Poor dietary diversity, wealth status and use of un-iodized salt are associated with goiter among school children: a cross-sectional study in Ethiopia

All children aged 6–12 years who lived in HDSS site and attended primary school during the study period were eligible for the study. The sample size was calculated using Epi-info version 2.3 by using the following assumptions; the prevalence of goiter among school-aged children was 37.6% [28], 95% level of confidence and 5% margin of error. Finally, the sample size of 757 was obtained by considering 5% non-response rate and a design effect of 2. A multistage stratified sampling followed by systematic random sampling technique was employed to reach the study participants. Initially, schools were stratified into urban and rural. Of the total twenty-four primary schools in the HDSS site, five (one urban and four rural) schools with a total of 3429 students were selected using the lottery method. Number of students included in each school were proportionate-to-population size. Finally, a systematic sampling technique was employed to select the study subjects.

Physical examination was done for the selected child, after that using the child’s name, parent’s name and address, household visit was made by data collectors to gather the socio-demographic, the household utilization of iodized salt and dietary habit related characteristics of the child and the parents. Women who were majorly involved in food preparation of the household were selected as a respondent.

A structured interviewer-administered questionnaire was used to collect data. The questionnaire was first prepared in English and was translated into the local language (Amharic) and back translated to English to maintain consistency by two BSc holder English teachers who are also native speakers of Amharic language. Pretest was done on five percent of the sample out of the study area. Two days training on techniques of interview, salt iodine content determination and thyroid physical examinationwas given for data collectors and supervisors. A total of nine data collectors (two health officers, an environmental health professional, and six permanent data collectors of the HDSS site) and three supervisors (two public health experts and a medical doctor) were involved in the study. Accordingly, the thyroid physical examination was undertaken by two Health Officers under the supervision of a medical doctor. Determination of salt iodine content was done by the trained environmental health professional. Daily supervision and feedback were carried out by the investigators and supervisors during the entire data collection period.

The presence of goiter was assessed by the trained Health Officers with strict adherence to the standard procedures stipulated by the World Health Organization. Accordingly, goiter was defined as grade 0 if no palpable mass in the neck was detected, grade 1 if there was a mass in the neck consistent with palpable enlarged thyroid, but not visible when the neck was in the normal position, whereas grade 2 was a swelling in the neck that was visible when the neck is in a normal position and is consistent with an enlarged thyroid when the neck is palpated (palpable and visible). Lastly, the child was deemed as having goiter when he/she had goiter of grade 1 or 2 [29].

A tablespoon of salt was collected from each household and the MBI international Rapid Test Kit (RTK) was used to determine the level of salt iodine content [16, 27, 29]. The small cup in the kit was filled with salt and made the cup surface flat. Two drops of test solution from white ampule were added to the surface of the salt by piercing the white ampoule with a pin and gently squeezing the ampule. The salt iodine content was determined within one minute by comparing the color developed on the salt with the color chart. The value 0 Parts per Million (PPM), <15 PPM and ≥15 PPM with the corresponding color chart on the rapid test kit were used to classify the level of iodine in the sampled salt. If no color appears, after 1 min, five drops of the recheck solution from red ampule was added to a fresh salt sample and followed by two drops of test solution on the same salt sample. Then, a comparison was done with the color chart indicators for salt iodine content [29].

Determination of dietary diversity score (DDS) of the child was started by asking the mother to list all food consumed by the child in the previous 24 h preceding the survey. Then reported food items were classified into nine food groups, as starchy staples; dark green leafy vegetables; vitamin A rich fruits and vegetables; other fruits and vegetables; organ meat; flesh meat and fish; and egg [30]. Considering four food groups as the minimum acceptable dietary diversity, a child with a DDS of less than four was classified as having poor dietary diversity; otherwise, it was deemed to have good dietary diversity [30].

Household’s wealth index, adopted from EDHS 2011 [31], was determined using Principal Component Analysis (PCA) by considering the household assets, such as quantity of cereal products, type of house, livestock and agricultural land ownership. First, variables were coded between 0 and 1. Then variables entered and analyzed using PCA, and those variables having a communality value of greater than 0.5 were used to produce factor scores. Finally, the factor scores were summed and ranked into tertiles as poor, medium and rich.

Similarly, the knowledge of mothers towards iodized salt use was computed by using nine knowledge item questions, adopted by reviewing different literatures [7, 16, 28], including the health benefit of iodized salt, disorders resulted from ID, food sources of iodine, appropriate place for salt storage, time to add salt during food preparation, salt storage material and existence of law prohibiting selling of non-iodized salt in Ethiopia. Accordingly, the factor scores were summed and ranked into poor, medium and high.

The collected data were checked and entered into Epi-info version 7 and exported to SPSS version 20 statistical software for analysis. Descriptive statics were carried out and the result was presented using text, tables and graph. A binary logistic regression model was fitted to identify factors associated with goiter. Variables with a p-value less than <0.2 in the bivariable analysis and those which frequently showed significant association with goiter in the previous studies were fitted into the multivariable logistic regression analysis and backward LR method was employed. Both Crude Odds Ratio (COR) and Adjusted Odds Ratio (AOR) with the corresponding 95% Confidence Interval (CI) were calculated to show the strength of association. In multivariable analysis, variables with a p-value of <0.05 were considered as statistically significant.

A total of 735 school children were included in the study, which makes a response rate of 97.1%. The median age of children was 10 years with Inter-quartile Range (IQR) of 3 years. About 54.1 and 61.6% children were females and lived in a family size of greater than five, respectively. Three-quarters of mothers were illiterate and 56.5% were outdoor workers. Most (80.7%) of the fathers were farmers (Table 1).

A substantial proportion, (96.2%), of households used unpacked salt for food preparation, and about 49.8% households’ added salt at the beginning and middle of food preparation. Only one-third, (32.5%), of the households used adequately iodized salt (Table 2). Furthermore, about 85.2% of children had DDS of below four (mean ± SD of DDS of the children was 2.8 ± 0.67); while none of them were included fish in their diet within 7 days prior to the date of survey (Table 3).

One-third (33.2 and 29.1%, respectively) of the mothers had higher knowledge and favorable attitude towards iodized salt use. Regarding the cause of goiter, some of the mothers believed that it is due to contaminated water (34.5%), while 13.8 and 23.4% of them thought that it was because of genetic predisposition and drinking leftover water from a person who had a goiter, respectively. Only a quarter, (23.4%), of mothers considered that regular consumption of iodized salt can prevent goiter (Table 4).

The overall prevalence of goiter was found to be 29.1% [95% CI: 25.9, 32.6]; one-fifth had grade-one goiter, while 6.7% had a grade two goiter. Moreover, goiter was more common among females (31.4%) than males (26.4%) (Fig. 1).

Both bivariable and multivariable logistic regression analyses were done to see the effect of the selected characteristics on goiter. As it is presented in Table 5, child age, dietary diversity, residence, source of drinking water, mother’s and father’s education, father’s occupation, wealth status, the level of salt iodine content, and consumption of cabbage were the factors showed significant association with goiter in the bivariable analysis.

Nevertheless, the result of multivariable logistic analysis revealed that child age, dietary diversity, maternal occupation, knowledge on the use of iodized salt, household wealth status, the level of salt iodine content, and source of drinking water were significantly and independently associated with goiter. Consequently, with a year increase in age, the odds of having goiter were increased by 12% (AOR = 1.12; 95% CI: 1.01, 1.26). The likelihood of developing a goiter was 1.48 times (AOR = 1.48; 95% CI: 1.02, 2.14) higher among children whose mothers were housewives compared to children of mothers working outside the home.

In this study, the higher odds of developing a goiter were also observed among children living in the household using unprotected well water (AOR = 6.38; 95% CI: 2.55, 16.01) and with inadequately iodized salt (AOR = 2.77; 95% CI: 1.84, 4.15). As compared to the richer households, children from a household with medium wealth status were found at increased odds of having a goiter (AOR = 1.75; 95% CI: 1.07, 2.87). Likewise, the odds of developing a goiter among children with poor DDS were 1.92 times (AOR = 1.92; 95% CI: 1.06, 3.48) higher compared to their counterparts. However, the odds of having goiter were decreased by 35% (AOR = 0.65; 95% CI: 0.42, 0.94) among children whose mothers had medium knowledge towards iodized salt use as compared to children of mothers with poor knowledge (Table 5).