Risk Factors for Predicting Diarrheal Duration

8/18/2019 Risk Factors for Predicting Diarrheal Duration

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ORIGINAL ARTICLE

Risk Factors for Predicting Diarrheal Duration

and Morbidity in Children with Acute Diarrhea

Archana B. Patel & Ronithung Ovung &

Neetu B. Badhoniya & Michael J. Dibley

Received: 19 October 2010 /Accepted: 12 September 2011 /Published online: 24 September 2011# Dr. K C Chaudhuri Foundation 2011

Abstract

Objective To identify baseline risk factors for prolongeddiarrheal duration and subsequent complications in children

aged 6 to 59 mo with acute diarrhea who participated in a

micronutrient clinical trial in a tertiary care hospital.

Methods The adjusted odds ratio or incidence risk ratios (IRR)

of the baseline variables for prolongation of diarrheal duration

(cox proportional hazard model), diarrhea >7 d (multiple

logistic regressions), severe dehydration experienced after

hospitalization (poisson regression models) was estimated.

Results Fever (OR 1.10, 95% CI 1.02 – 1.19, p=0.02), dehy-

dration (OR 1.32, 95% CI 1.10 – 1.59, p=0.003), dysentery

(OR 1.41 95% CI 1.09 – 1.82, p=0.008), those who received

medications (OR 1.19, 95% CI 1.03 – 1.39, p=0.02), and

weight for age Z-score ≤2 (OR 1.25, 95% CI 1.07 – 1.46,

p=0.004) were at a greater risk of prolonged diarrhea.Diarrhea >7 d was associated with younger age (OR 1.08,

95% CI 1.03 – 1.14, p=0.003), female child (OR 2.33, 95% CI

1.19 – 4.55, p=0.013), diarrheal duration before enrolment (OR

1.06, 95% CI 1.04 – 1.09, p


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last 50 y, diarrheal disease continues to be a major killer of

children aged less than 5 y and a principal cause of

morbidity for most impoverished children of the world [2, 3].

One third of the hospital admissions in developing

countries are due to diarrhea related diseases, with 17%

mortality [4, 5]. In India, 9% of children under five had

diarrhea and 1% of these children had blood in their stools

in two wk preceding the third National Family HealthSurvey (2005 – 6) [6]. Although the majority of episodes of

diarrhea are self-limited, the proportions that experience

mortality are due to dehydration and complications due to

prolongation of diarrhea [7]. Identification of risk factors for

prolongation of acute diarrhea in children can help in the

management, planning and prevention of complications due

to acute diarrhea and subsequent mortality. Although there

are many studies that report epidemiological risk factors for

acute diarrhea in children, there are few that identify the

risks of prolongation of the episode and its complications in

a cohort of children with acute diarrhea. If children with

these risk factors are provided greater medical attention, it may be possible to reduce childhood morbidity and

mortality. The aim of the present study was to identify

baseline factors in the study population that are associated

with prolonged duration of acute diarrhea.

Material and Methods

In the present study the authors determined the risk factors

that predicted diarrheal duration and subsequent morbidity

in 6 to 59-mo-old children, participating in a randomized

control trial which evaluated the effect of zinc and copper

in treatment of acute diarrhea, admitted at the Indira Gandhi

Government Medical College, Nagpur India [8]. This study

was a part of a micronutrient clinical trial of three arms

namely, placebo (Pl), zinc (Zn) only, and zinc and copper

(Zn+Cu) arms, in 808 children aged 6 to 59 mo of acute

diarrhea, which received ethical clearance from both the

involved institutes. The detailed methods for the trial have

been reported elsewhere [8]. Here the authors report the

baseline characters, nutritional status and etiological agent

of acute diarrhea in children aged 6 mo to 59 mo that

predict the diarrheal duration.

Baseline Assessment

At enrolment, the study research physician collected

information from the mother about: age, gender, duration

of illness (fever, vomiting, diarrhea), dehydration (present

or absent), blood in stools (dysentery or not), immunization

status (as per schedule), any breast feeding, maternal

education in years, number of children in the household,

household assets and facilities, water safety hand sanitation,

intake of anti-diarrheal or antimicrobial agents, type of

rehydration practiced at home, and hemoglobin concentra-

tion (Hemocue method) [9, 10]. The household wealth index,

water and hand sanitation scores were composite indices

derived by scoring different factors that contributed to these

indices using principal component analysis [11]. Factors

assessed for the household wealth index were ownership

of electricity, radio, television, refrigerator, bicycle, scooter and land, main material used for dwelling floor and fuel

used for cooking. For the water safety score the main

source of drinking water, water storage and treatment of

drinking water before use were assessed, and for the hand

sanitation score washing of hands by soap and water, mud,

plain water or not washed before feeding the child and after

going to latrine were assessed. Nutritional status was

assessed by measuring weight and height using standard

methods and calculating weight for age and, weight for

height Z-scores using the World Health Organization 2005

Anthro software [12]. Weight was measured to nearest 100 g

using an electronic scale (Wedderburn Tanita HD-316). For children


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variate analysis was carried out by estimating regression

coefficient or odds ratios (OR) or incidence risk ratios

(IRR) and their 95% confidence interval (CI) for all the risk

factors for diarrheal duration. Cox proportional hazards

model was used to estimate the relative hazards (RH) of

continuation of diarrhea of the baseline covariates. Using

intention to treat analysis, the unadjusted and adjusted OR

or IRR of the baseline variables for three additionaloutcomes (a) diarrhea longer than 7 d from onset(multiple

logistic regression), (b) complications in hospital, and (c)

severe dehydration experienced in hospital after enrolment

was estimated using poisson regression models. A full

model of multiple logistic regression (MLR) and multiple

poisson regression (MPR) included all risk factors mea-

sured in the present study. However, the final model

included the risk factors which were significant in the full

model at α level of 0.25. The level of significance was

fixed at α=0.05, for judging the significance of that

covariate in the final model. Baseline risk factors consid-

ered were age, gender, maternal education, immunization,any breastfeeding, prior duration of diarrhea, duration of

vomiting, stool frequency per day, stool type, any medica-

tion received, weight for age ≤2, dehydration status,

temperature, water safety score, wealth index, hand

washing score, serum zinc and copper level, hemoglobin

Table 1 Baseline characteristics of the children enrolled in the trial

Characteristics n=808

Age mo, mean (SD) 17.9 (11.1)

Male Gender N (%) 477 (59.03)

Mother ’s education schooling yrs, mean (SD) 7 (4.249967

Immunization complete to-date N (%) 549 (68)

Breast feeding/complimentary feeds N (%) 453 (56.1)

Duration of diarrhea, h, mean (SD) 35.4 (20.4)

Number of stool before enrolment mean (SD) 8.5 (4.2)

Duration of vomiting before mean (SD) 20.3 (20.8)

Temperature °C, mean (SD) 98.8 (1)

Dehydration N (%) 174 (21.5)

Dysentery N (%) 78 (9.6)

Rota virus diarrhea N (%) 169 (21.1)

Received any other medications N (%) 365 (45.2)

Weight for age Z-score ≤2N (%) 426 (52.7)

Household wealth index mean (SD) −0.0001 (1)

Water safety score mean (SD) 1.8 (0.93)

Hand washing score mean (SD) 1.2 (1.04)

Serum zinc μ g/dl, mean (SD) 71.2 (32.5)

Serum Copper μ g/dl, mean (SD) 123.5 (36.4)

Hemoglobin% g/dl, mean (SD) 9.7 (1.9)

Table 2 Relative hazards for

continuation of diarrhea in

children

Baseline variables Unadjusted Adjusted

OR (95% CI) P OR (95% CI) P

Zinc 1.05 (0.90, 1.22) 0.57

Zinc and Copper 1.02 (0.88, 1.18) 0.81

Age (mo) 0.98 (0.98,0.99)


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and ELISA test (Premier Rotaclane) was used for rotavirus

antigen detection.

Results

The baseline characteristics of the study population are

shown in Table 1. The univariate and multivariate hazardratios of baseline variables associated with continuation of

diarrhea are shown in Table 2 and that for diarrhea >7 d is

shown in Table 3. Clinical indicators such as younger age

(increased risk for continuation of diarrhea by 24% for age

reduction by each year), fever, blood in stools, weight for

age Z-score ≤2, duration of diarrhea at enrolment were

common risk factors for continuation of diarrhea and for

diarrhea >7 d. It is important to note that receiving zinc

supplement, lower sanitation (water safety and hand

washing) score, baseline zinc and anemia had no impact

on duration of diarrhea. Those children who were dehy-

drated (6.69, 95% CI 2 3.01, 14.85, p


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reviewed inpatient gastro-enteritis management found that

children with mucus and blood in their stools, fever on

admission and received antibiotics were more likely to have

bacterial pathogen with longer duration of stay in the

hospital. This is consistent with the findings of the present

prospective study and other studies worldwide [15 – 17].

Malnutrition was also a risk factor in the present study.

Prolonged diarrhea is a recognized risk factor for malnutri-tion in the low income countries and vice versa malnutrition

can be a risk factor for dehydration and prolongation of

diarrhea [18, 19]. In the present study 52.7% of the study

children had weight for age Z-score ≤2 and the risk of

continued diarrhea in this population was 25% more than

children with no malnutrition. Protein energy malnutrition

retards the repair of the damaged intestinal epithelium and

can prolong diarrhea [20]. Duration of diarrhea at admission

is also of clinical importance to monitor diarrheal severity.

The severity of diarrhea at enrolment was the most

important predictor for prolongation of diarrhea >4 d in

another study that evaluated the effect of zinc and copper mixed with ORS for treatment of acute diarrhea [21].

Similarly, presence of dehydration at enrolment could also

reflect severity of diarrhea and have been recognized to

increase the duration of diarrhea [22]. The only additional risk

factor for diarrhea >7 d was gender. Females had a higher

risk of experiencing diarrhea >7 d. This could be a regional

observation as the epidemiology of prolonged diarrhea

differs across studies [23 – 28].

The risk factors for severe dehydration after admission

were some dehydration, incomplete immunization and no

medication received at enrolment. These are the children who

would be experiencing more frequent stools or vomiting or

have not received adequate ORS or medical attention early in

the course of the illness. Despite treatment and monitoring in

hospital they were still susceptible to severe dehydration and

complications. This indicates that children with diarrhea who

receive early attention and adequate management even at

home are less likely to suffer either prolongation of diarrhea,

severe dehydration or its complications. Another case control

study from this region found similar baseline risk factors of

younger age, malnutrition and severity of illness for moderate

or severe dehydration [26].

Conclusions

Few prospective studies have identified baseline clinical

risk factors that predict morbidity in a cohort of children

with acute diarrhea for better monitoring of these children.

It was observed that clinical indicators such as younger

children, those malnourished, having fever, diarrhea with

blood, received no medications, longer duration of diarrhea

at admission and those with dehydration at the time of

hospitalization need to be carefully monitored as they are at

risk for prolonged diarrhea.

Acknowledgements The authors extend their thanks to all the

women, children and their families who participated in the trial, also

thank the following members of the research team who contributed to

the successful implementation of the study: Mr. Hussaini Ali and Mr.

Gadkari (Universal Medicaments Pharmacists), Ms. Smita Puppulwar

and Ms. Shubhangi Puranik. Authors are grateful to Prof. CatherineD’Este, Dr. AV Shrikhande and Dr. Nitin Kimmatkar, the members of

the treatment effects monitoring committee, who reviewed the

unexpected trial events and conducted an interim analysis. The project

was supported by a Wellcome Trust Collaborative Research Initiative

Grant (number 068664/Z/02/Z).

Contributions AP:developed the study protocol, questionnaires and

clinical trial procedures, directed the conduct of the trial, data analysis,

data interpretation and wrote the first draft of the paper; RO: helped in

reviewing literature, drafting and editing the paper; NB: helped with

data analysis and editing the manuscript; MJD: contributed to the

development of the protocol, helped in the development of study

questionnaires and trial procedures, contributed to the data analysis,

data interpretation and edited the paper. All authors reviewed drafts of

the manuscript, read and approved the final draft.

Conflict of Interest None.

Role of Funding Source Wellcome Trust Collaborative Research

Initiative Grant.

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