfive. These lists were provided by village heads and/or local health staff. The youngest and the second youngest underfive children in the households were taken as samples.

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Data collection was done by 6 teams, composed of 2 SEAMEO MSc students per team. Each team surveyed 2 villages from March 20 to April 5, 1995. One village was covered for a period of 5 days with the assistance of village leaders and/or health workers. Data were collected using the combined methods of interview, observation, clinical examination and anthropometric measurement. In addition to this, the students collected secondary data on demographic, agriculture and other pertinent data from the district/subdistrict/village level and conducted informal interview with village heads or elders and focus group discussion with the mothers (Result were attached in Annex 3). Data were collected using a structured questionnaire per household (see Annex 1). Data on the socio-economic condition, environment and sanitation, food consumption pattern, health information were collected by interview. Information on the living conditions, sanitation and home food production were obtained by observation. Clinical examination was done to check symptoms of Vitamin A deficiency (Bitot's spots, keratomalacia) and skin infections in children. Examination of visible goiter was done for both mother and children.

Anthropometric measurement consisted of taking weigh, height and mid-upper circumference of mother and children. Weight was taken using two types of electronic SECA scale; SECA 770 (old scale) and SECA 890 (new scale) and was recorded to the nearest 0.10 kg. The sensitivity and specificity of the new scale was also determined (Annex 2). Height of mothers and children above 2 years old was measured using a microtoise while subjects, barefoot, stood straight and back in contact with the wall. Length of children below 2 years was measured lying down using a baby board. Height and length was recorded to the nearest 0.1cm. MUAC was taken using Zerfas measuring tape which was wrapped on the mid-point of the shoulder blade and elbow. MUAC was recorded to the nearest 0.1 cm.

Data entry was done using EPI-INFO, version 6 computer program. Afterwhich, anthropomteric indices of weight, age, and height were converted to Z-scores (standard deviation (SD) of the median) using EPI-INFO version 5 and then compared with the National Center for Health Statistics (NCHS), USA reference population as recommended by WHO. Malnutrition was defined by Z-scores below -2.0 SD. This cut off point was used to categorized the following:

Underweight : weight for age Z-scores below -2.0 SD of reference population Stunting : height for age Z-scores below -2.0 SD of reference population, and Wasting : weight for height Z-scores below -2.0 SD of reference population

Further analysis was done using NCSS and SPSS (version 4.0.1.). Difference between

means of normally distributed data and categorical data was tested using analysis of variance and unpaired T-test. To correct the confounding effect of age, analysis of covariance was used. Difference between 2 categorical data was tested using Chi-square test.

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Results Table 1. General information of household by district _________________________________________________________________________________ District Sumbawa Dompu Total ________________________________________________________________________________ Sample Households 180 180 360 Underfive 235 237 472 Household members Family size 5.5 + 1.9 5.6 + 1.9 5.5 + 1.8 No of under five 1.3 + 0.5 1.3 + 0.5 1.3 + 0.5 No of children alive 2.7 + 1.8 3.3 + 1.9 3.0 + 1.9 No of earning member 2.2 + 0.8 1.6 + 0.7 1.9 + 0.7 Mother Age of mother (years) 28.3 + 6.2 29.6 + 6.2 29.0 + 6.2 No of pregnant women 21 21 42 (11.7%) No of lactating women 121 115 236 (65.6%) Household with children died<5 yrs 37 73 110 (30.5%) Household with children died<7 days 10 13 23 ( 6.4%) ________________________________________________________________________________ Average household size was about 5-6 members, with 3-4 of them being children. In both districts the maximum of household size was 11 persons. Number of earning member in District Dompu was quite smaller compare to Sumbawa district while number of children in Dompu was also bigger compare to Sumbawa District. About 99 % household head was the husband. Table 2. Education level of parents by district _______________________________________________________________________ Level of education Father (%) Mother (%) District Sumbawa Dompu Sumbawa Dompu

(n=180) (n=177) (n=180) (n=180) ________________________________________________________________________ <3 years 23.3 31.1 29.4 42.8 3-6 years 56.1 36.2 60.0 42.2 Secondary school 8.3 32.2 6.7 15.0 Higher education 12.2 0.5 3.9 0 _________________________________________________________________________ Majority of parents in Sumbawa (56 % of fathers and 60 % mothers) had education 3-6 years, while in Dompu 36 % of fathers had education 3-6 years. About 12.7 % out of 360 mothers followed KEJAR PAKET A (Government program as informal education for illiteracy eradication). About 97% of households were Moslems and 3% were Hindus. While the majority of households in

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Sumbawa were belong to Samawa (Sumbawa) ethnic and Bima ethnic for majorities people in Dompu District (Table 3). Couples belong to Bajo ethnic mainly live in Pulau Bungin (83%) and Pulau Bajo (97%), while those belong to Bima ethnic were living in Dompu district. Specifically for Teluk Santung, there were more than four ethnics live there; mainly Bugis people. Table 3. Frequency distribution of parents' ethnicity by district ________________________________________________________________________ Ethnicity Father (%) Mother (%)

Sumbawa Dompu Sumbawa Dompu n=180 n=177 n=180 n=180

________________________________________________________________________ Samawa 67.2 0 66.1 0 Bajau 15.6 16.4 21.2 15.6 Bugis 8.9 0 9.4 0.6 Sasak 3.9 0 4.4 0 Bima 1.7 76.3 0 77.8 Bali 0 5.6 0 5.6 Others 2.8 1.7 2.8 0.6 _________________________________________________________________________ About 23 % out of 300 households were actively participated in IDT program, the activity of the program was described in Table 4. Animal raising (horse) was carried out in Tepal and Batudulang village, fishery activities (buying fishing-net etc) was carried out in Pulau Bungin and Pulau Bajo. Table 4. Frequency distribution type of IDT activity by district _______________________________________________________ Type of activity Sumbawa Dompu Total ________________________________________________________ Staple crop - 1 1 Cash crop 3 - 3 Food crop 1 1 2 Fishery 1 10 11 Animal 23 14 37 Food stall 1 1 2 Vendor 5 3 8 Handycraft - 1 1 Other 3 - 3 ________________________________________________________ Total 37 31 68 _________________________________________________________

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Table 5. Main cccupation of father by district (n=356) ______________________________________________________________________ Type of occupation Sumbawa % (n=179) Dompu % (n=177) Total % ______________________________________________________________________ No occupation 0.6 - 0.6 Subsistence farmer 63.1 59.3 61.2 Daily paid farmer 0.6 6.2 3.4 Fishermen 19.6 15.3 17.4 Fishermen (without boat) 5.6 2.3 3.9 Fishermen (rent boat) 3.4 6.2 4.8 Civil servant 2.8 4.5 3.7 Trader 0.6 1.7 1.1 Others 3.9 4.5 4.0 ________________________________________________________________________

The majority of the head of households were farmers, and in Teluk Santong, Pulau Bungin, Pulau Bajo village large part of the population were fishermen. Out of 262 households, 72 % owned the land. About 54 % households in Pali village did not own land. Generally they cultivated the land with rice which was mainly for own consumption. Cash crop such as coffee was found in Batudulang and Tepal village. Table 6. Frequency Distribution of Status of Land Ownership _______________________________________________________________________________ Ownership status Sumba % (n=122) Dompu % (n=140) Total % (n=262)* ________________________________________________________________________________ Own all 77.9 67.9 72.5 Rent 8.2 23.6 16.4 Other 12.3 1.4 6.5 No Land 1.6 6.4 4.2 ________________________________________________________________________________ * Not included fishermen households in P. Bungin, P. Bajo and Teluk Santong. Table 7. Frequency distribution of household appliances ownership by disctrict ____________________________________________________________________ Type of goods Sumbawa (%) Dompu (%) Total (%)

n=180 n=180 n=360 ___________________________________________________________________ Radio 43.3 25.0 34.2 Electricity 23.3 9.4 16.4 Television 12.8 0.6 6.7 Parabola 5.0 0 2.5 Bicycle 4.4 11.1 7.8 Motorcycle 0.6 0 0.3 Refrigerator 2.2 0 1.1 ____________________________________________________________________ Electricity was available in Batudulang, Telok Santong, Sepayung, Pulau Bungin, and Pali. Television set was found mostly in Teluk Santong, also refrigerator and parabola.

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Table 8. Frequency distribution of cultivated crops and their usage _______________________________________________________________________ Crops Consumption Sale Both Not cultivated

(%) (%) (%) (%) _______________________________________________________________________ Rice, sawah (n=219) 38.8 0 5.5 55.8 Rice,ladang (n=255) 52.9 0.4 0.8 45.9 Maize (n=245) 41.6 1.6 0.8 55.9 Sweetpotato (n=228) 11.4 0.4 0.4 87.7 Groundnut (n=227) 3.5 1.3 0.9 94.2 Nuts (n=231) 4.3 35.1 3.9 56.7 Others (n=231) 1.7 14.7 10.0 73.6 _______________________________________________________________________ Table 9. Frequency distribution of possession of livestock and their usage ________________________________________________________________________ Animal Consumption Sale Both Physical Work ________________________________________________________________________ Goat (n=76) 15.8 61.8 14.5 7.9 Cow (n=42) - 38.1 - 59.5 Buffalo (n=45) - 15.6 2.2 80.0 Chicken (n=135) 34.8 33.3 24.4 - Horse (n=48) - 4.2 - 83.3 ________________________________________________________________________ Chicken were the most widely livestock for own consumption, while goat was mainly for sale. Horse, buffalo and cow were mainly used for their physical work. Horse were mainly raised by people in mountaneus villages (Mantar, Tepal, Batudulang, and Tropo) which also helpful as transportation means. Almost all of the livestocks were uncage. Figure 2 shows similar trend of food shortage by district. During rainy season, there was increasing number of households experienced food shortage with the peak in January for both districts. Their harvest was only sufficient for 5 months during the year. During the survey, it was time of preharvesting, which influenced food availability in the household level. While fish shortage was started from October up to February (Figure 3).

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Table 10. Means of duration of food shortage by village ═════════════════════════════════════════════════════════════════ Village Duration of Food Shortage n Mean±sd (months) _________________________________________________________________ Sumbawa district 180 3.12 ± 2.36* Mantar 30 2.13 ± 2.44 Batudulang 30 2.87 ± 1.91 Tepal 30 3.30 ± 1.51 Teluk Santong 30 2.33 ± 2.60 Sepayung 30 5.73 ± 2.39 Pulau Bungin 30 2.33 ± 0.66 Dompu district 180 4.40 ± 2.67 Tropo 30 4.13 ± 1.68 Pali 30 4.50 ± 3.50 Lasi 30 2.93 ± 0.98 Kiwu 30 3.77 ± 1.41 Pulau Bajo 30 3.93 ± 1.57 Tolo Kalo 30 7.13 ± 3.58 __________________________________________________________________ *)significant different between district, p<0.001, T-test ═════════════════════════════════════════════════════════════════ Hygienic situation and living conditions Table 11. Frequency distribution of place for defecaeting (n=360) _________________________________________________________________________ Place Sumbawa % (n=180) Dompu % (n=180) Total _________________________________________________________________________ Forest/open field 48.9 11.7 30.3 Sea 27.2 26.1 26.7 River 13.3 22.8 18.1 Latrine 9.4 39.4 24.4 Burried 0.6 0 0.3 Other 0.6 0 0.6 ________________________________________________________________________ About 30 % of household were used to defecaete in the field (people in Mantar, Tepal), and about 18 % in the river (in Tropo, and Sepayung). Mostly people in Pali and Kiwu got drinking water from hand pump. While in Lasi, people got drinking water from river. Both fishing villages Pulau Bungin and Pulau Bajo got their water supply from water tank built by funding from ASWS (Australian Sanitation Water Supply) project.

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Table 12. Place for getting drinking water by district __________________________________________________________________ Source Sumbawa(%) Dompu(%) Total (%)

n=180 n=180 n=180 __________________________________________________________________ Cemented well 38.9 43.9 41.4 Spring 30.0 - 15.0 Water tank 15.0 17.8 16.4 Hand pump 0 23.9 11.9 Non cemented well 8.9 11.7 10.3 Water vendor 5.6 0 2.8 River 0.6 2.8 1.7 Other 1.1 0 0.6 ___________________________________________________________________ Table 13. Place for disposing garbage by district __________________________________________________________________ Place Sumbawa(%) Dompu(%) Total (%)

n=180 n=180 n=180 __________________________________________________________________ Field 38.3 50.0 44.2 Sea 29.4 24.4 26.9 Forest 15.0 2.8 8.9 River 8.9 7.2 8.1 Burnt 3.3 8.3 5.8 Burried 0.6 6.1 3.3 Garbage disposal area 4.4 1.1 2.8 __________________________________________________________________ Majority people in Tepal (70 %) disposed their garbage to the forest. People in Batudulang, Sepayung, and Kiwu disposed garbage in the river. While people who stayed on the island (Pulau Bungin and Pulau Bajo) and Teluk Santong were used to dispose garbage to the sea. Table 14. Frequency distribution of material of housing by district ___________________________________________________________________________ Material Wall (%) Floor (%)

Sumbawa Dompu Sumbawa Dompu n=180 n=180 n=180 n=180

___________________________________________________________________________ Wood 26.7 72.2 64.4 80.6 Bamboo 70.0 17.8 26.7 5.0 Cement 0.6 6.7 2.8 5.0 Stone 1.1 1.1 0.6 0 Corrugated Iron 1.7 0 0 0 Palm Leaves 0 2.2 0 0 Soil 0 0 5.6 9.4 ___________________________________________________________________________ About 70 % wall of the housing in Dompu district was made of wood while in Sumbawa only 26.7 % and majority of the house was made from bamboo as the materials of the wall.

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Table 15. Frequncy distribution of food consumption frequency (n=360) Food

Several/day

Weekly

Several/year

Never

Staple food: Rice

96.1

1.1

2..8

0

Cassavaa

3.1

11.5

62

23.9

Maize

20.6

10.3

59.7

9.3

Tubersb

2.3

4.4

61.7

31.1

Plant protein:legumea

4.4

20.5

51.6

23.1

Tofu

2.2

18.3

14.7

64.7

Tempe

1.4

18.3

15.0

65.3

Groundnuta

8.0

25.9

47.0

18.9

Animal protein:egg

4.5

57.3

28.4

20.0

Chicken

0.3

14.5

66.7

18.6

Beef

1.2

8.3

44.1

46.4

Goat

0

1.7

70.6

27.8

Horseb

0

0.3

17.2

81.9

Deerd

0

3.9

43.8

51.1

Fishe

65.2

28.6

4.0

0

Vegetable:GLVf

69.2

25.8

1.2

0

Carrota

0.6

5.3

5.0

88.9

Cabbagea

0.6

11.7

37.5

50.0

Fruits:bananaa

7.5

60.2

22.7

9.2

Papajaa

4.7

43.9

35.9

15.3

Orangea

5.5

19.7

48.6

25.8

Jackfruita

2.8

8.3

65.9

22.8

Milk: cowmilk

0

0.6

1.2

98.3

Powder milk

0.6

1.1

3.4

95

Condensed milk

7.2

6.6

7.8

78.3

Oil

29.2

57.2

4.2

9.4

Sugarb

51.1

30.0

7.8

10.6

Snack

18.6

42..5

13.9

24.2

Crackersb

16.7

36.6

31.4

34.4

Note: a:1 hh no answer b:2 hhs no anwer c:3 hhs no answer d:4 hhs no answer e:8 hhs no answer f:14 hhs no answer

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Rice as the main staple food was consumed more than once per day by 96.1 % of the households. While cassava were less important and were consumsed seasonally. Maize was consumed as staple food several times per day (20.6 %) by households belong to Balinese ethnic in Tolokalo village. Fresh fish was the most important animal protein source. It was consumed at least once per day by 65.2 % households and 28.6 % of households consumed it on a weekly basis. Plant protein source such as tempe and tofu were not common food in the survey area. Second animal protein source was egg which was consumed by 57.3 % households on weekly basis. Green leavy vegetable (GLV) was consumed once or several times daily by 69,2 % of households. The most common GLV was 'daun kelor' and cassava leaves. Oil was consumed daily by 29.2 % households. While sugar was also important energy source was consumed by 51.1 % of households on daily basis and 30 % on weekly basis. Table 16. Frequency distribution of place for buying food ______________________________________________________________________________ Place Sumbawa Dompu Total

% (n=180) % (n=180) % (n=360) ______________________________________________________________________________ Warung 51.7 59.4 55.6 Market in neighbouring village 33.3 19.4 26.4 Food vendor 3.3 14.4 8.9 ________________________________________________________________________________ About 60 % households bought food in the local warung, this might influence the variety of the food consumption. 60 % mothers in Sumbawa Besar (n=180) and 68.9 % in Dompu (n=180) said that fathers were given first priority of meals at home, and 5.6 % and 11.7 % for children in Sumbawa Besar and Dompu respectively. Table 17. Frequency distribution of childcare by district ______________________________________________________ Person who take care Sumbawa Dompu

% (n=180) % (n=180) _______________________________________________________ Mother 72.8 84.4 Grandparents 10.0 5.6 Sister/brother 5.0 6,1 Father 0.6 0.3 Both parents 10.0 2.8 Relatives 1.7 1.1 _______________________________________________________ Mother was the person who take care of children either in Sumbawa or Dompu district (Table 17). In Mantar, Tepal, Sepayung only 63 % mothers take care of children.

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General health and nutritional status of mothers At the time of survey 14.4 % out of 360 mothers were pregnant. 83.3 % of mothers did not experience child birth spacing less than two years while 10.0 % of mothers experienced having one birth spacing less than two years and the others experienced it more than once. In Sumbawa Besar 20.5 % of mothers (n=180) had one or more underfive years children death while in Dompu there were 40 % of mothers experienced one or more underfive children passed away. The number of children who died was largest in Tolokalo and Pali where from the 30 interviewed households experienced a total of 16 cases and 15 cases respectively. Out of 360 households, there were 23 cases neonatal death. 90.2 % of mothers were assisted by traditional birth attendant during delivery her child. 11.1 % out of 180 mothers in Sumbawa and 7.8 % of mothers in Dompu experienced miscarriage. 4.7 % mothers had a visible swollen thyroid gland . Most cases occured (out of 30 households) in the mountaneous villages Batudulang (n=3), Tepal (n=7) and Sepayung (n=6). This indicates that goiter still is a problem in the mountaneous villages of the survey area. The nutritional status of mothers differed between villages (p=0.01). There was about 10 % of mothers had BMI value lower than 17. The worst situation was in Kiwu village (there was 52 % of mothers had BMI<18.5), followed by Tropo, and Sepayung. This data was also supported by means value of BMI which was also quite different by village. Furthermore, in Tropo, there was a high number of undernourish mother based on categorization of MUAC measurement. Table 18. Frequency distribution of nutritional status of non pregnant mothers by village _________________________________________________________________________________ VILLAGE N Weight (kg) Height(cm) BMI BMI<18.50 ________________________________________________________________________(%)______ District Sumbawa Besar:154 45.18 + 7.39 149.59 + 5.21& 20.12 + 2.67* 27.9 Mantar 24 44.52 + 7.65 149.63 + 5.96 19.79 + 2.55 37.5 Batudulang 27 45.13 + 6.28 148.57 + 4.49 20.42 + 2.58 25.9 Tepal 29 42.61 + 4.39 147.97 + 4.37 19.42 + 1.24 24.1 Teluk Santung 24 47.74 + 8.91 149.56 + 4.01 21.30 + 3.53 16.7 Sepayung 25 43.87 + 7.15 150.45 + 6.57 19.28 + 2.21 44.0 Pulau Bungin 25 47.72 + 8.72 151.70 + 5.11 20.66 + 3.22 20.0 District Dompu: 154 44.87+ 6.02 151.13 + 4.88 19.62+ 2.34 31.8 Tropo 26 42.83 + 5.01 150.41 + 4.64 18.91 + 1.92 46.2 Pali 26 46.76 + 5.56 151.95 + 5.02 20.25 + 2.33 19.2 Lasi 25 46.12 + 4.88 151.04 + 4.11 20.22 + 2.10 20.0 Kiwu 25 43.09 + 5.72 151.48 + 6.35 18.78 + 2.34 52.0 Pulau Bajo 26 45.34 + 8.83 151.63 + 3.88 19.65 + 3.20 42.3 Tolo Kalo 26 45.03 + 4.54 150.27 + 5.14 19.93 + 1.63 11.5 All villages 308 45.02 + 6.73** 150.36 + 5.09++ 19.88 + 2.52@ 29.9# ____________________________________________________________________________ Note: * significant between districts p=0.08 ** significant between villages p=0.05

++ significant between villages p=0.07 @ significant between villages p=0.01 # significant between villages p=0,01 & significant between districts p=0.01

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Table 19 . Nutritional status of mother (expressed by MUAC measurement) ____________________________________________________________________________ VILLAGE N MUAC (cm) MUAC<22.0 cm (%) ____________________________________________________________________________ District Sumbawa Besar: 180 24.22 + 2.73 20.6 Mantar 30 23.76 + 2.04 13.3 Batudulang 30 25.24 + 2.56 6.7 Tepal 30 22.43 + 1.23 36.7 Teluk Santong 30 24.16 + 3.49 10.0 Sepayung 30 24.08 + 2.16 16.7 Pulau Bungin 30 23.11 + 3.27 26.7 District Dompu: 180 23.62 + 2.36 26.1 Tropo 30 22.70 + 1.87 40.0 Pali 30 25.05 + 2.35 10.0 Lasi 30 24.36 + 2.36 20.0 Kiwu 30 22.75 + 1.89 26.7 Pulau Bajo 30 24.52 + 8.14 36.7 Tolo Kalo 30 23.69 + 1.84 13.3 All villages 360 23.92 + 2.56* 21.4* ____________________________________________________________________________ Note: * significant different between villages p=0.00 Health situation of children Of the total of 180 households, 104 households and 5 households had 2 and 3 underfive children respectively. The sex distribution of the children was 52.3 % boys and 47.7 % girls out of 472 children. There was no difference in nutritional status between gender. Only 39 % of the surveyed children possessed a KMS card. In the villages Batudulang and Lasi the coverage of health system were good quite good, this can be shown by 91.4 % and 88.9 respectively in both villages possessed KMS card. While in Tepal only 1 child possessed KMS card. The immunization coverage of the children is shown in Table 20. The coverage of BCG vaccination seems higher than the coverage of other vaccinations. It has to be remarked however that vaccination with the other types of vaccinations can be checked by looking whether the child has a scar, while the other types of vaccinations can only be checked through the KMS card. The coverage of BCG and DPT/Polio vaccination in Dompu was higher compare to Sumbawa District.

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Table 20. Frequency distribution of immunization coverage in underfive children ____________________________________________________________________ Immunization Sumbawa Dompu Total

% (n) % (n) % (n) _____________________________________________________________________ BCG 40.0 (90) 64.8 (147) 52.4(237) DPT/Polio 24.9 (54) 31.7 ( 71) 28.3(125) Measle 28.9 (55) 27.6 ( 56) 28.2(111) _______________________________________________________________________ Table 21. Frequency distribution of diseases prevalence in underfive children ___________________________________________________________________ Disease Sumbawa Dompu Total

% (n=235) % (n=237) % (n=472) ___________________________________________________________________ Point Diarrhea 8.1 16.9 12.5 Period Diarrhea 19.1 19.8 19.5 Period ARI 49.4 53.2 51.3 Point ARI 48.5 56.1 52.3 ____________________________________________________________________ About half (51.3 %) of the children suffered from respiratory infections at the time and 52,3 % of children the previous week of the survey. The prevalence of diarrhea at the time of the survey in Dompu district was twice compare to Sumbawa district. Breastfeeding and additional feeding About 56.8 % out of 472 children were braestfed at the time of the survey, their mean of age was 16.8 + 13.3 months. About 96.2 % of children below 6 months of age (n=79) were breastfed, and the majority of the children aged 12-18 months at the time of the survey were also still breastfed. Only 8 % of the children who were not breastfed anymore, stopped receiving breastmilk at their age of 11 months, while the rest stopped breastfed up to 2 years. Table 22. Frequency distribution of age when children receive additional food __________________________________________________________________ Age Sumbawa Dompu Total (months) % (n=217) % (n=216) %(n=433) ___________________________________________________________________ 0-3 54.4 61.6 58.0 4-6 25.8 14.8 20.3 7-12 13.4 10.6 12.0 >12 6.0 12.5 9.2 _______________________________________________________________________

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Almost half of the surveyed children was receiving additional food at the age of 0 to 3 months. For the first 4 to 6 months of life, breastmilk provides all necessary nutrients and fluids fo a baby. Introduction of additional food in early age, increases the risk of infection. After 4 to 6 months of age a child does need additional foods. Table 23. Frequency distribution of time when breastfeeding was started after birth of the child _____________________________________________________________________________ Time after birth Sumbawa Dompu Total

% (n=235) % (n=237) % (n=472) ______________________________________________________________________________ 0-4 hours 71.9 68.8 70.3 5-12 hours 1.7 1.7 1.7 >12 hours 25.5 29.5 27.5 Do not know 0.8 0 0.2 ______________________________________________________________________________ The first breastmilk (colostrum) is important for a child because it contains antibodies and consists of a nutrient composition especially for absorption by the newly born. Therefore it is important that breastfeeding should be started immediately after birth. In this survey 70. 3 % children was breastfed right after delivery. Table 24. Frequency distribution of food consumption of children > 12 months

Items

Several times /once per day

Several times/month

Several times/year

Never

Staple food

96.5

0.9

0

2.6

Plant protein

6.9

35.3

19.5

38.4

Animal protein

54.8

14.6

17.1

13.5

Vegetable

68.5

20.7

0

10.9

Fruit

8.6

50.1

25.9

15.5

Milk formula

6.3

3.4

0.9

89.4

Breastmilk

43.5

0.6

0.3

55.6

Oil

27.8

44.1

2.9

25.2

Sugar

40.4

33.3

2.0

24.4

Snack

34.1

43

8.0

14.9

Crackers

32.1

32.1

8.3

27.5

Other

2.3

0.3

0

97.4

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Table 24 shows the main meal of the children older than 12 months were staple food, vegetables and fish as source of animal protein. Nutritional Status of children Table 25 shows information on the mean height and weight of the children related to their age, and weight to their height in comparison with international reference values (NCHS). There was significant differences in nutritional status (WAZ and HAZ) between villages. The low average height-for-age in Mantar village stands out, which is in line with the high rate (61.5 %) of children with a SD score below -2 (Table 26 ). While in Tropo the high rate of weight-for-height SD score below -2 (24.4 %) was in line with the low average weight-for-height SD score. Table 25. Nutritional status of children according to anthropometric indicators

(expressed as Mean+SD of z-score) by village _______________________________________________________________________

WAZ HAZ WHZ VILLAGE N Mean+SD Mean+SD Mean+SD _______________________________________________________________________ District Sumbawa : 235 -1.78+1.13 -1.84+ 1.44 -0.78+0.88

1 Mantar 39 -2.18+0.96 -2.52+ 1.26 -0.93+0.91 2 Batu Dulang 35 -1.70+0.71 -1.69+ 1.02 -0.87+0.68 3 Tepal 30 -1.88+1.12 -2.07+ 1.54 -0.69+0.96 4 Teluk Santung 41 -1.89+0.95 -1.81+ 1.59 -1.05+0.84 5 Sepayung 42 -1.65+1.32 -1.56+ 1.41 -0.97+0.88 6 Pulau Bungin 48 -1.50+1.38 -1.49+ 1.54 -0.76+0.97 District Dompu: 234 -1.89+1.19 -1.78+ 1.46 -1.03+0.96* 1 Tropo 41 -2.05+1.14 -1.80+ 1.09 -1.22+1.02 2 Pali 43 -1.60+1.17 -1.55+ 1.34 -0.79+1.02 3 Lasi 36 -1.58+1.43 -1.36+ 2.07 -0.99+0.99 4 Kiwu 34 -1.92+1.12 -1.93+ 1.29 -0.92+1.02 5 Pulau Bajo 38 -2.21+0.99 -2.02+ 1.15 -1.19+0.80 6 Tolo Kalo 42 -2.00+1.23 -2.02+ 1.62 -1.06+0.89 All villages 469 -1.84+1.16++ -1.81+ 1.45** -0.96+0.93 _______________________________________________________________________ Note: * significant between district p<0.10 ++ significant between villages p<0.10 ** significant between villages p<0.05

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Table 26. Frequency distribution of prevalence of undernutrition (z-score <-2.0) among children _______________________________________________________________________________ VILLAGE N WASTING (%) UNDERWEIGHT (%) STUNTING (%) _______________________________________________________________________________ District Sumbawa 235 7.2 48.5 45.1 1 Mantar 39 10.3 66.7 61.5 2 Batu Dulang 35 5.7 34.3 34.3 3 Tepal 30 6.7 40.0 50.0 4 Teluk Santong 41 4.9 48.8 48.8 5 Sepayung 42 7.1 54.8 45.2 6 Pulau Bungin 48 8.3 43.8 33.3 District Dompu: 234 14.1* 52.1 44.4 1 Tropo 41 24.4 61 41.5 2 Pali 43 7.0 41.9 34.9 3 Lasi 36 16.7 44.4 38.9 4 Kiwu 34 11.8 52.9 47.1 5 Pulau Bajo 38 13.2 60.5 55.3 6 Tolo Kalo 42 11.9 52.4 50.0 All villages 469 10.7 50.3 44.8 _______________________________________________________________________ * significant different between district p<0.05 Table 27 . Frequency distribution of nutritional status of children >=12 months (expressed by MUAC measurement) ____________________________________________________________________________ VILLAGE N MUAC (cm) MUAC<12.5 cm (%) ____________________________________________________________________________ District Sumbawa: 174 14.61 + 1.21 3.4 Mantar 30 14.76 + 0.97 0 Batudulang 28 15.41 + 1.03 0 Tepal 19 14.49 + 1.05 5.3 Teluk Santung 35 14.17 + 1.34 8.6 Sepayung 31 14.21 + 0.93 0 Pulau Bungin 31 14.67 + 1.43 6.5 District Dompu: 172 14.15 + 1.30** 11.6@ Tropo 31 13.98 + 1.55 25.8 Pali 33 14.80 + 1.21 0 Lasi 29 14.32 + 1.25 10.3 Kiwu 22 13.93 + 0.98 9.1 Pulau Bajo 26 13.95 + 1.16 11.5 Tolo Kalo 31 13.78 + 1.31 12.9 All villages 346 14.38 + 1.28* 7.5# ____________________________________________________________________________ Note: @ significant different between districts p<0.05 ** significant different between districts p<0.05 # significant different between villages p<0.05 Figure 4, 5, and 6 shows the distribution of weight-for-age, height-for-age, weight-for-height SD

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score for the surveyed children compare to the reference. It can be shown that in the three figures, the distribution of SD score was shifted to the left. While in the children below 6 months and 12 months the distribution of height-for-age SD score was skewed to the left (Figure 7). Table 28 . Frequency distribution of nutritional status by sex and subdistrict ___________________________________________________________________________ VILLAGE N WAZ HAZ WHZ

Mean+SD Mean+SD Mean+SD ___________________________________________________________________________ All villages: 469 -1.84+1.16 -1.81+ 1.45 -0.96+0.93 Male 246 -1.86+1.15 -1.85+ 1.47 -0.97+0.97 Female 223 -1.82+1.18 -1.76+ 1.44 -0.94+0.88 District Sumbawa : 235 -1.78+1.13 -1.84+ 1.44 -0.78+0.88 Male 120 -1.95+1.06* -2.07+ 1.40_ -1.84+ 1.44 Female 115 -1.61+1.17 -1.60+ 1.45 -0.81+0.89 District Dompu: 234 -1.89+1.19 -1.81+ 1.45 -1.03+0.96 Male 126 -1.77+1.22� -1.64+ 1.50 -0.98+1.06 Female 108 -2.04+1.16 -1.94+ 1.41 -1.08+0.85 ____________________________________________________________________________ Note: * significant at p<0.05 _ significant at p<0.05 � significant at p<0.10

The nutritional status of male children in Sumbawa district worse than female children, while in Dompu district male children had better means value of weight-for-age and height-for-age z-score compare to female children. Table 29. Frequency distribution of nutritional status by age group ___________________________________________________________________________ Age group (mos) HAZ WHZ WAZ

n Mean + SD Mean + SD Mean + SD ____________________________________________________________________________ <6 79 -0.51+ 1.16 -0.17+ 0.92 -0.48+ 0.98 6-12 55 -1.09+ 1.38 -0.84+ 1.03 -1.53+ 1.05 12-18 46 -1.97+ 1.13 -1.61+ 0.58 -2.39+ 0.78 18-24 49 -2.38+ 1.56 -1.15+ 0.91 -2.28+ 1.19 24-36 99 -2.06+ 1.15 -1.23+ 0.74 -2.39+ 0.78 >36 141 -2.39+ 1.32 -0.97+ 0.80 -2.28+ 1.19 Total 469 ____________________________________________________________________________ The means value of weight-for-age, height-for-age and weight-for-height SD score in children less than 1 year was quite good compare to the older one. These young children are all breastfed which covered their nutritional needs and protected against infectiouse diseases. Only when children get addition of repeated illnesses, the nutritional status getting worst.

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Table 30. Relationship between nutritional status and BMI of non pregnant mothers ──────────────────────────────────────────────────────────────────────── BMI n WHZ * WAZ** ════════════════════════════════════════════════════════════════════════ < 17 25 -1.36± 0.81 -2.16± 1.11 >17-18.5 99 -1.12± 1.02 -2.04± 1.21 >18.5 286 -0.86± 0.99 -1.67± 1.22 ──────────────────────────────────────────────────────────────────────── Total 410 -1.79± 1.22 -0.95± 0.99 ──────────────────────────────────────────────────────────────────────── *) p=0.03 (significant different at p<0.05, ANOVA after controlling village variable) **) p=0.02 (significant different at p<0.05, ANOVA after controlling age and village variables) DETERMINANTS OF NUTRITIONAL STATUS Factors related to socio-economic

Tabel 31. Relationship between nutritional status and number of money earner ───────────────────────────────────────────────────────────────────────

Money-earner n WAZ* WHZ_ ══════════════════════════════════════════════════════════════════════ 1 person 143 -1.8 ± 1.3 -1.0 ± 1.0 2 person 269 -2.0 ± 1.2 -1.0 ± 1.0 3 person 38 -1.3 ± 1.0 -0.6 ± 0.9 > 3 person 19 -1.3 ± 1.1 -5.3 ± 1.1 ──────────────────────────────────────────────────────────────────────── Total 469 ────────────────────────────────────────────────────────────────────────

*) p = 0.093 (significant different at p < 0.1, ANOVA after controlling age and village variables) _) p = 0.066 (significant different at p < 0.1, ANOVA after controlling village variables)

Table 31 shows that the more number of money earner the better the means value of weight-for-age z score.

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Table 32. Relationship between nutritional status (MUAC) of the children** and father's ethnicity ──────────────────────────────────────────────────────────────────────── Father's Ethnicity n MUAC* ═══════════════════════════════════════════════════════════════════════

Bajau 56 14.3 ± 1.3 Bali 10 14.6 ± 1.3 Bima 135 14.1 ± 1.4 Sumbawa 108 14.7 ± 1.1 Bugis 21 14.5 ± 1.1 Others 16 13.7 ± 2.1

──────────────────────────────────────────────────────────────────────── Total 346

──────────────────────────────────────────────────────────────────────── *) p = 0.009 (significant different at p < 0.01 , ANOVA after controlling village variables)

**) MUAC of children equal or more than 12 months

Children more than 12 months belong to Bima ethnicity were likely had lower nutritional status in terms means of MUAC value than those from Sumbawa or Bali ethnicity.

Table 33. Relationship between nutritional status (WHZ) and mother's education ──────────────────────────────────────────────────────────────────────── Mother's Education n WHZ* ═══════════════════════════════════════════════════════════════════════ 0 - 3 yrs of schooling 169 -1.1 ± 1.0 >3- 6 yrs of schooling 240 -0.9 ± 1.0 >6- 9 yrs of schooling 40 -1.0 ± 0.8 > 9 yrs of schooling 20 -0.5 ± 0.8 ────────────────────────────────────────────────────────────────────────

Total 469 ──────────────────────────────────────────────────────────────────────── *) p = 0.007 (significant different at p < 0.01 , ANOVA after controlling village variables)

Children whose mother having education more than 9 years of schooing were likely to have better means value of weight-for-height z-score compare to those whose mothers having education less than 6 years of schooling.

Table 34. Relationship between nutritional status and illiteracy program

──────────────────────────────────────────────────────────────────────── Illiteracy Program n WAZ* WHZ_ ═══════════════════════════════════════════════════════════════════════ Participate 55 -1.5 ± 1.2 -0.7 ± 1.1 Not Participate 398 -1.9 ± 1.2 -1.0 ± 1.0 ────────────────────────────────────────────────────────────────────────

Total 469 ────────────────────────────────────────────────────────────────────────

*) p = 0.059 (significant different at p < 0.10, ANOVA, after controlling age and village variables) _) p = 0.061 (significant different at p < 0.10, ANOVA after controlling village variables)

Again children whose mothers participated in illitercy reducing program (Kejar Paket A) were had better nutritional status (WAZ and WHZ). In Mantar, Pulau Bungin, Tropo, and Tolo Kalo none of surveyed mothers participated in this program.

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Table 35. Relationship between nutritional status and father's secondary job ────────────────────────────────────────────────────────────────────────

Father's Secondary Job n HAZ* WAZ_ WHZ� ═══════════════════════════════════════════════════════════════════════ Farmer (owned&laborer) 43 -1.7 ± 1.5 -2.0 ± 1.0 -1.2 ± 0.8 Firewood gatherer 36 -2.5 ± 1.3 -2.2 ± 1.0 -1.0 ± 1.0 Fisherman 30 -2.2 ± 1.5 -2.2 ± 1.1 -1.0 ± 1.1 Honey gatherer 45 -1.8 ± 1.2 -2.2 ± 1.1 -1.4 ± 0.9 Trader/Handcrafting 25 -2.1 ± 1.2 -2.1 ± 0.7 -0.9 ± 1.0 Others 18 -2.2 ± 1.2 -2.2 ± 1.1 -1.2 ± 1.0 No secondary job 267 -1.6 ± 1.5 -1.6 ± 1.3 -0.9 ± 1.0 ────────────────────────────────────────────────────────────────────────

Total 469 ────────────────────────────────────────────────────────────────────────

*) p = 0.074 (significant different at p < 0.10, ANOVA, after controlling age and village variables) _) p = 0.090 (significant different at p < 0.10, ANOVA, after controlling age and village variables) �) p = 0.090 (significant different at p < 0.10, ANOVA, after controlling village variables)

Children whose fathers did not have secondary job had better nutritional status compare to those who had secondary job. The higher percentages of fathers having secondary job was gfound in Mantar (as firewood gatherer) and Tropo village (as honey gatherer). Factors related with food availability

Table 36. Relationship between nutritional status (WAZ) and farming system ──────────────────────────────────────────────────────────────────────── Farming system n WAZ* ═══════════════════════════════════════════════════════════════════════ Dry rice production 164 -2.0 ± 1.0 Other 164 -1.7 ± 1.2 ────────────────────────────────────────────────────────────────────────

Total 328 ──────────────────────────────────────────────────────────────────────── Production of groundnut 15 -2.5 ± 1.1** Not Produced 282 -1.8 ± 1.1 ────────────────────────────────────────────────────────────────────────

Total 297 ────────────────────────────────────────────────────────────────────────

*) p = 0.079 (significant different at p < 0.10, ANOVA, after controlling age and village variables) **) p = 0.079 (significant different at p < 0.10, ANOVA, after controlling age and village variables) Children whose father produced rice ladang had a better nutritional status of weight-for-age. However, this status closely related with seasonal fluctuation. During the survey, it was the starting time of harvesting. Children whose households produced ground nut had lower means value of weight-for-age z score than those who did not produced. Ground nut was not common plant among the surveyed households. The higher frequency of ground nut producers was in Batudulang village which was used for their own consumption.

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Table 37. Relationship between nutritional status (WAZ and MUAC) and fish yield ─────────────────────────────────────────────────────────────────────── Fish Yield n WAZ* WHZ_ n MUAC↑ ═══════════════════════════════════════════════════════════════════════ < 1 kg per day 12 -2.4 ± 1.3 -1.2 ± 1.2 - - >1 - 2 kg per day 38 -1.8 ± 1.4 -1.1 ± 0.9 33 13.9 ± 1.1 >2 - 5 kg per day 70 -1.8 ± 1.2 -1.0 ± 1.0 54 14.3 ± 1.4 >5 - 10 kg per day 21 -2.3 ± 1.1 -1.3 ± 0.8 15 14.0 ± 1.2 >10 kg per day 13 -1.1 ± 1.0 -0.3 ± 0.9 10 15.3 ± 0.9 ────────────────────────────────────────────────────────────────────────

Total 154 112 ──────────────────────────────────────────────────────────────────────── *) p = 0.010 (significant different at p < 0.01 , ANOVA after controlling age and village variables) _) p = 0.069 (significant different at p < 0.10, ANOVA after controlling village variables) ↑ ) P = 0.050 (significant different at p < 0.05 ,ANOVA after controlling village variables)

Children in the fishing families which getting fish catchment more than 10 kg per day were higher in nutritional status compare with those getting smaller amount of catchment.

Table 38. Relationship between nutritional status (MUAC) of children** and food shortage

─────────────────────────────────────────────────────────────────── Food Shortage n MUAC* ═══════════════════════════════════════════════════════════════════

No 49 14.8 ± 0.9 Yes 300 14.3 ± 1.3

─────────────────────────────────────────────────────────────────── Total 349

─────────────────────────────────────────────────────────────────── *) p = 0.088 (significant different at p=0.10, T-test after controlling age and village variables) **)children more than 12 months

Children in the households which were suffering from food shortage had lower means value of MUAC than those who did not experience food shortage. Factors related to health

Table 39. Relationship between nutritional status and diarrhea previous week of survey

─────────────────────────────────────────────────────────────────── Diarrhea n WAZ* ═══════════════════════════════════════════════════════════════════

No 376 -1.81 ± 1.19 Yes 92 -1.93 ± 1.28

─────────────────────────────────────────────────────────────────── Total 468

─────────────────────────────────────────────────────────────────── *) p = 0.06 (significant different at p=0.10, T-test after controlling age and village variables)

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Table 40. Relationship between nutritional status and ARI at the time of survey ─────────────────────────────────────────────────────────────────── ARI n WAZ* HAZ** ═══════════════════════════════════════════════════════════════════

No 223 -1.68 ± 1.19 -1.63 ± 1.46 Yes 246 -1.98 ± 1.21 -1.98 ± 1.43

─────────────────────────────────────────────────────────────────── Total 469

─────────────────────────────────────────────────────────────────── *) p = 0.005 (significant different at p=0.05), T-test after controlling age and village variables) **)p = 0.011 (significant different at p=0.05) T-test after controlling age and village variables)

Table 41. Relationship between nutritional status and ARI previous week of survey ─────────────────────────────────────────────────────────────────── ARI n WAZ* HAZ** ═══════════════════════════════════════════════════════════════════

No 224 -1.67 ± 1.23 -1.65 ± 1.48 Yes 241 -2.00 ± 1.17 -1.98 ± 1.41

─────────────────────────────────────────────────────────────────── Total 465

─────────────────────────────────────────────────────────────────── *) p = 0.03 (significant different at p=0.05), T-test after controlling age and village variables) **)p = 0.06 (significant different at p=0.1) T-test after controlling age and village variables)

Children who were suffering from ARI and diarrhea were having lower nutritional status (WAZ and HAZ) compare to healthy children. Annex 2 showed p value of the statistical analysis between nutritional status and disease prevalence. Factors related to food intake of children Table 42. Relationship between intake of fruits and nutritional status ________________________________________________________ Frequency n WHZ* ________________________________________________________ Never eat 24 -1.17+ 1.09 Once/several times per day 18 -1.11+ 0.83 Once/several times per month 104 -1.06+ 0.82 Sometimes 56 -0.86+ 0.88 ___________________________________________________________ * p= 0.02 (significant different at p<0.05, anova, after controlling village variable)

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Table 43. Relationship between intake of snacks and nutritional status ________________________________________________________ Frequency n WAZ* ________________________________________________________ Never eat 23 -2.26+ 0.96 Once/several times per day 76 -2.07+ 0.87 Once/several times per month 87 -2.10+ 1.13 Sometimes 16 -1.44+ 1.21 ___________________________________________________________ * p= 0.08 (significant different at p<0.1, anova, after controlling age, village variables) Chidren more than 12 months who sometimes eating fruits and snack were likely to have better nutritional status than those who never eat. Factors related to sanitation and environment condition

Table 44. Relationship between nutritional status and source of drinking water ─────────────────────────────────────────────────────────────────── Source of Drinking Water n WAZ* ════════════════════════════════════════════════════════════════════ Water tank 83 -1.9 ± 1.3 Cemented Well 197 -1.8 ± 1.2 Uncemented Well 49 -2.3 ± 0.9 Water Vendor 15 0.9 ± 1.1 Spring Water 65 -1.7 ± 1.1 Hand Pump 57 -1.6 ± 1.1 ────────────────────────────────────────────────────────────────────

Total 466 -1.8 ± 1.2 ─────────────────────────────────────────────────────────────────── *) p = 0.009 (significant different at p=0.01, ANOVA after controlling age and village variables)

Table 45. Relationship between nutritional status (z-score and MUAC) and source of bathing water

─────────────────────────────────────────────────────────────────── Source of Bathing n HAZ* WAZ _ WHZ_ n MUAC♦ Water ════════════════════════════════════════════════════════════════════ Water tank 75 -1.8±1.4 -1.9±1.3 -1.1±0.9 52 14.2±1.2 Cemented Well1 45 -1.9±1.6 -1.9±1.2 -1.1±0.9 116 14.2±1.2 Uncemented Well39 -2.5±1.2 -2.3±1.1 -1.1±1.1 31 13.9±1.1 Surface Water 86 -1.5±1.5 -1.8±1.3 -1.1±0.9 64 14.4±1.3 Water Vendor 12 -1.2±1.2 -0.8±1.1 0.0±1.2 - - Spring Water 55 -2.0±1.3 -1.8±1.1 -0.7±0.8 38 15.0±1.1 Hand Pump 54 -1.5±1.2 -1.5±1.1 -0.6±1.1 45 14.9±1.2 ────────────────────────────────────────────────────────────────────── Total 466 -1.8±1.4 -1.8±1.2 -1.0±1.0 346 14.4±1.3 ────────────────────────────────────────────────────────────────── *) p = 0.016 (significant different at p=0.05, ANOVA after controlling age and village variables) _) p = 0.009 (significant different at p=0.01, ANOVA after controlling age and village variables) _) p = 0.004 (significant different at p=0.01, ANOVA after controlling village variables)

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♦ ) p = 0.021 (significant different at p =0.05, ANOVA after controlling vilalge variables)

Table 46. Relationship between nutritional status (Z-score and MUAC) and source of washing water

───────────────────────────────────────────────────────────────────── Source of Washing n HAZ* WAZ _ WHZ_ n MUAC♦ Water ══════════════════════════════════════════════════════════════════════ Water tank 77 -1.8±1.4 -1.9±1.3 -1.1±0.9 54 14.1±1.2 Cemented Well 143 -1.9±1.6 -1.9±1.2 -1.1±0.9 114 14.1±1.2 Uncemented Well 38 -2.4±1.2 -2.3±1.1 -1.2±1.0 30 13.8±1.0 Surface Water 93 -1.6±1.5 -1.8±1.2 -1.0±0.9 70 14.5±1.3 Water Vendor 12 -1.2±1.2 -0.7±1.1 0.0±1.2 - - Spring Water 51 -2.0±1.3 -1.8±1.1 -0.6±0.8 35 15.0±1.1 Hand Pump 54 -1.5±1.2 -1.5±1.1 -0.6±1.1 45 14.9±1.2 ──────────────────────────────────────────────────────────────────── Total 468 -1.8 ± 1.5 -1.8 ± 1.2 -1.0±1.0 348 14.4±1.3 ────────────────────────────────────────────────────────────────────── *) p = 0.055 (significant different at p=0.10, ANOVA after controlling age and village variables) _) p = 0.012 (significant different at p=0.05, ANOVA after controlling age and village variables) _) p = 0.002 (significant different at p=0.01, ANOVA after controlling village variables) ♦ ) p = 0.007 (significant different at p=0.01, ANOVA after controlling village variables)

Children who get water for bathing and washing from hand pump had better nutritional status than those who get water from uncemented well.

Table 47. Relationship between nutritional status (Z-score) and place of garbage disposal ───────────────────────────────────────────────────────────────────── Place of Garbage Disposal n WHZ* ═════════════════════════════════════════════════════════════════════ River 41 -0.5 ± 0.9 Forest 36 -0.9 ± 0.8 Sea 131 -1.0 ± 1.0 Burried/Burned 42 -1.1 ± 1.0 Street/Backyard 219 -1.0 ± 1.0 ──────────────────────────────────────────────────────────────────────

Total 469 -1.0 ± 1.0 ────────────────────────────────────────────────────────────────────── *) p = 0.052 (significant different at p=0.10, ANOVA after controlling age and village variables)

Mostly mothers threw away the garbage in the backyard which caused unhygienic condition which also closely related with the disease prevalence, hence nutritional status. Factors related to food intake of households.

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Table 48. Relationship between Nutritional Status and Root/Tubers Intake

──────────────────────────────────────────────────────────────────────── Frequency of Root/ n HAZ * Tuber Intake ════════════════════════════════════════════════════════════════════════ Never 132 -2.0 ± 1.4 Daily/Weekly 35 -1.3 ± 1.3 Seasonal 211 -1.9 ± 1.4 Yearly 89 -1.6 ± 1.5 ──────────────────────────────────────────────────────────────────────── Total 467 -1.8 ± 1.4 ──────────────────────────────────────────────────────────────────────── *) p=0.008 (significant different at p<0.01, ANOVA after controlling age and village variables)

Table 49. Relationship between nutritional status (Z-score) and ground nut intake

──────────────────────────────────────────────────────────────────────── Frequency of Ground n WHZ * Nut Intake ════════════════════════════════════════════════════════════════════════ Never 85 -0.7 ± 1.0 Daily 45 -1.1 ± 1.0 Weekly 124 -1.1 ± 1.0 Seasonal 160 -1.0 ± 0.9 Yearly 54 -0.9 ± 1.0 ──────────────────────────────────────────────────────────────────────── Total 468 -1.0 ± 1.0 ──────────────────────────────────────────────────────────────────────── *) p=0.036 (significant different at p<0.05, ANOVA after controlling age and village variables)

Table 50. Relationship between nutrition status (MUAC) and tofu intake

──────────────────────────────────────────────────────────────────────── Frequency of Tofu n MUAC * ════════════════════════════════════════════════════════════════════════ Never 223 14.3 ± 1.2 Daily/Weekly 73 14.3 ± 1.3 Seasonal/Yearly 53 14.7 ± 1.4 ──────────────────────────────────────────────────────────────────────── Total 349 14.4 ± 1.3 ──────────────────────────────────────────────────────────────────────── *) p=0.043 (significant different at p<0.05, ANOVA after controlling age and village variables)

Table 51. Relationship between nutritional status (MUAC) and tempe intake ──────────────────────────────────────────────────────────────────────── Frequency of Tempe n MUAC * ════════════════════════════════════════════════════════════════════════ Never 226 14.3 ± 1.2 Daily/Weekly 69 14.3 ± 1.3 Seasonal/Yearly 54 14.7 ± 1.4 ──────────────────────────────────────────────────────────────────────── Total 349 14.4 ± 1.3 ────────────────────────────────────────────────────────────────────────

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*) p=0.041 (significant different at p<0.05, ANOVA after controlling age and village variables)

Table 52. Relationship between Nutritional Status (Z-score) and beef intake ──────────────────────────────────────────────────────────────────────── Frequency of Beef n HAZ * ════════════════════════════════════════════════════════════════════════ Never 208 -1.8 ± 1.5 Daily/Weekly 54 -1.2 ± 1.4 Yearly 207 -2.0 ± 1.4 ──────────────────────────────────────────────────────────────────────── Total 469 -1.8 ± 1.5 ──────────────────────────────────────────────────────────────────────── *) p=0.030 (significant different at p<0.05, ANOVA after controlling age and village variables)

Table 53. Relationship between nutritional status (Z-score) and horse intake ──────────────────────────────────────────────────────────────────────── Frequency of Horse n HAZ * ════════════════════════════════════════════════════════════════════════ Never 381 -1.7 ± 1.5 Ever 85 -2.3 ± 1.2 ──────────────────────────────────────────────────────────────────────── Total 466 -1.8 ± 1.4 ──────────────────────────────────────────────────────────────────────── *) p=0.019 (significant different at p<0.05, ANOVA after controlling age and village variables)

Determinant factors of mothers nutritional status

Table 54. Relationship between ethnicity group and nutritional status of non pregnant mother

─────────────────────────────────────────────────────────────────────── Ethnicity n BMI* ═══════════════════════════════════════════════════════════════════════ Bima 119 19.5 ± 2.2 Sumbawa 104 19.7 ± 2.2 Others 85 20.6 ± 3.1 ──────────────────────────────────────────────────────────────────────── Total 308 ──────────────────────────────────────────────────────────────────────── *) p=0.01 (significant different at p<0.05, ANOVA )

BMI of mothers who belong to Sumbawa or Bima ethnic were worse compare to other ethnic such as Sasak, Bajo or Bali.

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Table 55. Relationship between mother's job and nutritional status of non pregnant mother

─────────────────────────────────────────────────────────────────────── Job n BMI* ═══════════════════════════════════════════════════════════════════════ Housewife 160 20.2 ± 2.7 Farmer 105 19.5 ± 2.2 Others 43 20.5 ± 3.1 ──────────────────────────────────────────────────────────────────────── Total 308 ──────────────────────────────────────────────────────────────────────── *) p=0.02 (significant different at p<0.05, ANOVA)

Table 56. Relationship between main job of father and nutritional status of non pregnant mother

─────────────────────────────────────────────────────────────────────── Job n BMI* ═══════════════════════════════════════════════════════════════════════ Farmer 188 19.6 ± 2.0 Fishermen 77 20.4 ± 3.3 Others 43 20.3 ± 2.6 ──────────────────────────────────────────────────────────────────────── Total 308 ──────────────────────────────────────────────────────────────────────── *) p=0.02 (significant different at p<0.05, ANOVA)

BMI of mothers belong to farmers' households was smaller compare to fishermen's households. While activities of mothers also effect the nutritional status of mothers. Mothers who helped the husband (having job as farmer) had smaller BMI value compare to pure housewife.

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Table 57. Association between housing condition and nutritional status of mothers ═════════════════════════════════════════════════════════════════ Wall made of n MUAC of Mothers*

Mean±sd _________________________________________________________________ Wood or Bamboo 336 23.84±2.59 Stone or Cement 24 25.04±1.73 p = 0.026 ═════════════════════════════════════════════════════════════════ *)significant different at p<0.05, T-test

Table 57 suggested that mothers who lived in the house with wall made of wood or bamboo had lower MUAC than those who lived in house with wall made of stone or cement. Table 58. Association between property ownership and nutritional status of mothers ═════════════════════════════════════════════════════════════════ Property MUAC BMI Ownership n Mean±sd n Mean±sd ________________________________________________________________ TELEVISION No 336 23.86±2.55* 288 19.79±2.43** Yes 24 24.79±2.75 20 20.96±3.53 _________________________________________________________________ Total 360 308 *) significant different at p<0.1, T-test **)significant different at p<0.05, T-test ═════════════════════════════════════════════════════════════════ ELECTRICITY No 301 23.77±2.56* 263 19.73±2.47** Yes 59 24.72±2.47 45 20.74±2.64 __________________________________________________________________ Total 360 308 *)significant different at p<0.05, T-test **)significant differrent at p<0.05, T-test ═════════════════════════════════════════════════════════════════ The mothers in households with possesion of television or electricity had better nutritional status than those pertaining to households without those commodity possessions. There was positive correlation between MUAC and BMI(r=0.83, p=0.000). The higher MUAC the higher BMI.

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Table 59. Association between food shortage and nutritional status of mothers ════════════════════════════════════════════════════════════════ Food Shortage MUAC BMI Experience n Mean±sd n Mean±sd ________________________________________________________________ No 48 24.54±2.38* 37 20.49±2.66** Yes 312 23.83±2.58 271 19.79±2.49 _________________________________________________________________ Total 360 308 *)significant different at p<0.1, T-test **)significant different at p<0.1, T-test ═════════════════════════════════════════════════════════════════ Table 59 showed that the mothers who experienced food shortage (staple food) tended to have lower nutritional status (MUAC and BMI) than those without experience of food shortage. Table 60. Association between fish shortage and nutritional status of mothers among

households of fishermen ════════════════════════════════════════════════════ Duration of MUAC BMI Fish Shortage n Mean±sd n Mean±sd ______________________________________________________________ ≤ 3 months 44 24.54±3.49* 37 20.84±3.50** > 3 months 35 23.13±2.25 28 19.53±2.70 Total 79 65 ____________________________________________________________________________________________________________________________ *) significant different at p<0.05, T-test

**)significant different at p<0.1, T-test Among fisherman households, mothers with fish shortage experience over 3 months were of worse nutritional status than those having fish shortage duration of 3 months or less.

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Table 61. Association between household frequency of food consumption and nutritional status of mothers

═════════════════════════════════════════════════════════════════ Food Frequency MUAC of Mothers BMI of Mothers

n mean±sd n mean±sd __________________________________________________________________ TOFU Nevera 233 23.47±2.28* 205 19.57±2.26** Frequentlyb 34 24.62±3.03 28 20.93±3.20 Occasionallyc 93 25.09±2.79 75 20.43±2.70 *) significant different at p<0.001, anova, LSD test a differs from b, a differs from c **)significant different at p<0.05, anova. LSD test a differs from b, a differs from c

═════════════════════════════════════════════════════════════════ TEMPE Nevera 235 23.53±2.35* 207 19.64±2.41** Frequentlyb 26 24.62±3.04 20 20.08±3.50 Occasionallyc 99 24.65±2.75 81 20.35±2.46 *) significant different at p<0.001, anova, LSD test a differs from b, a differs from c **)significant different at p<0.05, anova. LSD test a differs from b, a differs from c ═══════════════════════════════════════════════════════════════ OIL Nevera 34 23.58±1.80* Frequentlyb 225 24.30±2.74 Occasionallyc 101 23.17±2.20 Total 360 _____________________________________________________________________________ *) significant different at p<0.001, anova, LSD test b differs from c Frequently : more than once per week

Occasionally : once per week or less BMI: only pregnant mothers were analyzed Table 61 showed that mothers who never ate tofu and tempe had lower MUAC and BMI than those who ate those food frequently or occasionally.

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DISCUSSION

The nutritional status of the surveyed children was found higher than reported data of SUSENAS 1992; it was indicated by 44.8 % of the children were too short (stunting as a sign of chronic malnutrition) for their age, while 10.7 % were too thin for their height (wasting or sign of acute malnutrition), and 50.3 % underweight. The figure is seemed in line with the stunting prevalence of the underfive children which was done in 1992 in PPSTN project area and it was similar with the stunting prevalence in Pasaman District of West Sumatra in 1991 (Table 62). PPSTN project in Lombok was started in September 1991, while the health program just started in beginning of 1993. This data showed the nutritional situation of the underfive children in Sumbawa island was in the same condition with the nutritional status of children in PPSTN area at the starting of the project. Table 62. Prevalence of malnutrition indicated by a low height-for-age (z-score <-2) as

determined in several surveys. ______________________________________________________________________ Study area Province Year Sample Prevalence

size (n) (%) ____________________________________________________________________________________ 5 villages West Kalimantan 1993 202 68.8 PPSTN project area West Nusa Tenggara (Flores) 1989 667 52.0 5 villages West Kalimantan 1992 91 47.3 PPSTN project area West Nusa Tenggara (Lombok) 1992 480 46.6 12 villages West Nusa Tenggara (Sumbawa)1995 469 44.8 Rural Pasaman West Sumatra 1991 911 44.2 Jeneponto South Sulawesi 1992 833 40.8 2 villages East java 1992 182 34.5 Credit groups East Java 1993 191 33.0 Malang East Java 1994 434 32.5 2 villages, Ophir West Sumatra 1994 80 30.0 East Jakarta Jakarta 1993 279 22.6 ____________________________________________________________________________________

Body Mass Index (BMI) was calculated as an indicator nutritional status of the adults. BMI represents the relation between weight and height. A low BMI (<17) is associated with a decreased working capacity and it may constitute a risk to health. About 10 % of the non-pregnant women in the survey area have BMI with a value below 17. Furthermore in three mountaneous villages several women had clinical signs of iodine deficiency. The most severe is in Tepal village where the prevalence of VGR was 23 % among women in the survey sample which was higher than prevalence VGR determined by SUSENAS 1992.

There were several factors associated with deficient nutritional situation in the surveyed villages. The nutritional status of children below 6 months old was still satisfactory. Children who were breastfed tend to have a better nutritional status than children who were not breastfed anymore. This might be indicated that breastmilk was not replaced by adequate diet either in terms of quality or quantity. In this survey data was collected in terms of quantity, however in terms of quality it can be observed that the main daily diet of the household was rice, fish and green leavy vegetable. Households of fishermen had a

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better food consumption pattern than households of farmers. Foods like egg, fish, sugar, chicken, oil, tofu, and tempe were consumed more frequently in fishermen (in fishing village) households than farmers' households. The nutritional status of mothers of fishermen households was better that of farmers' wives. Ethnicity and activity of mothers also influenced the nutritional status of mothers. In the fishermen households, only father who went for fishing and mothers were the one who sole the catchment.

Households experienced food shortage during dry season in Dompu District was higher than in Sumbawa District (Figure 3 ). Many complains of food shortage were mentioned by households in Sepayung and Tropo village. While during rainy season, mostly households in fishing villages; in Pulau Bungin, Pulau Bajo and Teluk Santong villages experienced fish shortage.

In this survey the prevalence of acute respiratory infections (ARI) was determined. Children who suffering from ARI and diarrhea had lower means value of height-for-age and weight-for-age than healthy children. Diarrhea was influenced by the hygienic situation in the village. Source of drinking water associated with the means value of weight-for-age z score. Also source of bathing and washing water (uncemented well) was associated with lower nutritional status of children.

There were some significant associations between socio-economic factors and nutritional status, such as education of mothers, number of earner money in the households, ethnicity and secondary job of fathers. All of these factors were closely related with earning income of the households. Some sub-groups in the surveyed population were worse than other groups. These sub-groups should get more priority in the poverty alleviation program. As mentioned before, the farmers' households were less favourable than fishermen' households. However this might be solely because of the difference among villages. The worst condition in farming village was Tolokalo village, while among the fising villages, Pulau Bajo was the worst. The results of the survey can be summarized as follows: * The nutritional status of the children was relatively unfavourable with high prevalence of

reduced growth rate and in some villages many of acutely malnourished children. Childhood mortality was high (30 %), specifically in Dompu district.

* Household food intake was insufficient in terms of quality and probably also in quantity. An

improvement of diversifying food pattern could be reached through improvement of awareness and related socio economic factors.

* Habits of child feeding was unfavorable. Many newborns were given additional food at early

age, while prolonged breastfeeding with insufficient additional food was still applied in children older than one year. Knowledge of mother on additional child feeding when exclusive breastfeeding is not sufficient anymore should be increased.

* Trend food shortage in Dompu district was higher in Sumbawa District. However further

information related with seasonality should be collected, whether food insecurity existed in those

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areas. Paticularly in Tolokalo village in Dompu district and Sepayung village in Sumbawa district where the means duration of food shorted durring the year was relatively high.

* The hygienic and sanitation should be improved, especially in villages where people get drinking

water from uncemented well. Other important factors in relation with favourable enviroment was encouraging awareness of keeping the livestock at cage.

* Among the farming villages in Sumbawa district, Mantar village and among those in Dompu

district; Tropo village needs most urgent attention. While of fishing villages; Pulau Bajo in Dompu district also needs attention.

Following is some suggestions possible for intervention in the survey area:

No

Main problem

Intervention

Target group

1

Sanitation and hygienic environment: (related with infectious disease prevalence) drinking water source, clean environment

extension the importance of getting drinking water from safe and clean water source, cage the livestock, encourage the usage of latrine particularly in the villages where latrines had been built.

father, mother, village staffs

2

Health status of children: (related with nutritional status) immunization coverage and regular weighing

increase POSYANDU activities

kader, puskesmas staffs and mother

3

Health care of mothers: (related with the nutritional status of the child) family planning, prenatal care

extension on the importance of family planning and prenatal care

traditional birth attendance(TBAs), puskesmas staffs and mother

4

Health care of children: (related with nutritional status) weaning and feeding practises

education program on the importance of giving proper weaning and child feeding

mothers through TBAs and health staffs

5

Socio-economic factors: IDT activities

organize and manage IDT group and give extension related with their main activities, encourage usage of their home garden

IDT group through IDT motivator and agricultural extension service staffs