Outpatient Nutritional Screening and Rehabilitation of Malnourished Egyptian Children: Are Rural Areas at More Risk?

doi:10.21203/rs.3.rs-1976332/v2

Background

Malnutrition presents a major global health burden. In Egypt, it remains an important issue in children under 5 years especially in urban communities. This increased the interest in screening the pediatrics outpatient clinics for early detection and proper management of malnutrition.

Aim of the study:

The aim of the study was to screen 2–5 years old children enrolled from Egyptian hospitals in rural and urban areas for the risk of malnutrition using Screening Tool for Assessment of Malnutrition in Pediatric (STAMP) and to evaluate the effectiveness of nutritional intervention program.

Subjects and Methods:

This cross-sectional study was conducted on 90 patients recruited from Bolaque El-Dakror hospital in urban Cairo, and El-Badrashine hospital representing rural areas. Dietary history and anthropometric measurements were assessed. Patients at intermediate and severe risk of malnutrition according to STAMP were given tailored nutritional programs and were followed up.

Results

In the rural hospital, 4.4% of the screened children were underweight, 22.2% were marginally underweight, and 73.3% had normal weight. Regarding the urban hospital, 15.6% were marginally underweight, 84.4% had normal weight and no patients were underweight. Among the rural group 46.7% were at low risk of malnutrition, 17.8% were at intermediate risk and 35.6% were at high risk according to STAMP score results. In the urban group 71.1% were at low risk, 8.9% were at intermediate risk and 20% were at high risk. Nevertheless, the only significant differences were the more stunting and higher BMI in rural hospital patients. After nutritional intervention, high-risk category patients decreased in both groups coupled by significant improvement in the anthropometric parameters and nutrition data with no significant differences between them.

Conclusion

Nutritional education and prompt implementation of nutritional rehabilitation program for malnourished children detected by screening tools result in improvement in their nutritional status disregards their location whether urban or rural.

Malnutrition

nutritional intervention

nutritional screening

rural

STAMP

urban

Malnutrition is one of the major global health burdens. Malnutrition is a deficiency or improper intake of energy and nutrients. Malnutrition leads to economic, social, and health issues for families, at the community and national level [1].

Malnutrition can be defined as a state resulting from lack of intake or uptake of nutrients that leads to altered body composition and body cell mass causing diminished physical and mental function and impaired clinical outcome from disease [2].

Globally in 2019, 149 million children under the age of 5 years were stunted, almost 50 million wasted, 340 million suffered from micronutrient deficiencies and 38.2 million were overweight and obese [3]. In Egypt Elsary and collaborators reported that malnutrition remains an important issue especially among under-five sick children in rural areas [4]. The latter authors emphasized the need for implementing hospital and community-based intervention nutritional program.

There is an ongoing interest in nutritional screening tools (NSTs) in pediatrics to facilitate the identification of children at risk for malnutrition who need further assessment and possible nutritional intervention. Nutritional screening is considered a key part of the nutrition care process and pediatric nutritional care algorithm [5].

Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP) offers a validated screening tool for the detection of malnutrition and malnutrition risk in pediatric primary health care settings. Furthermore, the use of STAMP in a primary health care clinic raised clinician's awareness of nutritional status. This was reflected as an increase in anthropometric measurements and the documentation of nutritional status following study implementation [6].

The aim of the study was to use STAMP in screening 2–5 years old children at outpatient clinics in Egyptian hospitals from urban and rural locations and to evaluate the effectiveness of nutritional intervention program for children at risk.

Patients and study design:

This cross-sectional, observational, prospective study was conducted in two different hospitals: Bolaque El-dakror hospital which represents an urban area, and El-Badrashine hospital as a representative of rural areas during the period from August 2018 to September 2019.

The study included 90 patients whose ages ranged between 2 and 5 years and were visiting the outpatient clinics in the assigned hospitals. Patients with chronic or congenital diseases which can affect the nutritional status and those who needed hospitalization were excluded.

Methods: The sample size was calculated according to the results of a nutritional survey carried out in Fayoum, Egypt [4]. The sample size was calculated using EPIDAT software version 3.1 (Level of confidence 95%, precision 5%). The final sample size in each of the two groups was estimated to be 45.

Ethical approval

An informed consent was obtained from the parents before enrollment in the study according to the Faculty of Medicine, Ain Shams University Research Ethical Committee.

Upon enrollment all patients were subjected to the following:

1. Full medical history including current complaint and presence of any chronic disease, allergy and/or genetic disorder.

2. Thorough clinical examination to ensure the clinical stability of the patient.

3. Full anthropometric measures including weight and height. Body mass index (BMI) and z-scores were calculated as well (Weight for age z-score, Height for age z-score, and BMI z-score).

Weight (Wt) in Kg: It was measured by a weight scale. The subject stood bare footed on the center of the platform without touching or leaning on anything, wearing the least possible clothes, reading was taken to the nearest 0.1 kg. Values were put on the CDC growth charts [7].
Height (Ht) in cm: Height was measured by stadiometer. The patient stood in an upright position barefoot on the base plate, with his feet parallel, and his heels, buttocks, shoulders and back of the head touching the stadiometer and the arms were hanging extended on side. The measuring arm was taken down to the subject`s head which is held comfortably erect. The cursor gives the accurate measurement of the height, and the reading was taken to the nearest millimeter. Values were put on the CDC growth charts [7].
Body mass index (BMI): BMI values were calculated using measured height and weight values as follows:

BMI (Kg/m²) = weight ÷(height) ²

Undernutrition was defined as stunting (height for age z-score (HAZ) < -2 SD) and underweight (weight for age z-score (WAZ) < -2 SD) and these are the moderate cases. The mild cases were < -1 SD whereas severe undernutrition was defined as severe stunting HAZ < -3 SD and severe underweight WAZ < -3 SD [8].

4. 24-hours diet recall was taken for three days and analyzed through software program based on food composition table of National Nutrition Institute (NNI), Egypt. Dietary recall included breakfast, lunch, dinner, and snacks of the previous 24 hours. The average of the three sheets was taken and energy gap was calculated.

5. All patients were screened with STAMP which is a 5-step tool. It consists of three elements: clinical diagnosis (classified by the possible nutritional implications), nutritional intake and anthropometric measurements (weight). Each component carries a score of 1-3 and the total score reflects the risk of undernutrition. It was established in 2004 and evaluated in 2007. To evaluate the quick and easy-to-use NSTs for hospitalized children, three factors were considered: diagnosis, nutritional intake, as well as weight and height. After evaluating these factors, the sum was classified into low, medium, and high risk, and the STAMP also suggested that a care plan in the last step. A score of 2 or 3 indicates medium risk and a score ≥ 4 indicates high risk [9].

According to the results of STAMP score patients at low risk were given routine clinical care at the outpatient clinic.

Patients at intermediate risk were given a nutritional intervention program, which included:

Educational program
The nutritional rehabilitation program was individually designed, so that any errors in the meal timing or size were corrected, diversity score fulfilled, and any energy or nutrient gaps were covered.

Patients at high risk were given a tailored nutritional intervention program as previously mentioned for the intermediate risk and were in addition referred to the nutritional support team.

All enrolled patients were followed up again after 1 and 3 months using the same study tools.

Statistical analysis:

Data were collected, revised, coded, and entered to the Statistical Package for Social Science (IBM SPSS) version 23. The quantitative data were presented as mean, standard deviations and ranges when their distribution was parametric and median, inter-quartile range (IQR) when data was non-parametric. Qualitative variables were presented as numbers and percentages.

The comparison between groups with qualitative data was done by the Chi-square test and Fisher exact test instead of the Chi-square only when the expected count in any cell found less than 5.

The comparison between two groups having quantitative data with parametric distribution was done by t-test while non-parametric data was done by the Mann-Whitney test.

The comparison between more than two independent groups with quantitative data and parametric distribution was done by One Way Analysis of Variance (ANOVA) while non-parametric distribution was done by Kruskal-Wallis.

The comparison between two paired groups with quantitative data and parametric distribution was done by a Paired t-test while non-parametric distribution was done by the Wilcoxon test.

The comparison between more than two paired groups with quantitative data and parametric distribution was done by the Repeated Measures ANOVA test, while non-parametric distribution was done by the Friedman test.

Spearman correlation coefficients were used to assess the correlation between two quantitative parameters in the same group.

The confidence interval was set to 95% and the margin of error accepted was set to 5%. The p-value was considered significant if more than 0.05.

The total number of the study population was 90 patients divided equally between the 2 hospitals (45 in each). Age of enrolled patients ranged from 2 to 5 years with mean ± SD of3.56 ± 0.943 years in Bolaque hospital and 3.37 ± 1.00 years in El-Badrashine hospital. Age showed no significant difference between the two groups. Regarding gender distribution, each group involved 22 females (48.9%) and 23 males (51.1%).

On comparing between the anthropometric measurements at the initial and follow up visits of the study group in Bolaque hospital, there was highly significant increase in weight and height and non-significant change in the rest of the parameters as seen in table 1. Although there was a non-significant difference between the three visits as regards STAMP score, there was a slight increase in numbers of patients at low and intermediate-risk and a slight decrease in the patients at high risk of malnutrition.

Comparison between the nutritional analysis at the initial and follow up visits of the study group in Bolaque hospital showed highly significant increase in caloric intake, sodium, carbohydrates, fat, water, fibre, protein, and calcium. Additionally, there was non-significant increase in the intake of zinc and iron as shown in table 2.

On comparing between the anthropometric measurements at the initial and follow up visits of the study group in El-Badrashine hospital, weight and height showed significant increase, while the rest of the parameters showed non-significant change as shown in table 3. Regarding the STAMP score, there was a distinct but non-significant increase in numbers of patients who were at intermediate risk as well as a slight decrease in patients at high risk of malnutrition.

Comparison between the nutritional analysis at the initial and follow up visits of the study group in El-Badrashine hospital showed significant increase in caloric intake, sodium, carbohydrates, calcium, fiber, fat and water. In addition, there was non-significant increase in the intake of zinc, iron and protein as shown in table 4.

Comparing the anthropometric measurements in the initial visit between the two hospitals showed significant difference in only the height z-score and BMI. The rural area group showed a higher number of patients who were marginally stunted (33.3%), and a higher number of patients who were stunted (20%). Moreover, only the rural area group showed severely stunted patients (4.4%). Regarding BMI the urban group showed significantly lower BMI. Initial STAMP score results showed no significant difference between the two studied groups.

When comparing both groups as regards nutritional analysis in the initial visit, there was no significant difference in the intake of calories, nor any of the macronutrients or the micronutrients.

Comparing the anthropometric measurements in the first month follow up visit between the two hospitals showed significantly higher height values in the urban group with p-value 0.019. Regarding the height z score, it was significantly higher in the urban group with p-value 0.005 since the rural group had 33.3% marginally stunted which was higher than the urban group (15.6%) and 20% stunted patients which was higher ae well (6.7% in the urban patients) and uniquely had severely stunted patients.

Regarding STAMP score, there was a significant difference between the two groups at the first month follow up visit with p-value 0.038. The rural group showed a higher number of patients who were at high risk (22.2%), compared to the urban one (11.1%) and more patients at intermediate risk as well (33.3% and 17.8% respectively).

On comparing urban and rural study groups in the first follow up visit as regards nutritional analysis, there was a significantly higher fat intake in the urban group with p-value 0.027. Although there was no significant difference between the two groups in the other nutrients, the rural group showed distinctly higher zinc intake, and the urban group showed higher intake in total calories, sodium, CHO, Ca, water, iron, fiber, and protein.

When comparison was done between the two studied groups in the second follow up visit, results were similar to the first follow up visit. There was a significantly higher height values in the urban group with p-value 0.012. Regarding STAMP score, there was a significant difference between the two groups with p-value 0.019. The urban group showed a higher number of patients at low risk (75.6%), compared to the other group (46.7%). The rural group showed a higher number of patients at intermediate risk (33.3%), compared to the urban group (15.6%) and a higher number of patients at high risk (20%), compared to urban one (8.9%).

On comparing both studied groups as regards nutritional intake in the second follow up visit, there was significantly higher intake of fat and protein in the urban group with p values of 0.024 and 0.018 respectively

Comparison between the groups as regards the effect of nutritional intervention showed non-significant changes in the studied anthropometric measurements and nutritional analysis parameters (table 5).

Correlation between STAMP score and all study parameters of the total study group in the total of the three visits was done. There was significant inverse correlation between STAMP score and all study parameters in the first visit. Additionally, there was significant inverse correlation in the first follow up visit but it didn`t reach significant difference with age. Regarding correlation between STAMP and the study parameters in the second follow up visit, there was significant inverse correlation except with age and BMI where the correlations were distinctly inverse but without significant difference.

Results of the current study revealed that moderate stunting was significantly higher in El-Badrashine outpatient clinic patients (20%) presenting the rural area compared to 6.7% in urban Bolaque. Similar results were found in a study done by Mahfouz and collaborators, in which prevalence was 19.1% in rural upper Egypt [10]. Additionally, a study done in Suhag, which is a southern Egyptian governorate revealed more moderate stunting in rural areas compared to urban ones, but the numbers were higher than the current study (25.6% and 21.6% respectively) [11]. Moreover, a study done among children and adolescents living in the Middle East and North Africa region revealed that the prevalence of stunting was 34.1% in rural and 12.4% in urban areas [12]. In Tangail district in Bangladesh, Islam et al., (2014) reported moderate stunting among 144 under-five children to be 44.45% in rural and 2.78% in urban areas [13].

As regards mild (marginal) stunting, it was 33.3% in the studied patients from rural hospital, compared to 17.8% in the urban area. This disagrees with Islam and collaborators (2014) who reported marginal stunting to be 12.5% in rural compared to 16.6% in urban [13]. Nevertheless, the results of the current study agree with the latter authors in their report concerning severe stunting which is only present in their rural area patients (5.56%).

In the studied urban group, there were no underweight children, while 4.4% of children from the rural hospital were underweight. Similarly, a study done in Libya documented higher prevalence of underweight in rural areas (4.9%) than in urban areas (4.1%) [14]. Additionally, underweight was significantly more prevalent in the rural schools, in a study done in Morocco [15].

Mild or marginal underweight was detected among 15.6% of the urban area patients compared to rural ones who showed 22.2% marginal underweight. Similarly, in Tangail district of Bangladesh a higher percentage of children who had marginal underweight were in rural areas (38.8%) compared to urban (8.34%) [13].

Although Katsagoni and collaborators [16] documented that the Paediatric Yorkhill Malnutrition Score (PYMS) showed the best diagnostic accuracy compared to STAMP in pediatrics, the superiority of STAMP in detecting patients at risk of malnutrition compared to other screening stools as StrongKids was previously reported in literature [17-19].

STAMP was used as a malnutrition screening tool in the current study and its score results revealed that among the rural group 17.8% were at intermediate risk and 35.6% were at high risk of malnutrition. In the urban group 8.9% were at intermediate risk and 20% were at high risk. Higher percentages were reported in studies which screened hospitalized patients. For instance, in 2019, Moreno and collaboratorsfound a high risk of malnutrition in 48.3% of patients and a moderate risk in 48.2% and reported that the higher STAMP score was associated with longer length of hospital stay (P<0.01) and greater severity (P<0.01) [20].

Nutritional analysis of the study group intake showed higher intake in all macronutrients and micronutrients in patients from the urban hospital compared to rural one, but the differences were insignificant. This finding could contribute to the anthropometric measurements` differences between patients from studied urban and rural areas. From another prespective, in a study done by Abd El-Latife and collaboratorsin Sharkaia Egyptian governorate, the mean total intake of most nutritional components in the diet considerably exceeded the standards in both urban and rural preschool childrenwhich explained their finding of overweight among their series of rural and urban children(one in five and one in four respectively) [21].

Abdel-Rahman et al., reported that in Egypt, urban areas have captured the largest percentage of public health spending, whereas rural areas have invariably received less attention and are poorly funded which can explain the differences detected between the anthropometric measurements and nutritional data of the studied urban and rural areas. Moreover, rural areas are characterized by low levels of income, education, and economic development [22].Additionally, Sharaf and Rashad [23] suggested earlier that while child health has improved tremendously in Egypt, socioeconomic discrepancies remain considerable which can explain the more undernutrition burden in rural areas.

Concerning the effect of nutritional intervention program, there was significant increase in weight of children after 3 months in both rural and urban patients. Similar result was documented in Pradesh India, as 100 children aged from 13 to 36 months had significant weight gain after nutritional intervention program for 6 months [24], and in Kolkata India Debnath and Agrawal, documented weight gain after one-month nutritional intervention program among 104 three to six years old children [25].The latter authors also documented height gain in consistency with the current results.

The distinct though non-significant increase in BMI in the currently studied patients also agrees with the report of Debnath and Agrawal, [25].Additionally, there was improvement in STAMP score and an increase in almost all nutritional analysis parameters in the two studied groups after nutritional intervention program.

To explain the above findings, there was a significant increase in calories in patients from both urban and rural outpatient clinics after nutritional educational intervention which is consistent with Debnath and Agrawal who found that 32% of the children were taking less than optimal calorie intake daily, which decreased to 14% after nutrition education session leading to positive changes in children nutritional behavior [25]. Moreover, the increase in nutrients` intake in both studied groups upon nutritional rehabilitation, which reached statistical significance in many of them, is also countable because growth isn`t only about calories especially the height which can be influenced by more than one nutrient. In 2004 Ibrahim et al., concluded that several nutrient deficiencies occur simultaneously in stunted children and can be responsible for the condition among which zinc and magnesium were documented [26].

Based on the previous data, nutritional intervention program caused positive change in weight, height and nutritional behavior which led to decrease in childhood malnutrition. This agrees with Sawyer and collaborators, in Bayelsa State, in Nigeria, who documented that the nutrition intervention program delivered in a primary health care facility can positively change nutrition behavior and prevent childhood malnutrition [27].

Concerning STAMP score there was an inverse correlation between STAMP score and all initial study parameters as well as follow up data, which further proves its prognostic value (STAMP score decreased parallel to the increase in the nutritional intake and anthropometric measurements upon nutritional rehabilitation). This comes in agreement with McCarthy and collaborateurs [9]who reported that STAMP score is a reliable, specific, and sensitive nutritional screening tool in identifying nutrition risk.

In conclusion the studied Egyptian rural area showed more undernutrition burden compared to the urban location. Fortunately, screening of pediatric outpatient clinics allows early detection of malnutrition in children. This ensures prompt intervention tools including parent education and tailored nutritional plan which can lead to improvement of nutritional status disregards the location whether rural or urban.

Limitations

This study has its own limitations. The small sample size and the short nutritional rehabilitation period are among these limitations.

Ethical Approval and Consent to participate

All methods were carried out in accordance with relevant guidelines and regulations. Ethical committee approval at the pediatric department, Faculty of Medicine, Ain Shams University was obtained, and the parents or care givers of each patient gave an informed consent before participating in the study.

Consent for publication

All co-authors have shared in this work and have approved the final manuscript and the submission for possible publication in the Nutrition Journal.

Availability of data and materials

The authors will provide all patients` data upon request.

Competing interests

The authors declare that they have no conflicts of interest.

Funding

There were no external funds received by any of the authors for the current study.

Authors' contributions

Nassar MF substantially contributed to conception and design of the current study. She contributed to analysis and interpretation of data. Professor Nassar drafted the manuscript, revised it for important intellectual content, and she prepared the final form.

Abdel-Wahed MA contributed to the idea of the current study. He contributed to data interpretation. Professor Abdel-Wahed approved the final manuscript form.

Abdelhaleem BA contributed to the idea of the current study. She participated in data analysis. Dr Abdelhaleem approved the final manuscript form.

Ahmed AK contributed to the plan of the practical part of the current study. He contributed to the acquisition and analysis of data. Dr Ahmed approved the final form of the manuscript.

El Kholy HE contributed to the design of the current study. She contributed to the acquisition of data and its interpretation. Dr El Kholy contributed to the editing of manuscript and approved its final form.

Acknowledgements

The authors acknowledge the support of Professor Emam EK, the head of the Clinical Nutrition Unit at the Children`s Hospital, Ain Shams University for his continuous support.

Impact statements

Despite the improvement in child health care, socioeconomic inequalities can cause different malnutrition risks in urban and rural locations.
Early detection for the children at risk of malnutrition by the nutrition screening tools allows for prompt intervention with parents` education and tailored nutrition program disregards the location whether urban or rural.

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Table (1): Comparison between anthropometric measurements at initial and follow up visits for patients from the urban hospital

Bolaque hospital (urban area)		Initial visit	1^st month visit	3^rdmonth visit	One way	p-value	Sig.
Bolaque hospital (urban area)		No. = 45	No. = 45	No. = 45	ANOVA Test	p-value	Sig.
Weight (kg)	Mean±SD	15.17 ± 2.90	15.37 ± 2.94	15.78 ± 2.95	477.809	<0.001	HS
Weight (kg)	Range	10.2 – 21.5	10.3 – 21.8	10.7 – 22.3	477.809	<0.001	HS
Weight z Score	Mild underweight	7 (15.6%)	7 (15.6%)	6 (13.3%)	0.117	0.998	NS
	Underweight	0 (0.0%)	0 (0.0%)	0 (0.0%)
	Normal	38 (84.4%)	38 (84.4%)	39 (86.7%)
Height (cm)	Mean±SD	97.46 ± 8.82	98.08 ± 8.76	99.25 ± 8.66	1466.687	<0.001	HS
Height (cm)	Range	80 – 113	80.7 – 113.6	82 – 114.5	1466.687	<0.001	HS
Height z Score	Normal	34 (75.6%)	35 (77.8%)	35 (77.8%)	0.110	0.998	NS
	Mild stunted	8 (17.8%)	7 (15.6%)	7 (15.6%)
	Moderate Stunting	3 (6.7%)	3 (6.7%)	3 (6.7%)
	Severe stunted	0 (0.0%)	0 (0.0%)	0 (0.0%)
BMI	Mean±SD	15.86 ± 1.09	15.88 ± 1.12	15.93 ± 1.11	2.711	0.088	NS
BMI	Range	13.9 – 18.9	14 – 18.9	14 – 18.8	2.711	0.088	NS
BMI z Score	Normal	22 (48.9%)	20 (44.4%)	20 (44.4%)	0.267	0.991	NS
	Overweight	17 (37.8%)	18 (40.0%)	18 (40.0%)
	Obese	6 (13.3%)	7 (15.6%)	7 (15.6%)
STAMP Score	Low risk	32 (71.1%)	32 (71.1%)	34 (75.6%)	3.783	0.436	NS
	Intermediate risk	4 (8.9%)	8 (17.8%)	7 (15.6%)
	High risk	9 (20.0%)	5 (11.1%)	4 (8.9%)

Table (2): Comparison between nutritional analysis at initial and follow up visits for patients from the urban hospital

Bolaque hospital (urban area)		Initial visit	1^st month visit	3^rdmonth visit	One-way AVOVA test	p-value	Sig.
		No. = 45	No. = 45	No. = 45
Calories (Kcal)	Mean±SD	1282.85 ± 542.53	1494.92 ± 447.38	1539.97 ± 390.25	15.677	<0.001	HS
	Range	344 – 2334	505 – 2411.5	712.3 – 2616.2
Sodium (mg)	Mean±SD	2265.54 ± 1399.63	2753.45 ± 1274.44	2887.13 ± 1246.38	8.053	0.001	HS
	Range	414 – 6003.7	521.5 – 6373	589 – 6018.9
CHO (g)	Mean±SD	186.32 ± 94.39	213.22 ± 73.04	219.84 ± 70.49	6.532	0.004	HS
	Range	18.1 – 387.5	54.4 – 341.4	52.6 – 434
Ca (mg)	Mean±SD	675.72 ± 387.05	842.90 ± 352.94	874.37 ± 417.46	4.319	0.016	S
	Range	71.9 – 1636.2	159.3 – 1624.5	155.5 – 1997.6
Fat (g)	Mean±SD	36.98 ± 14.18	46.18 ± 15.59	46.24 ± 12.03	11.131	<0.001	HS
	Range	16.2 – 68.7	19.4 – 101.8	16.7 – 68.2
Water (ml)	Mean±SD	473.42 ± 191.44	575.09 ± 197.72	592.45 ± 227.59	5.845	0.004	HS
	Range	130.1 – 935	245.4 – 1119.1	175.7 – 1060.7
Zinc (mg)	Mean±SD	7.31 ± 3.89	7.65 ± 2.84	12.51 ± 27.29	1.623	0.210	NS
	Range	1.2 – 15.3	2.2 – 15.5	3.5 – 190.5
Iron (mg)	Mean±SD	10.69 ± 9.02	11.51 ± 11.77	11.17 ± 4.93	0.108	0.898	NS
	Range	0.8 – 50.8	1.4 – 84.2	2.8 – 24.6
Fiber (g)	Mean±SD	4.43 ± 3.08	5.66 ± 2.62	6.38 ± 3.14	10.222	<0.001	HS
	Range	0.3 – 13.1	0.1 – 11	0.2 – 13.4
Protein (g)	Mean±SD	51.35 ± 23.56	58.46 ± 18.65	61.75 ± 15.09	7.874	0.001	HS
	Range	12 – 104.7	22.9 – 105.9	24.5 – 102.7

Table (3): Comparison between anthropometric measurements at initial and follow up visits for patients from the rural hospital

El-Badrashine hospital (rural area)		Initial visit	1^st month visit	3^rdmonth visit	One-way AVOVA test	p-value	Sig
El-Badrashine hospital (rural area)		No. = 45	No. = 45	No. = 45	One-way AVOVA test	p-value	Sig
Weight (kg)	Mean ± SD	14.19 ± 2.44	14.38 ± 2.47	14.76 ± 2.50	182.673	<0.001	HS
Weight (kg)	Range	10.4 – 20	10.7 – 20.3	11.2 – 20.7	182.673	<0.001	HS
Weight z Score	Mild underweight	10 (22.2%)	10 (22.2%)	9 (20.0%)	0.089	0.999	NS
	Underweight	2 (4.4%)	2 (4.4%)	2 (4.4%)
	Normal	33 (73.3%)	33 (73.3%)	34 (75.6%)
Height (cm)	Mean ± SD	93.26 ± 8.07	93.85 ± 8.03	94.69 ± 8.23	9.181	0.004	HS
Height (cm)	Range	71.5 – 109	72.2 – 109.5	73.5 – 110.5	9.181	0.004	HS
Height z Score	Normal	19 (42.2%)	19 (42.2%)	19 (42.2%)	0.000	1.000	NS
	Mild stunted	15 (33.3%)	15 (33.3%)	15 (33.3%)
	Moderate Stunting	9 (20.0%)	9 (20.0%)	9 (20.0%)
	Severe stunted	2 (4.4%)	2 (4.4%)	2 (4.4%)
BMI	Mean ± SD	16.26 ± 1.48	16.27 ± 1.49	16.30 ± 1.49	0.831	0.404	NS
BMI	Range	13.3 – 20.9	13.4 – 20.9	13.4 – 20.9	0.831	0.404	NS
BMI z Score	Normal	16 (35.6%)	17 (37.8%)	16 (35.6%)	0.229	0.993	NS
	Overweight	14 (31.1%)	13 (28.9%)	15 (33.3%)
	Obese	15 (33.3%)	15 (33.3%)	14 (31.1%)
STAMP Score	Low risk	21 (46.7%)	20 (44.4%)	21 (46.7%)	5.068	0.280	NS
	Intermediate risk	8 (17.8%)	15 (33.3%)	15 (33.3%)
	High risk	16 (35.6%)	10 (22.2%)	9 (20.0%)

Table (4): Comparison between all visits of the study group in the rural hospital as regards the nutritional analysis

El-Badrashine hospital (rural area)		Initial visit	1^st month visit	3^rdmonth visit	One way ANOVA test	p-value	Sig
		No. = 45	No. = 45	No. = 45
Calories (Kcal)	Mean ± SD	1188.44 ± 409.13	1334.68 ± 357.98	1408.80 ± 339.99	22.920	<0.001	HS
	Range	354.6 – 2505.4	685 – 2325.5	734.2 – 2250
Sodium (mg)	Mean ± SD	2170.46 ± 1280.20	2550.02 ± 1087.19	2830.27 ± 1331.62	9.614	0.001	HS
	Range	269.2 – 6855.8	697.3 – 6325	420.1 – 6200
CHO (g)	Mean ± SD	171.63 ± 67.32	192.28 ± 57.15	207.84 ± 62.42	13.793	0.000	HS
	Range	37.6 – 375.2	84.9 – 355.20	73.5 – 361.9
Ca (mg)	Mean ± SD	535.41 ± 374.70	828.16 ± 406.62	825.01 ± 425.58	10.408	<0.001	HS
	Range	56.7 – 1334.5	137.9 – 2442.2	126 – 2450
Fat (g)	Mean ± SD	34.57 ± 12.76	39.66 ± 11.74	40.86 ± 10.14	6.777	0.002	HS
	Range	14.9 – 66.2	20.7 – 72.1	18.8 – 66.5
Water (ml)	Mean ± SD	447.65 ± 180.59	524.08 ± 162.21	549.34 ± 159.60	7.026	0.002	HS
	Range	72.9 – 824.6	236.5 – 1033	246.5 – 912.4
Zinc (mg)	Mean ± SD	7.01 ± 3.05	9.15 ± 13.80	9.75 ± 13.70	0.749	0.453	NS
	Range	1.8 – 15.9	2.5 – 97.9	1.3 – 97.9
Iron (mg)	Mean ± SD	9.55 ± 5.82	10.78 ± 14.24	9.91 ± 3.68	0.299	0.625	NS
	Range	2.2 – 27.12	1.9 – 101.7	2.2 – 19.1
Fiber (g)	Mean ± SD	4.71 ± 2.76	5.47 ± 2.23	6.03 ± 3.04	5.361	0.010	S
	Range	1.2 – 13.9	1.3 – 12.2	1.2 – 13.4
Protein (g)	Mean ± SD	48.67 ± 19.24	52.09 ± 17.98	53.83 ± 16.13	3.115	0.059	NS
	Range	11.7 – 107.2	23.2 – 115.5	12.2 – 98.4

Table (5): Comparison between the study groups of the urban and rural hospitals as regards the increments in the anthropometric measurements and nutritional analysis parameters after 3 months follow up

Difference after 3^rd visit	Bolaque (urban)		El Badrashine (rural)		t-test	p-value	Sig
Difference after 3^rd visit	Mean	SD	Mean	SD	t-test	p-value	Sig
Weight (kg)	0.61	0.17	0.57	0.26	0.864	0.390	NS
Height (cm)	1.78	0.29	1.43	2.77	0.843	0.401	NS
BMI	0.07	0.24	0.04	0.26	0.569	0.571	NS
STAMP score	-0.36	0.74	-0.40	1.29	0.180	0.857	NS
Calories	257.12	363.82	220.36	255.98	0.554	0.580	NS
Sodium	621.58	1090.17	671.51	1242.32	0.203	0.839	NS
CHO	33.53	63.69	36.21	50.08	0.222	0.824	NS
Ca	198.65	476.31	289.60	539.52	0.848	0.398	NS
Fat	9.25	15.03	6.28	12.22	1.029	0.307	NS
Water	119.03	232.10	101.68	187.40	0.390	0.697	NS
Zinc	5.20	26.51	2.74	14.06	0.550	0.584	NS
Iron	0.48	9.01	0.36	4.92	0.078	0.938	NS
Fiber	1.94	2.77	1.32	3.26	0.972	0.333	NS
Protein	10.40	20.08	5.16	15.48	1.386	0.169	NS

No competing interests reported.

Outpatient Nutritional Screening and Rehabilitation of Malnourished Egyptian Children: Are Rural Areas at More Risk?

Status:

Version 2

Abstract

Background

Aim of the study:

Subjects and Methods:

Results

Conclusion

Introduction

Patients And Methods

Results

Discussion

Declarations

References

Tables

Additional Declarations

Status:

Version 2