DEMOGRAPHIC

AND

HEALTH

SURVEYS

DHS WORKING PAPERS

2015 No. 116

Adam Bennett

Thom Eisele

Joseph Keating

Josh Yukich

March 2015

This document was produced for review by the United States Agency for 

International Development.

Global Trends in Care Seeking and 

Access to Diagnosis and 

Treatment of Childhood Illnesses

Global Trends in Care Seeking and Access to Diagnosis and 

Treatment of Childhood Illnesses 

Adam Bennett1

Thom Eisele2

Joseph Keating2

Josh Yukich2

ICF International 

Rockville, Maryland, USA 

March 2015 

1

Malaria Elimination Initiative, Global Health Group, University of California, San Francisco 

2

Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical 

Medicine 

Corresponding author: Thom Eisele, Center for Applied Malaria Research and Evaluation, Department of Global 

Health Systems and Development, Tulane University School of Public Health and Tropical Medicine, 1440 Canal 

Street, Suite 2200, New Orleans, LA 70112 USA; Phone: +1-504-988-3542; Fax: +1-504-988-1568; Email: 

teisele@tulane.edu
Acknowledgments: 

Lia Florey (ICF International), Erin Eckert (USAID), and Rene Salgado (USAID) are thanked for their 

review and comment on the draft report. Zhe Xu (Tulane University) is sincerely thanked for his help with 

data management and data processing. 

Editor: Sidney Moore 

Document Production: Natalie La Roche 

This study was carried out with support provided by the United States Agency for International 

Development (USAID) through The DHS Program (#GPO–C–00–08–00008–00). The views expressed are 

those of the authors and do not necessarily reflect the views of USAID or the United States Government. 

The DHS Program assists countries worldwide in the collection and use of data to monitor and evaluate 

population, health, and nutrition programs. For additional information about The DHS Program, contact 

DHS Program, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; Phone: 

+1 301-407-6500; Fax: +1 301-407-6501; Email: reports@dhsprogram.com; Internet: 

www.dhsprogram.com. 

Recommended citation: 

Bennett, Adam, Thom Eisele, Joseph Keating, and Josh Yukich. 2015. Global Trends in Care Seeking 

and Access to Diagnosis and Treatment of Childhood Illnesses. DHS Working Papers No. 116. Rockville, 

Maryland, USA: ICF International.
i 

CONTENTS 

EXECUTIVE SUMMARY ........................................................................................................... iii

1. INTRODUCTION .............................................................................................................. 1

2. METHODS ......................................................................................................................... 5

2.1 Outcomes and Covariate Measures ......................................................................... 6

2.2 Data Analyses ......................................................................................................... 6

2.3 Assessment of Child, Mother, and Household-level Factors Associated with 

Treatment Seeking for Diarrhea, Fever, and Symptoms of ARI ............................ 7

2.4 Assessment of Trends in Treatment Seeking for Diarrhea, Fever, and 

Symptoms of ARI ................................................................................................... 8

2.5 Assessment of Distance from the Nearest Health Facility in Malawi 

and Zambia.............................................................................................................. 8

3. RESULTS ......................................................................................................................... 11

3.1 Trends in Treatment Seeking for Diarrhea, Fever, and Symptoms of ARI in 

Children by Subregions......................................................................................... 11

3.2 Meta-analysis of Predictors of Treatment Seeking for Diarrhea, Fever, and 

Symptoms of ARI by Subregions ......................................................................... 13

3.3 Effect of Distance from the Nearest Health Facility on Treatment Seeking for 

Childhood Illnesses in Malawi and Zambia.......................................................... 18

4. DISCUSSION ................................................................................................................... 21

5. CONCLUSIONS............................................................................................................... 25

REFERENCES ............................................................................................................................. 27 

APPENDICES ...............................................................................................................................31 

Appendix A: Prevalence of treatment seeking for diarrhea, fever, and symptoms of 

acute respiratory infection (ARI) ...............................................................35 

Appendix B: Loess regression and linear regression results for trends in treatment 

seeking for diarrhea, by subregions ...........................................................43 

Appendix C: Loess regression and linear regression results for trends in treatment 

seeking for fever, by subregions ................................................................54 

Appendix D: Loess regression and linear regression results for trends in treatment 

seeking for symptoms of acute respiratory infection (ARI), 

 by subregions .............................................................................................66 

Appendix E: Results of subregional and global meta-analyses of predictors of 

treatment seeking for diarrhea, by subregions ...........................................81 

Appendix F: Results of subregional and global meta-analyses of predictors of 

treatment seeking for fever, by subregions ................................................95 
ii 

Appendix G: Results of subregional and global meta-analyses of predictors of 

treatment seeking for symptoms of acute respiratory infection (ARI), 

by subregions ...........................................................................................109 

Table 1. Random effect logistic regression results for factors associated with treatment 

seeking for childhood illnesses in Malawi and Zambia .............................................19 

Figure 1. Map of United Nations geographical subregions with datasets included in study ...... 7

Figure 2. Trends in treatment seeking for diarrhea (A), fever (B), and symptoms of ARI 

(C) in East Africa, 2000-2013 ................................................................................... 12

Figure 3. Trends in treatment seeking for diarrhea (A), fever (B), and symptoms of ARI 

(C) in West Africa, 2000-2013 .................................................................................. 12

Figure 4. Trends in treatment seeking for diarrhea (A), fever (B), and symptoms of ARI 

(C) in South-eastern Asia, 2000-2013 ....................................................................... 13

Figure 5. Trends in treatment seeking for diarrhea (A), fever (B), and symptoms of ARI 

(C) in South America, 2000-2013 ............................................................................. 14
iii 

EXECUTIVE SUMMARY 

Diarrhea, malaria, and acute respiratory infection (ARI) are among the leading causes of 

child mortality worldwide, with the greatest burden concentrated in developing countries. Child 

mortality has declined in recent years as a result of socioeconomic development and affordable 

and effective prevention and treatment options, yet many countries in Asia and Africa are not on 

track to meet Millennium Development Goal (MDG) 4—to reduce child mortality by two-thirds 

by 2015. Although evidence suggests that an increase in targeted interventions can accelerate child 

survival, a strong health care system is a necessary prerequisite for sustained reductions in 

preventable child deaths. 

An investigation into commonalities across countries and regions is needed to understand 

trends in treatment-seeking behavior and how sociodemographic and cultural factors interact to 

influence treatment-seeking modalities. This information will strengthen efficient delivery of care 

across all levels of the health system. Although many studies have documented barriers to 

accessing quality care, systematic analysis of these barriers is lacking. Yet large amounts of data 

are currently available (1) to identify and quantify the major barriers hindering access to quality 

care, and (2) to specify where these barriers are most prominent, relative to health care needs at 

the subnational level. 

This analysis used 258 publically-available datasets from nationally-representative 

household surveys that included individual-level information on treatment-seeking for diarrhea, 

fever, and the symptoms of ARI. The surveys were conducted between 2000 and 2013 and came 

from three sources: Demographic and Health Surveys (DHS), Malaria Indicator Surveys (MIS), 

and Multiple Indicator Cluster Surveys (MICS). Each survey included information on treatment 

seeking for children under age 5, based on reports of the child’s mother or caregiver. For this 

analysis, the survey datasets provided information on treatment seeking for a total of 1,922,225 

children under age 5. The purpose of this paper is as follows: 

1. To assess trends in treatment seeking for diarrhea, fever, and symptoms of ARI among 

children under age 5, across countries and regions, using nationally-representative, 

cross-sectional survey datasets (2000-2013) 
iv 

2. To identify individual, household, and community factors influencing treatment 

seeking for diarrhea, fever, and symptoms of ARI among children under age 5, at the 

country and regional level

3. To perform a meta-analysis at the subregional level to understand factors related to 

treatment seeking for diarrhea, fever, and symptoms of ARI among children under 

age 5.

Most of the subregions covered in this analysis showed substantial variation between 2000 

and 2013 in treatment seeking for the three childhood illnesses: diarrhea, fever, and symptoms of 

ARI. There was no consistent upward trend in treatment-seeking behavior. The results of the 

analysis—which explored both barriers to and facilitators of treatment seeking for childhood 

illness—were, for the most part, in the expected directions. The analysis for Zambia and Malawi 

supports previous research showing that access to treatment, as measured by distance from the 

nearest health facility, is strongly correlated with whether treatment is received. 

Several conclusions can be drawn from the results of this study. First, between 2000 and 

2013, there was considerable variation across countries and regions in progress toward 

improvements in treatment seeking and access to health care for childhood illnesses. Second, many 

factors act as barriers to treatment seeking and accessing treatment for young children with 

diarrhea, fever, and the symptoms of ARI. These factors include mother’s level of education, 

household wealth status, and distance from the nearest health facility. Children of mothers with 

little or no education, children living in households that are in the lowest wealth quintiles, and 

children who live far from the nearest health facility are less likely to be taken for treatment when 

sick than other children. Third, health systems need to be strengthened to improve access to high 

quality and appropriate health services for childhood illnesses. Finally, the data indicate that efforts 

to improve access to health care, such as the ongoing scale-up of community case management, 

need to focus on less-educated mothers in low income households in rural areas to have the greatest 

program impact. 
1 

1. INTRODUCTION 

Diarrhea, malaria, and acute respiratory infection (ARI) are the leading causes of child 

mortality across most regions of the world, with the greatest burden concentrated in low- and 

middle-income countries [1, 2]. While child mortality has been declining in recent years, as a result 

of socioeconomic development and increasing access to effective new-born and child survival 

interventions, many countries in Asia and Africa are not on track to meet Millennium Development 

Goal (MDG) 4—to reduce child mortality by two-thirds by 2015 [1-3]. While there is evidence 

suggesting that an increase in targeted interventions can accelerate child survival [4-6], a strong 

health care system is a necessary prerequisite for sustained reductions in preventable child deaths. 

Ensuring prompt diagnosis and appropriate management of diarrhea, malaria (fever), and 

ARI is crucial for reducing morbidity and mortality among young children. Although an estimated 

43% of fevers among children under age 5 in Africa are due to malaria, only 28% of these children 

were taken for treatment to a public health facility, and only 20% received an anti-malarial drug 

within 24 hours of onset of symptoms (during the period before rapid diagnostic tests for malaria) 

[7]. Additionally, in many low income countries, few children receive appropriate treatment for 

symptoms of diarrhea and ARI. For example, coverage of oral rehydration salts (ORS), used in the 

treatment of diarrhea, was 35% globally between 2008 and 2012. At the same time, while globally 

78% of children with symptoms of ARI were taken to a health care provider, coverage is only 43% 

in low income countries [8]. Less than 30% of children under age 5 with symptoms of ARI in low 

income countries received antibiotics. It is likely that many children are not taken for treatment at 

all, making surveillance and disease management difficult in these countries. To meet MDG 4, all 

cases of diarrhea, fever, and symptoms of ARI must be diagnosed and treated. The main challenge 

is delivering these interventions at scale within the context of sometimes fragile health care 

systems [9]. 

Current policy focuses on providing prompt and effective access to treatment of childhood 

illnesses. The success of this policy hinges on a family’s decisions regarding (1) whether to access 

health care and (2) where to seek health care. These decisions are largely determined by availability 

of health care services but also by social and economic factors, such as religious and cultural 

norms, cost of seeking health care, and acceptability of treatment practices [10]. Barriers to 

accessing the formal health system result from a lack of availability, affordability, or acceptability. 
2 

Individual sociocultural factors play an important role in the decision to seek treatment for 

common childhood illnesses. These factors have been examined in a variety of settings. In 

communities less familiar with the formal health sector, treatment delays often result from low 

treatment seeking for childhood illnesses. This pattern is due to a number of factors including 

limited understanding of disease causation, symptomology, and severity of illness. Delays in 

treatment seeking have also been shown to result from lack of understanding of disease etiologies 

and cultural traditions that prescribe seeking treatment first from nonmedical traditional 

healers [11]. 

Many qualitative studies have examined care-seeking patterns for childhood illness such 

as diarrhea [12], malaria [13], and symptoms of ARI [14]. These studies collectively identify a 

range of individual and contextual factors that influence treatment-seeking behavior: cultural 

beliefs and illness perceptions, severity of illness, location, gender, wealth, and treatment cost [10]. 

These studies conclude that the decision to initiate treatment seeking outside the home is a dynamic 

process characterized by uncertainty and debate. However, few of the studies offer a 

comprehensive quantitative framework for understanding treatment-seeking behavior for 

childhood illness. 

Quantitative studies have concluded that improvements in education may be associated 

with seeking care in public health clinics, as opposed to informal drug shops or use of home 

remedies [15, 16]. The persistence of illness is a primary driver for whether treatment is sought for 

diarrhea or symptoms of ARI. For all three diseases, access to treatment seeking is often hindered 

in other, more fundamental ways. Costs—user fees, lost work time, travel expenses—are 

frequently the primary factor determining health care utilization and the greatest barrier to 

accessing prompt and effective care [9]. Numerous studies have documented a strong relationship 

between low household wealth status, inadequate treatment seeking for fever, and overall lack of 

access to prompt and effective treatment of malaria [17]. The inability to gain access to health 

services is often a direct result of poverty [18]. 

Numerous small-scale studies have shown that distance from the nearest health facility acts 

as a significant barrier to seeking and accessing care for childhood illnesses. Distance can be a 

barrier because of the direct cost of travel to the health facility and the indirect cost of time lost 

during travel to the facility [19-23]. However, research has shown that other factors may supersede 
3 

distance from the nearest facility, including facility characteristics, cost of services, and perceived 

quality of services at the facility [24, 25]. Assessing distance from the nearest health facility 

requires that all facilities be listed and geocoded, which is relatively rare at the national level in 

developing countries. We were unable to identify any studies at the national level that 

quantitatively assess the association between distance from the nearest health facility and 

treatment-seeking behavior for childhood illnesses. 

Study Objectives 

An investigation into commonalities across countries and regions is needed to understand 

trends in treatment-seeking behavior and how socioeconomic, cultural, behavioral, and contextual 

factors interact to influence treatment seeking for the major childhood illnesses of diarrhea, malaria 

(fever), and ARI. This information will strengthen the delivery of care across all levels of the health 

system. While many individual studies have documented factors that are barriers to treatment 

seeking and accessing care, we identified no systematic analyses of these factors in the published 

literature. Large amounts of data currently available from nationally-representative household 

surveys can now be used to identify and quantify individual, household, and community factors 

influencing treatment seeking for childhood illnesses. 

Using available population-based data, the purpose of this paper is as follows: 

1. To assess trends in treatment seeking for diarrhea, fever, and symptoms of ARI among 

children under age 5, across countries and regions, using nationally-representative, 

cross-sectional survey datasets (2000-2013) 

2. To identify individual, household, and community factors influencing treatment 

seeking for diarrhea, fever, and symptoms of ARI among children under age 5, at the 

country and regional level; and 

3. To perform a meta-analysis at the subregional level to understand factors related to 

treatment seeking among children under age 5, for diarrhea, fever and symptoms of 

ARI.
4 
5

2. METHODS 

This analysis uses data from all publically-available, nationally-representative household 

surveys conducted between 2000 and 2013 that included individual-level information on 

treatment-seeking for diarrhea, fever, and symptoms of ARI. These surveys included the 

Demographic and Health Surveys (DHS), Malaria Indicator Surveys (MIS), and Multiple Indicator 

Cluster Surveys (MICS). Each survey included information on treatment seeking for children 

under age five based on responses of the child’s mother or caregiver to questions on the Woman’s 

Questionnaire. Although the questions about symptoms of childhood illness and treatment seeking 

were not identical between the DHS/MIS and the MICS, they are analyzed here in a standardized 

way. 

A total of 248 nationally-representative datasets (DHS, MICS, and MIS) were included in 

this analysis conducted between 2000 and 2013. The number of datasets available for analysis of 

each illness varied—diarrhea (118), fever (200), and symptoms of ARI (223). Child-level 

information on treatment seeking during the previous two weeks was available for 685,049 

children under age 5—diarrhea (151,607), fever (358,821), and symptoms of ARI (174,621). 

Datasets with more than 15% missing for treatment seeking for diarrhea, fever, and 

symptoms of ARI outcomes were excluded from the analysis. The analysis of treatment seeking 

for fevers included 193 datasets with 350,878 children under age 5 with a reported fever in the 

past two weeks. Many datasets only asked about treatment seeking for children who had both fever 

and symptoms of ARI and were thus excluded from this analysis. The analysis of treatment seeking 

for diarrhea included 116 datasets with 27,799 children under age five with reported diarrhea in 

the past two weeks. The MICS does not ask if treatment was sought for diarrhea, only if oral 

rehydration therapy was given, while the MIS does not ask about diarrhea at all; these datasets 

were not included in this analysis. The analysis of treatment seeking for symptoms of ARI included 

214 datasets with 151,607 children under age 5 with reported symptoms of ARI in the past two 

weeks. The MIS does not ask about symptoms of ARI, so these datasets were excluded from the 

analysis. Appendix B summarizes the prevalence of treatment seeking for diarrhea, fever, and 

symptoms of ARI in children under five for each survey. 
6

2.1 Outcomes and Covariate Measures 

Treatment seeking for diarrhea, fever, and symptoms of ARI was defined as the proportion 

of children under age 5 (children <5) who experienced an episode of illness (diarrhea, fever, or 

symptoms of ARI) in the past two weeks, for whom treatment was sought from a formal public or 

private health facility. Symptoms and treatment seeking were based on responses given by the 

child’s mother/caregiver at the time of the interview. Symptoms of ARI in DHS and MIS datasets 

were defined as a cough, plus rapid breathing or shortness of breath. In MICS datasets, ARI was 

defined as above, plus cough in the chest. Formal public and private health facilities were defined 

as all public or private health clinics or any higher-level facility, plus community health workers. 

Places such as stores, shops, pharmacies, and traditional healers were not included as formal public 

or private health facilities. 

For assessing trends in barriers to treatment seeking and facilitators of treatment seeking 

by country, region, and year, several demographic variables were examined. These included 

survey year, child’s age, household wealth quintile, household residence (urban/rural), household 

size, mother’s age, and mother’s level of education. To make covariate point estimates amenable 

to a meta-analysis, the demographic variables were dichotomized based on the most pronounced 

cut points from analysis of their expanded categories. For example, child age in the logistic 

regression models was dichotomized as 0-23 (<24) months and 24-59 months; mother’s age was 

dichotomized as less than age 30 (<30) years and 30 or more (30+) years; mother’s education was 

dichotomized as no education/or only primary and secondary or higher; and household wealth 

quintiles were dichotomized as the two lowest quintiles (lowest and second) and the three highest 

quintiles (middle, fourth, and highest). 

2.2 Data Analyses 

Estimates of treatment seeking were produced for each survey dataset, and aggregate 

values were calculated for 15 of the 22 United Nations geographical subregions for which datasets 

were available (Figure 1). The analysis included 95% confidence intervals (CI), calculated using 

survey-weighted standard errors to account for clustering at the primary sampling unit (PSU) level. 
7

Figure 1. Map of United Nations geographical subregions with datasets included in study 

Source: United Nations 

2.3 Assessment of Child, Mother, and Household Factors Associated with Treatment 

Seeking for Diarrhea, Fever, and Symptoms of ARI 

Random effects logistic regression models were used to assess child, mother, and 

household factors associated with treatment seeking for diarrhea, fever, and symptoms of ARI. 

The primary sampling unit (PSU) within each dataset was used as the random effect. The analysis 

was limited to children that had diarrhea, fever, or symptoms of ARI in the past two weeks. Each 

analysis was conducted at the dataset level with a common set of six covariates: (1) child sex, (2) 

child age, (3) mother’s age, (4) mother’s education, (5) residence (urban or rural), and (6) 

household wealth quintile. All the regression models were carried out in SAS. 

Results from the regression models for each outcome were then grouped by subregion—

UN subregions have been used in this study—and a random effects meta-analysis was conducted 

to assess common characteristics associated with treatment seeking in each subregion and globally. 

The meta-analysis was conducted in R using the DerSimonian-Laird random effects estimator 

option in the metan package. 
8

2.4 Assessment of Trends in Treatment Seeking for Diarrhea, Fever, and Symptoms 

of ARI 

Trends over time were assessed for each country in which multiple datasets were available 

over time and each subregion, using locally-weighted regression (LOESS). Loess regression 

curves were estimated using the loess function in R. In loess regression the α parameter defines 

the span of the data included in calculation of the local slope as well as the weight given to closerversus-farther away points in the time series. The α parameter was varied between 0.5 and 2, where 

smaller values give greater weight to recent data trends. Statistical estimates of trends over time 

were produced for each outcome by subregion using a child-level logistic regression model with 

year as the primary covariate and controlling for socio-demographic factors across children. Forest 

plot figures were produced to illustrate which factors were associated with each of the three 

treatment-seeking outcomes, after controlling for year. 

2.5 Assessment of Distance from the Nearest Health Facility in Malawi and Zambia 

In Malawi and Zambia geo-coordinates of all public and private health care providers as of 

2010 were available. These coordinates were matched with the geo-coordinates of the primary 

sampling units in five survey datasets: Malawi 2004 DHS [26], Malawi 2010 DHS [27], Malawi 

2012 MIS [28], Zambia 2007 DHS [29], and Zambia 2010 MIS [30]. The datasets were pooled for 

this analysis, with the Primary Sampling Unit (PSU) used as the random effect. Euclidean distance 

between each PSU centroid and the nearest facility was estimated within ArcGIS. 

Following exploratory analysis, households were categorized into four distance categories: 

<1.9 km from the nearest facility; 1.9 km to 3.5 km from the nearest facility; 3.6 km to 5.8 km 

from the nearest facility; and >5.8 km from the nearest facility. Other covariates included in this 

analysis were child’s sex, child’s age (in years), mother’s age (categorized as <20 years, 20-29 

years, 30-39 years, and 40+ years), residence (urban or rural), and household wealth quintile. Type 

of facility attended and dataset were included as fixed effect control variables. It was hypothesized 

that the effect of distance from the nearest health facility might be modified by urban-rural 

residence. This interaction (distance x urban-rural) was tested and found to be non-significant; the 

analysis was therefore pooled across urban-rural areas. 
9

The combined Malawi and Zambia (DHS and MIS) datasets comprise a total of 42,349 

children under age 5. The analysis of treatment seeking for diarrhea included three datasets with 

10,868 children under age 5 with reported diarrhea in the past two weeks. The analysis of treatment 

seeking for fever included four datasets with 8,953 children under age 5 with a reported fever in 

the past two weeks. The analysis of treatment seeking for symptoms of ARI included four datasets 

with 5,142 children under age 5 with reported symptoms of ARI in the past two weeks. The MIS 

did not ask about diarrhea and symptoms of ARI.
10 
11 

3. RESULTS 

3.1 Trends in Treatment Seeking for Diarrhea, Fever, and Symptoms of ARI in Children 

by Subregions 

Appendix B presents the Loess regression and linear regression results for trends in 

treatment seeking for diarrhea, fever, and symptoms of ARI by subregions. Subregions with fewer 

than two survey datasets were not included. 

Trends in treatment seeking for diarrhea, fever, and symptoms of ARI between 2000 and 

2013 were highly variable by subregion. There was a significant increase in treatment seeking for 

diarrhea over this period in Western Africa (p=0.004), Eastern Africa (p=0.002), South-eastern 

Asia (p=0.026), and Western Asia (p=0.025); other regions saw no significant increase. For 

treatment seeking for fever, there was a significant increase in Western Africa (p=0.030) and 

marginally significant increases in South-eastern Asia (p=0.050) and Southern Africa (p=0.073) 

over this period; other regions saw no significant increase. For treatment seeking for symptoms of 

ARI, there was a marginally significant increase in South-eastern Asia (p=0.063), Western Asia 

(p=0.066), and Central America (p=0.072); other regions saw no significant increase. 

A more in-depth look between 2000 and 2013 indicates that among those subregions with 

a reasonable number of point estimates—Eastern Africa, Western Africa, South-eastern Asia, and 

South America—treatment seeking is highly variable by illness symptoms as well as subregion. 

Treatment seeking across countries in Eastern Africa ranged from 14% to 72% for symptoms of 

diarrhea, 18% to 100% for fevers, and 21% to 76% for symptoms of ARI, with a significant 

increase over this period in treatment seeking for diarrhea [Figure 2, Appendices A-D]. 

Treatment seeking across countries in Western Africa, between 2000 and 2013, ranged 

from 12% to 51% for symptoms of diarrhea, 19% to 74% for symptoms of fever, and 28% to 79% 

for symptoms of ARI, with a significant increase over this period in treatment seeking for diarrhea 

and fever [Figure 3, Appendices A-D]. Treatment seeking overall between 2000 and 2013 appears 

to have been slightly lower for symptoms of diarrhea, especially before 2005, compared with 

treatment seeking for fever and symptoms of ARI. 
12 

Figure 2. Trends in treatment seeking for diarrhea (A), fever (B), and symptoms of ARI (C) in East 

Africa, 2000-2013 

Figure 3. Trends in treatment seeking for diarrhea (A), fever (B), and symptoms of ARI (C) in West 

Africa, 2000-2013 

Treatment seeking across countries in South-eastern Asia between 2000 and 2013 appeared 

slightly higher (compared with Eastern and Western Africa), ranging from 22% to 72% for 

symptoms of diarrhea, 31% to 80% for fevers, and 37% to 90% for symptoms of ARI [Figure 4, 

A B C 

A B C 
13 

Appendices A-D]. There was a significant increase over this period in treatment seeking for 

diarrhea, and a marginally significant increase for fever and symptoms of ARI. Similar to Western 

Africa, treatment seeking overall between 2000 and 2013 appears to have been slightly lower in 

South-eastern Asia for diarrhea, compared with treatment seeking for fever and symptoms of ARI. 

Figure 4. Trends in treatment seeking for diarrhea (A), fever (B), and symptoms of ARI (C) in 

South-eastern Asia, 2000-2013 

Treatment seeking across countries in South America between 2000 and 2013 appeared to 

be higher than in the African regions and South-eastern Asia, ranging from 29% to 59% for 

diarrhea, 43% to 79% for fevers, and 48% to 83% for symptoms of ARI [Figure 5, Appendices AD]. Overall, treatment seeking in South America between 2000 and 2013 appears to have been 

slightly lower for diarrhea than for fever and symptoms of ARI. 

3.2 Meta-analysis of Predictors of Treatment Seeking for Diarrhea, Fever, and 

Symptoms of ARI by Subregions 

Appendix C presents results of subregional and global meta-analyses of predictors of 

treatment seeking for diarrhea, fever, and symptoms of ARI. Similar patterns emerged across 

subregions according to individual and household factors associated with treatment seeking. The 

patterns were similar across types of illness symptoms. 

A B C 
14 

Figure 5. Trends in treatment seeking for diarrhea (A), fever (B), and symptoms of ARI (C) in South 

America, 2000-2013 

3.2.1 Child’s age 

Diarrhea. Child’s age was a strong predictor of treatment seeking for diarrhea overall, 

with younger children more likely to have been brought for care than older children [Adjusted odds 

ratio AOR] (AOR=1.26, 95%, CI 1.22-1.31). This effect was noted across all regions with the 

exception of Southern Africa and Southern Europe (one survey - Albania), with the strongest effect 

in Northern Africa (AOR=1.59, 95% CI 1.40-1.80). 

Fever. Across all subregions, child’s age was a strong predictor of treatment seeking for 

fever as well, with younger children (<24 months) more likely to have been brought for care than 

older children (24-59 months) (AOR=1.28, 95% CI 1.25-1.32). The strongest effect of child’s age 

was seen in Southern Africa (AOR=1.55, 95% CI 1.29-1.88) and South America (AOR=1.44, 95% 

CI 1.35-1.54). 

Symptoms of ARI. Across all subregions, child’s age was a strong predictor of treatment 

seeking for symptoms of ARI, irrespective of fever, with younger children (<24 months) more 

likely to have been brought for care than older children (24-59 months) (AOR=1.34, 95% CI 1.29-

1.38). In the Caribbean, younger children (<24 months) were 1.3 times more likely to have been 

brought for care than older children (24-59 months) (AOR=1.32, 95% CI 1.20-1.44). Child’s age 

A B C 
15 

was also a significant predictor in Central Africa (AOR=1.22, 95% CI 1.12-1.33), Eastern Africa 

(AOR=1.36, 95% CI 1.26-1.47), Northern Africa (AOR=1.48, 95% CI 1.28-1.70), Southern Africa 

(AOR=1.47, 95% CI 1.26-1.72), and Western Africa (AOR=1.27, 95% CI 1.16-1.39). Younger 

age of child was a strong predictor in South America (AOR=1.59, 95% CI 1.49-1.70), in Central 

America (AOR=1.39, 95% CI 1.23-1.57), and a more moderate predictor in South-eastern Asia 

(AOR=1.17, 95% CI 1.01-1.36). 

3.2.2 Sex of child 

Diarrhea. Male children were more likely than female children to have been taken for care 

for diarrhea (AOR=1.07, 95% CI 1.04-1.09), but this effect was only significant in Northern Africa 

(AOR=1.26, 95% CI 1.12-1.41), Western Africa (AOR=1.13, 95% CI 1.07-1.19), and Southern 

Asia (AOR=1.14, 95% CI 1.01-1.27). 

Fever. Across all subregions, male children were slightly more likely than female children 

to have been taken for care for fever (AOR=1.05, 95% CI 1.03-1.07). Male children were 

significantly more likely to have been taken for care for fever in Central Africa (AOR=1.07, 95% 

CI 1.03-1.11), Northern Africa (AOR=1.17, 95% CI 1.04-1.31), Western Africa (AOR=1.07, 95% 

CI 1.03-1.10), South-eastern Asia (AOR=1.08, 95% CI 1.03-1.14), and Southern Asia (AOR=1.19, 

95% CI 1.11-1.28), but not in other regions. 

Symptoms of ARI. Across all subregions, male children were slightly more likely than 

female children to be taken for care for symptoms of ARI (AOR=1.06, 95% CI 1.03-1.09), but 

there was substantial variation by region. Child’s sex was not a significant predictor of treatment 

seeking for symptoms of ARI in most sub-regions, but males were more likely to have been taken 

for care in Northern Africa (AOR=1.42, 95% CI 1.22-1.66), South-eastern Asia (AOR=1.11, 95% 

CI 1.01-1.22), Southern Asia (AOR=1.19, 95% CI 1.08-1.31), and Western Asia (AOR=1.21, 95% 

CI 1.05-1.40), and slightly more likely to have been taken for care in Western Africa (AOR=1.07, 

95% CI 1.00-1.15). 

3.2.3 Mother’s age 

Diarrhea. Younger mothers (under age 30) were slightly more likely than older mothers 

(age 30 and older) to take their child for treatment of diarrhea (AOR=1.03, 95% CI 1.00-1.07) 

across most subregions. This effect was significant in the Caribbean (AOR=1.16, 95% CI 1.03-
16 

1.30), Eastern Africa (AOR=1.09, 95% CI 1.02-1.16), Southern Asia (AOR=1.11, 95% CI 1.01-

1.22), and marginally significant in South-eastern Asia (AOR=1.11, 95% CI 1.00-1.23). 

Fever. Younger mothers (<30 years) were slightly more likely than older mothers (30+ 

years) to take their child for treatment for fever (AOR=1.07, 95% CI 1.04-1.10). The strongest 

effects were seen in Eastern Africa (OR=1.14, 95% CI 1.08-1.21), Southern Asia (AOR=1.19, 

95% CI 1.11-1.28), and South-eastern Asia (AOR=1.07, 95% CI 1.01-1.14), but were not 

statistically significant in other regions. 

Symptoms of ARI. Across all subregions, younger mothers (<30 years) were slightly more 

likely than older mothers (30+ years) to take their child for treatment for symptoms of ARI 

(AOR=1.04, 95% CI 1.01-1.08), but there were substantial differences by region. Younger women 

were more likely to take their child for treatment in the Caribbean (AOR=1.15, 95% CI 1.04-1.26) 

and Southern Asia (AOR=1.21, 95% CI 1.10-1.33), but slightly less likely to take their child for 

treatment in Central Africa (AOR=0.88, 95% CI 0.78-1.00). Mother’s age had no effect in other 

regions. 

3.2.3 Mother’s education 

Mother’s level of education is positively associated with increased odds of treatment 

seeking for symptoms of childhood illness. 

Diarrhea. Across all subregions, mothers with no education or only primary education 

were significantly less likely than mothers with secondary or higher education to seek treatment 

for diarrhea (AOR=0.77, 95% CI 0.73-0.81). This effect was significant across all subregions that 

had at least two surveys, with the exception of Northern Africa (AOR=1.03, 95% CI 0.90-1.18) 

and Western Asia (AOR=1.25, 95% CI 0.83-1.88). 

Fever. Across all subregions, mothers with no education or only primary education were 

significantly less likely than mothers with secondary or higher education to seek treatment for 

fever (AOR=0.75, 95% CI 0.72-0.77). Mother’s level of education was associated with increased 

odds of treatment seeking when their child had fever in all subregions except Northern Africa, 

Southern Africa, and Western Asia. 

Symptoms of ARI. Across all subregions, mothers with no education or only primary 

education were significantly less likely than mothers with secondary or higher education to seek 
17 

treatment for symptoms of ARI (AOR=0.72, 95% CI 0.68-0.75). Mother’s education was a 

significant predictor in all regions that had at least two surveys, with the exception of Northern 

Africa (OR=0.80, 95% CI 0.60-1.06) and Southern Africa (AOR=0.87, 95% CI 0.66-1.14). 

3.2.4 Household wealth quintile 

Diarrhea. Across all subregions, higher household wealth quintile was a strong predictor 

of treatment seeking for diarrhea, with children in the poorest households (lowest quintile and 

second quintile) significantly less likely to have been taken for treatment (AOR=0.78, 95% CI 

0.74-0.83). This association was significant in all subregions except the Caribbean (only 3 data 

points), Central America (only 2 data points), and Southern Africa. 

Fever. Across all subregions, household wealth quintile was a strong predictor of treatment 

seeking for fever, with children in the poorest households (lowest quintile and second quintile) 

significantly less likely to have been taken for treatment than those in wealthier households 

(middle quintile, fourth quintile, and highest quintile) (AOR=0.73, 95% CI 0.70-0.76). This 

association was in a positive direction and significant in all subregions except the Caribbean (3 

data points), Central America (2 data points), Central Asia (2 data points), Northern Africa (3 data 

points), South America, Southern Africa, and Western Asia. 

Symptoms of ARI. Across all subregions, children in the poorest households (lowest 

quintile and second quintile) were less likely than children in wealthier households (middle 

quintile, fourth quintile, and highest quintile) to be taken for treatment for symptoms of ARI 

(AOR=0.73, 95% CI 0.69-0.77). Children in the poorest households were significantly less likely 

to be taken for treatment in all subregions that had at least four surveys, except South America 

(AOR=0.94, 95% CI 0.83-1.06), with the largest effect in South-eastern Asia (AOR=0.61, 95% CI 

0.53-0.71). 

3.2.5 Urban-rural residence 

Diarrhea. Across all subregions, children living in urban areas were slightly more likely 

to be taken for treatment of diarrhea than children in rural areas (AOR=1.08, 95% CI 1.01-1.15). 

Children in urban areas were significantly more likely to be taken for treatment in Western Africa 

(AOR=1.25, 95% CI 1.06-1.46) and Southern Asia (AOR=1.30, 95% CI 1.05-1.60). However, 
18 

children in urban areas in Western Asia were less likely to be taken for treatment of diarrhea 

(AOR=0.79, 95% CI 0.68-0.92). 

Fever. Across all subregions, children in urban areas were more likely to be taken for 

treatment of fever than children in rural areas (AOR=1.28, 95% CI 1.21-1.35), with the largest 

effect in Southern Asia (AOR=1.47, 95% CI 1.23-1.74), Central America (AOR=1.50, 95% CI 

1.09-2.06), and Eastern Africa (AOR=1.44, 95% CI 1.27-1.62). 

Symptoms of ARI. Across all subregions, children in urban areas were significantly more 

likely to be taken for treatment of symptoms of ARI than children in rural areas (AOR=1.27, 95% 

CI 1.19-1.36), with the largest effect in Southern Asia (OR=1.44, 95% CI 1.21-1.73), Northern 

Africa (AOR=1.52, 95% CI 1.07-2.17), and Eastern Africa (AOR=1.40, 95% CI 1.20-1.62). There 

was no difference by urban-rural residence in Western Asia (AOR=1.03, 95% CI 0.68-1.54), 

Southern Africa (AOR=1.17, 95% CI 0.85-1.59), and South America (AOR=0.96, 95% CI 0.78-

1.18). 

3.3 Effect of Distance from the Nearest Health Facility on Treatment Seeking for 

Childhood Illnesses in Malawi and Zambia 

Results from the random effects logistic regressions carried out on pooled Malawi and 

Zambia datasets (section 2.5 above) showed that distance from a health facility is a strong 

determinant of treatment seeking for diarrhea, fever, and symptoms of ARI (Table 1). For all three 

illnesses, the farther a household is from a health facility, the less likely the family is to seek 

treatment for childhood illnesses. Other factors associated with treatment seeking were similar to 

those observed in the meta-analyses already presented. Younger children, children of younger 

mothers, and children living in wealthier households were more likely to be taken for treatment 

when sick. 
19 

Table 1. Random effect logistic regression results for factors associated with treatment seeking for childhood illnesses in Malawi and 

Zambia 

 Fever 

(n = 8,953 with fever) 

Diarrhea 

(n = 10,868 with diarrhea) 

Symptoms of ARI 

(n = 5,142 with cough in chest)

Characteristic AOR 95% CI P-value AOR 95% CI P-value AOR 95% CI P-valueSex Male 1.017 (0.925-1.118) 0.7275 1.062 (0.947-1.191) 0.3026 1.077 (0.946-1.227) 0.2624 

Female - - - 

Child’s age (in years) 

0 (infant) 1.242 (1.055-1.462) 0.0093 1.128 (0.881-1.444) 0.3406 1.010 (0.812-1.257) 0.9281 

1 1.326 (1.134-1.550) 0.0004 1.424 (1.121-1.810) 0.0039 1.232 (0.991-1.532) 0.060 

2 1.198 (1.022-1.403) 0.0259 1.143 (0.885-1.477) 0.3067 1.066 (0.849-1.340) 0.5802 

3 1.006 (0.854-1.186) 0.9399 1.153 (0.868-1.530) 0.3261 0.956 (0.753-1.213) 0.7109 

4 - - - 

Mother’s age (in years) 

20-29 0.843 (0.686-1.037) 0.1055 0.952 (0.773-1.173) 0.6448 0.929 (0.717-1.203) 0.5767 30-39 0.778 (0.626-0.967) 0.0235 0.917 (0.730-1.152) 0.4568 0.996 (0.755-1.315) 0.9796 40-49 0.713 (0.547-0.929) 0.0123 0.901 (0.662-1.227) 0.5088 0.899 (0.627-1.288) 0.5606 Under 20 - - - 

Mother’s education None 0.751 (0.385-1.465) 0.401 1.152 (0.533-2.490) 0.7183 0.850 (0.202-3.569) 0.8239 

Primary 0.870 (0.452-1.678) 0.6786 1.436 (0.673-3.063) 0.3489 0.823 (0.198-3.424) 0.7892 

Secondary 1.121 (0.580-2.166) 0.7338 1.788 (0.836-3.822) 0.134 1.130 (0.271-4.714) 0.8665 

More than secondary - - - 

Residence Urban 0.983 (0.817-1.181) 0.8519 0.891 (0.694-1.144) 0.3669 0.818 (0.601-1.114) 0.202 

Rural - - - 

Wealth quintile 

Lowest 0.687 (0.561-0.842) 0.0003 1.235 (0.970-1.573) 0.0867 0.749 (0.565-0.994) 0.0456 

Second 0.758 (0.618-0.930) 0.0079 1.300 (1.022-1.654) 0.0324 0.809 (0.613-1.069) 0.1365 

Middle 0.813 (0.665-0.993) 0.0424 1.161 (0.918-1.468) 0.212 0.887 (0.677-1.162) 0.3833 

Fourth 0.778 (0.639-0.948) 0.0129 1.189 (0.946-1.496) 0.1382 0.959 (0.733-1.255) 0.7604 

Highest - - - 

Distance from nearest facility 

Within 1.9 km 1.612 (1.350-1.926) <.0001 1.399 (1.126-1.737) 0.0024 1.684 (1.306-2.173) <.0001 1.9 - 3.5 km 1.487 (1.256-1.760) <.0001 1.159 (0.959-1.401) 0.1276 1.262 (1.010-1.578) 0.0405 3.6 - 5.7 km 1.302 (1.107-1.531) 0.0014 1.132 (0.939-1.364) 0.1926 1.248 (1.006-1.549) 0.0439 Farther than 5.7 km - - - 

Note: Random effects logistic model also controlled for type of facility visited and dataset. Fever analysis included data from Malawi 2010 DHS, Malawi 2012 DHS, 

Zambia 2007 DHS, and Zambia 2010 MIS (the 2004 Malawi DHS only asked about treatment for cough and not fever). Diarrhea and cough analysis included data 

from Malawi 2004 DHS, Malawi 2010 DHS, and Zambia 2007 DHS (MIS did not collect information on diarrhea and cough).

19 
20 
21 

4. DISCUSSION 

This study used 248 datasets from nationally-representative household surveys (2000-

2013) to assess individual-level trends and sociodemographic determinants of treatment seeking 

for three childhood illnesses: diarrhea, fever, and symptoms of ARI. The number of datasets used 

for each illness varied because of availability of data—diarrhea (118), fever (200), and symptoms 

of ARI (223). Survey datasets were from the Demographic and Health Surveys (DHS), Malaria 

Indicator Surveys (MIS), and Multiple Indicator Cluster Surveys (MICS). Child-level information 

on treatment seeking was available for a total of 685,049 children under age 5 with diarrhea 

(151,607), fever (358,821), and symptoms of ARI (174,621). 

Levels of treatment seeking for symptoms of childhood illnesses varied across countries 

and subregions, by illness symptoms, and among surveys carried out between 2000 and 2013. 

However, nearly all subregions saw an upward trend in treatment seeking for childhood illnesses; 

none saw a significant decrease. The majority of subregions showed a significant or marginally 

significant increase in treatment seeking for fever, including countries of Central America, Southeastern Asia, Central Asia, Western Asia (marginal), Eastern Africa (marginal), Northern Africa, 

Southern Africa (marginal), and Western Africa. For diarrhea, significant increases in care seeking 

were seen in Central America, Eastern Africa, South-eastern Asia, Western Asia, and Western 

Africa. Gains across the subregions were weakest in treatment seeking for symptoms of ARI, with 

none showing statistically significant increases. Central America, South-eastern Asia, and Western 

Asia showed marginally significant increases. 

The lack of statistically significant increases in treatment seeking for symptoms of ARI 

and diarrhea, compared with fever, can be largely attributed to the lower prevalence, and therefore 

smaller sample sizes, of symptoms of ARI and diarrhea. Additionally, the overall levels of 

treatment seeking for symptoms of ARI were relatively high to begin with in many subregions, 

with all but Western Africa averaging well above 50% between 2000 and 2013. It is also important 

to note that while we attempted to measure treatment seeking for illness symptoms that presumably 

require medical attention, many illnesses reported by mothers and caregivers in the surveys were 

likely not severe and could have been adequately managed at home; this would include very low 

fever that lasts a day or two, and mild bouts of diarrhea or cough [15, 16]. While we attempted to 

mitigate this problem for symptoms of ARI by limiting the sample to children with cough 
22 

accompanied by rapid breathing or shortness of breath (plus cough occurring in the chest in the 

MICS), fever was only a “yes” or “no” question in the surveys, with no additional qualification of 

severity. For diarrhea, we did not find the addition of blood in the stool to be reliably associated 

with treatment seeking. 

The results of the analysis that explored the child, mother, and household-level factors 

associated with treatment seeking for childhood illness were overall in the expected directions and 

in line with previous research [9, 17, 19-23]. Mothers with higher levels of education, mothers 

living in urban areas, mothers in wealthier households, and mothers living closer to a health facility 

were more likely to take their child for treatment of illness. This pattern was seen for treatment 

seeking regarding diarrhea, fever, and symptoms of ARI. 

The analysis of pooled data from Zambia and Malawi, which made use of geo-coordinates, 

demonstrated that access to health services, as measured by distance from the nearest health 

facility, is a strong and consistent barrier to treatment seeking. For all three illnesses, children in 

households less than 2 km from a health facility were 1.4 to 1.7 times more likely to be taken for 

treatment than their counterparts in households at least 6 km from a health facility, showing a 

pattern of decreasing odds of treatment seeking with increasing distance from a health facility. 

These findings are consistent with previous research in this area [19-23]. Distance from a facility 

likely acts as a barrier to treatment seeking in several ways: (1) increased cost of travel to and from 

the facility, (2) increased time required for seeking treatment, and (3) decreased motivation to take 

a sick child on a lengthy trip to receive treatment. Similarly, across all datasets, children in rural 

households, which are typically farther from health facilities than urban households, were 

consistently less likely to be taken for treatment for their illnesses compared with their urban 

counterparts [31]. 

As expected, younger children (under age 2) were more likely to be taken for treatment 

than older children (age 2-5 years), across almost all subregions. This may be due to younger 

children having more severe symptoms, although we were unable to test this with these data. This 

finding is consistent with previous research in several low-income settings [31-34]. 

Mother’s age was less consistently related to treatment seeking for childhood illness across 

subregions, although the association was similar for diarrhea, fever and symptoms of ARI. When 

the association between mother’s age and treatment seeking was significant, results showed that 
23 

younger mothers were more likely than older mothers to take their child for treatment of symptoms 

of illness. Several factors may account for this pattern; for example, the child of younger mothers 

is more likely to be the woman’s first child, and she would therefore be more likely to seek 

treatment; also older mothers may perceive themselves more adept at discerning whether an illness 

is severe enough to warrant seeking medical attention [35,36]. 

Previous research [17, 37, 38] has shown that women living in poorer households are less 

likely to seek treatment for their sick child than women living in more affluent households. Across 

the subregions, women in the two lowest (poorest) quintiles of the household wealth index were 

consistently less likely to seek treatment for their child with diarrhea, fever, and symptoms of ARI. 

This is likely due to a number of factors including (1) lack of money to pay user fees or medicine 

costs, (2) transportation costs to and from the health facility, and (3) time lost from work or farming 

to take the child for treatment [19-23, 39]. 

Mothers with no education or only primary education were consistently less likely to take 

their child for treatment when sick, compared with mothers with secondary education or higher, 

for all three illnesses. This pattern has been shown consistently in previous research in low-income 

settings [18, 35, 40, 41]. It is suggested that women with little or no education (1) are less likely 

to recognize severe symptoms in their sick child, (2) are more likely to seek treatment from a 

traditional healer, and (3) are less likely to have the financial and other resources to take the sick 

child for treatment at a health facility. 

In the majority of subregions, sex of the child was not associated with whether or not the 

child was taken for treatment to a health facility, irrespective of the illness symptoms. However, 

boys were slightly more likely to be taken for treatment for their illness in several subregions, 

including Western Africa, Southern Asia, and South-eastern Asia (AORs ranged between 1.01 and 

1.1). The disparity of boys being more likely to be taken for treatment was more pronounced in 

Northern Africa, with boys being 26% more likely to be taken for treatment of diarrhea, 17% more 

likely to be taken for treatment of fever, and 42% more likely to be taken for treatment of 

symptoms of ARI. While we found no published research studies specific to Northern Africa, 

differential access to treatment for male and female children is supported by previous research 

[34, 42]. 
24 

There are some important limitations to consider when interpreting the results of this 

analysis. First, a number of unmeasured and unobserved factors were not included in the risk factor 

meta-analyses. Perhaps the most important of these were (1) perceived quality of health care 

available to mothers/caregivers and (2) actual quality of health care services available at the health 

facilities. Both have been shown to be strong predictors of whether treatment is sought and where 

it is sought, across many low-income settings [13, 14, 24, 35, 43, 44]. Other important factors that 

were not measured included perception of severity and duration of illnesses, perceived selfefficacy of mothers/caregivers, social capitol in the community, and local cultural beliefs about 

the causes of childhood illnesses and appropriate remedies. All of these factors have been shown 

to hinder treatment seeking for childhood illnesses across many low-income settings [11, 43, 45]. 

Second, there are always random and systematic errors with respect to recall of illness symptoms 

and treatment sought [46, 47]. Third, in some subregions the number of datasets available for 

analysis was small, yielding estimates with a broad range of uncertainty regarding trends in 

treatment seeking. This situation limited the statistical power available to identify statistically 

significant trends over time. Fourth, in the analysis of the effect of distance from the nearest health 

facility on treatment seeking in Malawi and Zambia, the geocoded lists of health facilities were 

from 2010. There is, therefore, the potential for misclassification in earlier survey years because 

the lists may not accurately reflect the health facilities present in the two countries before 2010. 
25 

5. CONCLUSIONS 

Several important conclusions resulted from these analyses. First, between 2000 and 2013, 

there was substantial variation across countries and subregions regarding progress in treatment 

seeking and access to health care for childhood illnesses. Second, many barriers to treatment 

seeking hinder children from accessing health care services for treatment of the three most 

important (and potentially deadly) childhood illnesses: diarrhea, fever, and ARI. These barriers 

include mother’s lack of education, low household income, and distance from the nearest health 

facility. Third, health systems need to improve access to high quality and appropriate health 

services for treatment of childhood illnesses. Lastly, the results of this study suggest that efforts to 

improve access to care, such as the ongoing scale-up of community case management, should 

focus on poor and less educated households in rural areas in order to have the largest programmatic 

impact. 
26 

 
27 

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44. Hadad, S., E. Franca, and E. Uchoa, Preventable infant mortality and quality of health 

care: maternal perception of the child's illness and treatment. Cad Saude Publica, 2002. 

18(6): p. 1519-27. 

45. Kauchali, S., et al., Local beliefs about childhood diarrhoea: importance for healthcare 

and research. J Trop Pediatr, 2004. 50(2): p. 82-9. 

46. Eisele, T.P., et al., Measuring Coverage of MNCH: Total survey error and the 

interpretation of intervention coverage estimates from household surveys. PLoS Med, 

2013. 10(5): p. e1001386. 

47. Eisele, T.P., et al., Measuring coverage of MNCH: Accuracy of measuring diagnosis and 

treatment of childhood malaria from household surveys in Zambia. PLoS Med, 2013. 

10(5): p. e1001417. 
30 
31

APPENDICES 

Appendix A: Prevalence of treatment seeking for diarrhea, fever, and symptoms of acute 

respiratory infection (ARI) 

Appendix B: Loess regression and linear regression results for trends in treatment seeking for 

diarrhea, by subregions 

Appendix C: Loess regression and linear regression results for trends in treatment seeking for 

fever, by subregions 

Appendix D: Loess regression and linear regression results for trends in treatment seeking for 

symptoms of acute respiratory infections (ARI), by subregions 

Appendix E: Results of subregional and global meta-analyses of predictors of treatment seeking 

for diarrhea, by subregions 

Appendix F: Results of subregional and global meta-analyses of predictors of treatment seeking 

for fever, by subregions 

Appendix G: Results of subregional and global meta-analyses of predictors of treatment seeking 

for symptoms of acute respiratory infections (ARI), by subregions 

Appendix A: Point estimates of treatment seeking for diarrhea, fever and symptoms of acute respiratory infection (ARI), 2000-2013 

Treatment seeking for 

diarrhea 

Treatment seeking for 

fever 

Treatment seeking for 

symptoms of ARI 

UN Region Country Year Survey n Proportion 95% CI n Proportion 95% CI n Proportion 95% CI Eastern Africa Burundi 2000 MICS 548 0.49 0.45 0.52 417 0.48 0.43 0.53 Eastern Africa Burundi 2005 MICS 1,922 0.49 0.46 0.52 1,080 0.44 0.40 0.47 Eastern Africa Burundi 2010 DHS 1,787 0.57 0.55 0.60 2,077 0.63 0.60 0.65 2,087 0.52 0.49 0.55 Eastern Africa Burundi 2012 MIS 1,689 0.54 0.51 0.57 Eastern Africa Comoros 2004 DHS 1,108 0.21 0.18 0.25 1,780 0.41 0.38 0.45 762 0.41 0.35 0.46 Eastern Africa Comoros 2011 DHS 2,060 0.23 0.20 0.26 2,621 0.28 0.25 0.31 1,657 0.24 0.21 0.27 Eastern Africa Djibouti 2006 MICS 112 0.66 0.56 0.76 91 0.76 0.65 0.87 Eastern Africa Ethiopia 2000 DHS 1,612 0.32 0.28 0.36 2,049 0.25 0.22 0.28 1,237 0.25 0.21 0.29 Eastern Africa Ethiopia 2005 DHS 2,154 0.13 0.11 0.15 2,872 0.18 0.15 0.21 2,199 0.16 0.13 0.19 Eastern Africa Ethiopia 2011 DHS 1,612 0.32 0.28 0.36 2,049 0.25 0.22 0.28 1,237 0.25 0.21 0.29 Eastern Africa Kenya 2000 MICS 1,135 0.56 0.52 0.61 545 0.67 0.61 0.73 Eastern Africa Kenya 2003 DHS 865 0.30 0.26 0.34 2,213 0.46 0.43 0.50 1,008 0.49 0.45 0.53 Eastern Africa Kenya 2008 DHS 946 0.49 0.43 0.54 1,354 0.50 0.46 0.54 710 0.52 0.46 0.58 Eastern Africa Comoros 2000 MICS 1,407 0.54 0.51 0.56 448 0.65 0.61 0.69 Eastern Africa Madagascar 2000 MICS 1,021 0.42 0.37 0.46 374 0.64 0.58 0.71 Eastern Africa Madagascar 2003 DHS 467 0.31 0.23 0.38 1,030 0.39 0.33 0.45 443 0.48 0.40 0.55 Eastern Africa Madagascar 2008 DHS 1,003 0.35 0.31 0.38 1,074 0.43 0.39 0.47 604 0.43 0.37 0.48 Eastern Africa Madagascar 2011 MIS 959 0.31 0.27 0.36 Eastern Africa Madagascar 2013 MIS 693 0.35 0.28 0.42 Eastern Africa Malawi 2000 DHS 1,755 0.28 0.26 0.31 4,245 0.26 0.24 0.28 2,672 0.27 0.24 0.29 Eastern Africa Malawi 2004 DHS 2,187 0.32 0.29 0.35 3,702 0.41 0.39 0.44 1,865 0.37 0.34 0.40 Eastern Africa Malawi 2006 MICS 8,053 0.43 0.41 0.45 1,716 0.64 0.60 0.67 Eastern Africa Malawi 2010 DHS 3,098 0.62 0.60 0.65 6,178 0.66 0.64 0.67 2,764 0.66 0.64 0.69 Eastern Africa Malawi 2010 MIS 895 0.65 0.60 0.69 Eastern Africa Malawi 2012 MIS 676 0.49 0.44 0.54 Eastern Africa Mozambique 2003 DHS 1,199 0.49 0.44 0.54 2,272 0.53 0.49 0.56 925 0.55 0.51 0.60 

(Continued...) 

33 
Appendix A − Continued

Treatment seeking for 

diarrhea 

Treatment seeking for 

fever 

Treatment seeking for 

symptoms of ARI 

UN Region Country Year Survey n Proportion 95% CI n Proportion 95% CI n Proportion 95% CI Eastern Africa Mozambique 2008 MICS 534 0.76 0.71 0.81 Eastern Africa Mozambique 2011 DHS 1,071 0.56 0.51 0.61 1,313 0.56 0.51 0.60 495 0.54 0.47 0.60 Eastern Africa Rwanda 2000 MICS 1,012 0.22 0.19 0.25 352 0.48 0.43 0.54 Eastern Africa Rwanda 2005 DHS 2,229 0.14 0.12 0.16 3,181 0.22 0.21 0.24 2,757 0.21 0.20 0.23 Eastern Africa Rwanda 2007 DHS 687 0.33 0.28 0.37 1,037 0.36 0.32 0.40 873 0.29 0.25 0.33 Eastern Africa Rwanda 2010 DHS 1,107 0.37 0.34 0.41 1,311 0.43 0.40 0.47 835 0.39 0.35 0.43 Eastern Africa Rwanda 2013 MIS 876 0.55 0.51 0.59 Eastern Africa Somalia 2011 MICS 1,288 0.18 0.15 0.21 834 0.32 0.27 0.38 Eastern Africa Tanzania 2004 DHS 1,011 0.53 0.48 0.57 1,585 0.65 0.61 0.69 528 0.63 0.57 0.69 Eastern Africa Tanzania 2010 DHS 1,672 0.57 0.53 0.61 Eastern Africa Uganda 2000 DHS 1,176 0.45 0.41 0.49 2,617 0.67 0.64 0.70 1,343 0.67 0.63 0.71 Eastern Africa Uganda 2006 DHS 1,956 0.70 0.67 0.73 3,091 0.75 0.72 0.77 1,728 0.74 0.70 0.77 Eastern Africa Uganda 2009 MIS 1,684 0.72 0.69 0.75 2,855 0.80 0.78 0.82 1,641 0.75 0.72 0.78 Eastern Africa Uganda 2011 DHS 1,684 0.72 0.69 0.75 2,855 0.80 0.78 0.82 1,641 0.75 0.72 0.78 Eastern Africa Zambia 2000 MICS 868 0.58 0.48 0.67 Eastern Africa Zambia 2001 DHS 1,225 0.43 0.39 0.46 2,603 0.65 0.62 0.68 861 0.69 0.66 0.73 Eastern Africa Zambia 2006 MIS 464 1.00 1.00 1.00 Eastern Africa Zambia 2007 DHS 902 0.59 0.55 0.64 1,025 0.64 0.60 0.68 523 0.65 0.59 0.70 Eastern Africa Zambia 2008 MIS 871 1.00 1.00 1.00 Eastern Africa Zambia 2010 MIS 1,108 0.66 0.61 0.70 Eastern Africa Zambia 2012 MIS 733 0.62 0.56 0.67 Eastern Africa Zimbabwe 2005 DHS 613 0.32 0.27 0.37 375 0.28 0.22 0.33 530 0.28 0.23 0.34 Eastern Africa Zimbabwe 2006 DHS 674 0.36 0.31 0.40 515 0.37 0.32 0.41 531 0.44 0.39 0.49 Eastern Africa Zimbabwe 2009 MICS 530 0.43 0.37 0.48 491 0.52 0.47 0.57 Central Africa Angola 2000 MICS 1,422 0.62 0.59 0.66 408 0.64 0.58 0.70 Central Africa Angola 2006 MIS 265 0.52 0.44 0.59 

(Continued...) 

34 
Appendix A − Continued

Treatment seeking for 

diarrhea 

Treatment seeking for 

fever 

Treatment seeking for 

symptoms of ARI 

UN Region Country Year Survey n Proportion 95% CI n Proportion 95% CI n Proportion 95% CI Central Africa Angola 2011 MIS 2,645 0.56 0.52 0.59 Central Africa DRC 2000 MICS 4,143 0.35 0.32 0.38 979 0.58 0.52 0.63 Central Africa DRC 2007 DHS 1,287 0.33 0.27 0.38 2,556 0.45 0.41 0.49 1,224 0.42 0.38 0.46 Central Africa DRC 2010 MICS 2,992 0.58 0.54 0.62 678 0.65 0.60 0.71 Central Africa CAR 2000 MICS 4,702 0.30 0.28 0.33 1,547 0.44 0.40 0.47 Central Africa CAR 2006 MICS 2,019 0.33 0.30 0.37 671 0.41 0.36 0.47 Central Africa CAR 2010 MICS 3,337 0.38 0.35 0.41 771 0.37 0.32 0.42 Central Africa Congo 2005 DHS 627 0.25 0.21 0.29 1,002 0.46 0.40 0.51 322 0.47 0.40 0.55 Central Africa Congo 2011 DHS 1,529 0.37 0.32 0.41 2,278 0.47 0.42 0.51 807 0.50 0.44 0.56 Central Africa Cameroon 2000 MICS 830 0.34 0.30 0.38 204 0.56 0.49 0.63 Central Africa Cameroon 2006 MICS 1,154 0.37 0.33 0.41 441 0.55 0.48 0.61 Central Africa Eq Guinea 2000 MICS 741 0.48 0.43 0.53 247 0.70 0.62 0.77 Central Africa Gabon 2000 DHS 592 0.33 0.28 0.38 509 0.61 0.55 0.66 Central Africa Gabon 2012 DHS 978 0.36 0.31 0.41 1,300 0.47 0.41 0.54 830 0.47 0.41 0.54 Central Africa Sao Tom/Pri 2000 MICS 633 0.73 0.68 0.77 71 0.79 0.69 0.89 Central Africa Sao Tom/Pri 2008 DHS 227 0.52 0.43 0.62 246 0.72 0.63 0.81 203 0.69 0.61 0.77 Central Africa Chad 2000 MICS 1,560 0.24 0.21 0.26 656 0.36 0.32 0.40 Central Africa Chad 2004 DHS 1,186 0.17 0.13 0.20 1,535 0.22 0.18 0.26 Central Africa Chad 2010 MICS 4,219 0.38 0.35 0.41 1,442 0.44 0.39 0.48 Northern Africa Egypt 2000 DHS 1,059 0.66 0.62 0.70 Northern Africa Egypt 2003 DHS 1,334 0.46 0.42 0.49 689 0.70 0.66 0.75 Northern Africa Egypt 2005 DHS 2,471 0.48 0.45 0.51 2,749 0.61 0.59 0.64 1,407 0.67 0.63 0.70 Northern Africa Egypt 2008 DHS 979 0.56 0.52 0.60 1,466 0.65 0.62 0.68 1,067 0.70 0.67 0.74 Northern Africa Morocco 2003 DHS 723 0.22 0.19 0.26 1,549 0.34 0.31 0.38 693 0.38 0.33 0.42 Northern Africa Sudan 2000 MICS 5,290 0.42 0.38 0.45 1,112 0.64 0.60 0.68 Northern Africa Tunisia 2011 MICS 492 0.78 0.73 0.83 

 (Continued...) 

35 
Appendix A − Continued

Treatment seeking for 

diarrhea 

Treatment seeking for 

fever 

Treatment seeking for 

symptoms of ARI 

UN Region Country Year Survey n Proportion 95% CI n Proportion 95% CI n Proportion 95% CI Southern Africa Lesotho 2000 MICS 252 0.59 0.53 0.65 Southern Africa Lesotho 2004 DHS 470 0.29 0.24 0.34 885 0.57 0.53 0.61 663 0.60 0.55 0.64 Southern Africa Lesotho 2009 DHS 417 0.53 0.48 0.59 642 0.60 0.55 0.65 458 0.60 0.55 0.66 Southern Africa Namibia 2000 DHS 477 0.51 0.44 0.57 755 0.58 0.53 0.63 606 0.55 0.49 0.61 Southern Africa Namibia 2006 DHS 576 0.60 0.55 0.66 773 0.56 0.51 0.61 385 0.67 0.61 0.73 Southern Africa Namibia 2009 MIS 1,130 0.73 0.68 0.77 Southern Africa Swaziland 2000 MICS 135 0.52 0.43 0.61 335 0.70 0.65 0.75 Southern Africa Swaziland 2006 DHS 347 0.57 0.50 0.64 712 0.49 0.44 0.54 369 0.57 0.51 0.64 Southern Africa Swaziland 2010 MICS 273 0.64 0.58 0.71 342 0.65 0.59 0.70 Southern Africa Swaziland 2010 MIS 39 0.69 0.55 0.84 Western Africa Burkina Faso 2003 DHS 1,864 0.17 0.15 0.20 3,425 0.33 0.30 0.36 819 0.36 0.31 0.41 Western Africa Burkina Faso 2006 MICS 1,051 0.31 0.26 0.36 218 0.45 0.37 0.54 Western Africa Burkina Faso 2010 DHS 2,027 0.47 0.44 0.50 2,935 0.54 0.51 0.57 591 0.51 0.45 0.56 Western Africa Benin 2001 DHS 643 0.24 0.20 0.27 1,965 0.32 0.29 0.35 568 0.35 0.30 0.40 Western Africa Benin 2006 DHS 1,395 0.21 0.18 0.23 4,204 0.37 0.35 0.39 1,409 0.36 0.33 0.39 Western Africa Benin 2011 DHS 816 0.37 0.33 0.41 1,141 0.39 0.35 0.42 421 0.35 0.30 0.41 Western Africa Cote d'Ivoire 2000 MICS 2,441 0.36 0.34 0.38 265 0.67 0.61 0.73 Western Africa Cote d'Ivoire 2006 MICS 2,209 0.29 0.26 0.33 422 0.61 0.55 0.67 Western Africa Cote d’Ivoire 2011 DHS 1,273 0.27 0.24 0.31 1,624 0.35 0.31 0.38 597 0.33 0.27 0.38 Western Africa Guinea Biss 2000 MICS 2,515 0.61 0.59 0.63 566 0.71 0.67 0.75 Western Africa Guinea Biss 2006 MICS 782 0.42 0.38 0.47 249 0.62 0.54 0.69 Western Africa Ghana 2006 MICS 796 0.45 0.39 0.50 187 0.63 0.54 0.71 Western Africa Ghana 2003 DHS 580 0.26 0.21 0.31 747 0.47 0.43 0.51 347 0.44 0.38 0.51 Western Africa Ghana 2008 DHS 548 0.41 0.36 0.46 546 0.51 0.46 0.56 301 0.49 0.42 0.56 Western Africa Ghana 2011 MICS 1,802 0.63 0.59 0.67 271 0.61 0.52 0.71 Western Africa Gambia 2000 MICS 486 0.68 0.63 0.74 248 0.78 0.71 0.85 

 (Continued...) 

36 
Appendix A − Continued

Treatment seeking for 

diarrhea 

Treatment seeking for 

fever 

Treatment seeking for 

symptoms of ARI 

UN Region Country Year Survey n Proportion 95% CI n Proportion 95% CI n Proportion 95% CI Western Africa Gambia 2005 MICS 536 0.74 0.69 0.78 362 0.79 0.75 0.84 Western Africa Guinea 2005 DHS 822 0.27 0.22 0.32 1,768 0.35 0.31 0.39 414 0.43 0.37 0.50 Western Africa Guinea 2012 DHS 1,071 0.38 0.33 0.42 1,850 0.34 0.30 0.38 792 0.33 0.27 0.39 Western Africa Liberia 2007 DHS 1,055 0.50 0.44 0.56 1,589 0.60 0.55 0.64 695 0.60 0.54 0.66 Western Africa Liberia 2009 MIS 1,596 0.56 0.51 0.60 Western Africa Liberia 2011 DHS 1,617 0.56 0.51 0.60 Western Africa Mali 2001 DHS 2,183 0.12 0.10 0.14 3,254 0.41 0.38 0.43 1,187 0.45 0.40 0.50 Western Africa Mali 2006 DHS 1,450 0.18 0.15 0.21 2,094 0.33 0.30 0.36 699 0.38 0.33 0.43 Western Africa Mali 2012 DHS 844 0.28 0.25 0.32 809 0.28 0.24 0.33 324 0.28 0.22 0.34 Western Africa Mauritania 2007 MICS 1,439 0.33 0.29 0.36 49 0.44 0.29 0.60 Western Africa Nigeria 2003 DHS 911 0.22 0.16 0.28 1,559 0.33 0.29 0.37 503 0.34 0.27 0.41 Western Africa Nigeria 2007 MICS 2,218 0.41 0.38 0.44 339 0.65 0.59 0.72 Western Africa Nigeria 2008 DHS 2,620 0.43 0.40 0.45 3,849 0.56 0.53 0.58 1,166 0.50 0.46 0.54 Western Africa Nigeria 2010 MIS 1,805 0.35 0.30 0.39 Western Africa Nigeria 2011 MICS 5,172 0.58 0.55 0.60 987 0.62 0.58 0.67 Western Africa Nigeria 2013 DHS 2,950 0.29 0.26 0.32 3,516 0.33 0.31 0.36 1,122 0.33 0.28 0.37 Western Africa Niger 2000 MICS 1,899 0.19 0.16 0.23 563 0.46 0.40 0.52 Western Africa Niger 2006 DHS 1,669 0.17 0.14 0.20 2,170 0.45 0.41 0.49 1,166 0.47 0.41 0.53 Western Africa Niger 2012 DHS 1,588 0.51 0.48 0.54 1,545 0.52 0.48 0.56 823 0.49 0.44 0.55 Western Africa Sierra Leone 2000 MICS 1,224 0.52 0.49 0.55 211 0.54 0.46 0.61 Western Africa Sierra Leone 2005 MICS 1,828 0.49 0.46 0.52 566 0.54 0.50 0.59 Western Africa Sierra Leone 2008 DHS 581 0.48 0.41 0.54 1,210 0.46 0.41 0.50 482 0.51 0.45 0.57 Western Africa Sierra Leone 2010 MICS 3,155 0.72 0.70 0.75 699 0.79 0.76 0.83 Western Africa Senegal 2000 MICS 2,024 0.34 0.32 0.37 610 0.38 0.33 0.42 Western Africa Senegal 2005 DHS 2,092 0.20 0.18 0.23 2,883 0.41 0.38 0.45 1,206 0.47 0.43 0.52 Western Africa Senegal 2006 MIS 2,196 0.35 0.32 0.37 2,314 0.43 0.40 0.46 1,262 0.42 0.38 0.46 

 (Continued...) 

37 
Appendix A − Continued

Treatment seeking for 

diarrhea 

Treatment seeking for 

fever 

Treatment seeking for 

symptoms of ARI 

UN Region Country Year Survey n Proportion 95% CI n Proportion 95% CI n Proportion 95% CI Western Africa Senegal 2008 MIS 972 0.39 0.34 0.44 1,146 0.43 0.39 0.48 402 0.50 0.43 0.57 Western Africa Senegal 2010 DHS 1,734 0.42 0.38 0.45 Western Africa Senegal 2012 DHS 4,270 0.42 0.39 0.44 Western Africa Togo 2000 MICS 1,121 0.27 0.24 0.31 268 0.46 0.38 0.53 Western Africa Togo 2006 MICS 766 0.23 0.19 0.26 230 0.34 0.27 0.41 Western Africa Togo 2010 MICS 1,666 0.58 0.54 0.62 234 0.58 0.50 0.65 Caribbean Cuba 2010 MICS 315 0.96 0.93 1.00 Caribbean Dom Rep 2000 MICS 206 0.69 0.61 0.76 Caribbean Dom Rep 2002 DHS 1,682 0.36 0.33 0.40 3,123 0.65 0.62 0.67 2,249 0.65 0.62 0.67 Caribbean Dom Rep 2007 DHS 1,773 0.53 0.49 0.57 2,369 0.66 0.62 0.69 1,493 0.62 0.58 0.66 Caribbean Haiti 2000 DHS 1,518 0.24 0.21 0.28 2,534 0.41 0.38 0.43 2,398 0.38 0.34 0.42 Caribbean Haiti 2005 DHS 1,217 0.23 0.19 0.28 1,430 0.28 0.25 0.31 1,507 0.25 0.22 0.28 Caribbean Haiti 2012 DHS 1,413 0.35 0.32 0.39 1,852 0.42 0.39 0.45 2,435 0.35 0.32 0.38 Caribbean Jamaica 2005 MICS 92 0.83 0.74 0.91 Caribbean Jamaica 2011 MICS 91 0.84 0.76 0.93 Caribbean Trinid & Tob 2000 MICS 26 0.77 0.63 0.90 Caribbean Trinid & Tob 2006 MICS 27 0.89 0.77 1.01 Central America Belize 2006 MICS 44 0.76 0.62 0.91 Central America Belize 2011 MICS 66 0.88 0.79 0.96 Central America Costa Rica 2011 MICS 166 0.92 0.85 0.98 Central America Honduras 2005 DHS 1,797 0.47 0.44 0.49 1,973 0.52 0.49 0.55 1,891 0.53 0.50 0.56 Central America Honduras 2011 DHS 1,918 0.52 0.49 0.55 2,515 0.62 0.59 0.64 2,097 0.64 0.61 0.67 Central America Nicaragua 2001 DHS 843 0.44 0.40 0.48 1,617 0.62 0.58 0.65 1,992 0.58 0.55 0.61 South America Bolivia 2000 MICS 384 0.59 0.52 0.66 South America Bolivia 2003 DHS 2,267 0.34 0.32 0.37 2,920 0.47 0.44 0.50 2,228 0.48 0.45 0.51 South America Bolivia 2008 DHS 2,055 0.48 0.44 0.51 1,654 0.51 0.47 0.55 

 (Continued...) 

38 
Appendix A − Continued

Treatment seeking for 

diarrhea 

Treatment seeking for 

fever 

Treatment seeking for 

symptoms of ARI 

UN Region Country Year Survey n Proportion 95% CI n Proportion 95% CI n Proportion 95% CI South America Columbia 2000 DHS 649 0.29 0.25 0.33 1,135 0.46 0.43 0.50 South America Columbia 2005 DHS 2,169 0.30 0.27 0.33 3,672 0.43 0.40 0.45 South America Columbia 2010 DHS 2,495 0.43 0.40 0.46 4,717 0.53 0.51 0.55 1,143 0.65 0.61 0.68 South America Guyana 2000 MICS 330 0.65 0.56 0.74 185 0.81 0.73 0.89 South America Guyana 2006 MICS 191 0.62 0.54 0.70 173 0.79 0.70 0.88 South America Guyana 2009 DHS 213 0.59 0.49 0.68 395 0.60 0.54 0.67 210 0.64 0.54 0.73 South America Peru 2000 DHS 2,205 0.38 0.36 0.41 3,496 0.54 0.51 0.56 2,534 0.58 0.55 0.61 South America Peru 2004 DHS 2,680 0.42 0.39 0.45 4,363 0.65 0.63 0.67 3,244 0.67 0.64 0.69 South America Peru 2007 DHS 2,680 0.42 0.39 0.45 4,363 0.65 0.63 0.67 3,244 0.67 0.64 0.69 South America Peru 2009 DHS 1,475 0.42 0.38 0.46 2,349 0.64 0.61 0.66 1,631 0.66 0.62 0.69 South America Peru 2010 DHS 1,399 0.37 0.34 0.41 2,242 0.57 0.54 0.60 1,530 0.57 0.54 0.61 South America Peru 2011 DHS 1,312 0.34 0.30 0.37 1,903 0.63 0.60 0.66 1,457 0.62 0.58 0.65 South America Peru 2012 DHS 1,254 0.33 0.30 0.37 2,031 0.55 0.52 0.58 1,343 0.59 0.56 0.63 South America Suriname 2000 MICS 76 0.62 0.51 0.73 South America Suriname 2006 MICS 155 0.79 0.70 0.87 47 0.76 0.62 0.89 South America Suriname 2010 MICS 233 0.63 0.56 0.70 78 0.83 0.72 0.93 South America Venezuela 2000 MICS 173 0.79 0.71 0.87 Central Asia Kazakhstan 2010 MICS 144 0.83 0.77 0.90 Central Asia Kazakhstan 2005 MICS 172 0.67 0.53 0.82 Central Asia Kyrgyzstan 2012 DHS 221 0.55 0.46 0.64 203 0.44 0.35 0.53 94 0.35 0.22 0.47 Central Asia Tajikistan 2005 MICS 296 0.46 0.40 0.53 64 0.66 0.52 0.79 Central Asia Tajikistan 2012 DHS 716 0.54 0.49 0.59 440 0.58 0.52 0.64 104 0.66 0.55 0.77 Central Asia Uzbekistan 2000 MICS 6 0.50 -0.07 1.07 Central Asia Uzbekistan 2005 MICS 107 0.69 0.59 0.80 Eastern Asia Mongolia 2000 MICS 137 0.83 0.77 0.90 Eastern Asia Mongolia 2006 MICS 314 0.69 0.62 0.75 

 (Continued...) 

39 
Appendix A − Continued

Treatment seeking for 

diarrhea 

Treatment seeking for 

fever 

Treatment seeking for 

symptoms of ARI 

UN Region Country Year Survey n Proportion 95% CI n Proportion 95% CI n Proportion 95% CI Eastern Asia Mongolia 2010 MICS 65 0.87 0.78 0.96 Southern Asia Afghanistan 2010 MICS 2,938 0.71 0.67 0.74 Southern Asia Bangladesh 2004 DHS 485 0.16 0.12 0.19 2,553 0.18 0.16 0.20 1,255 0.20 0.17 0.23 Southern Asia Bangladesh 2006 MICS 1,595 0.85 0.83 0.87 Southern Asia Bangladesh 2007 DHS 560 0.44 0.39 0.49 2,163 0.45 0.42 0.49 768 0.52 0.47 0.57 Southern Asia Bangladesh 2011 DHS 394 0.25 0.20 0.30 3,080 0.27 0.25 0.30 1,375 0.33 0.30 0.37 Southern Asia Bhutan 2010 MICS 440 0.76 0.70 0.82 Southern Asia India 2005 DHS 4,435 0.63 0.60 0.65 7,165 0.73 0.71 0.74 4,158 0.69 0.67 0.71 Southern Asia Maldives 2009 DHS 186 0.84 0.78 0.91 1,078 0.85 0.82 0.88 508 0.81 0.77 0.85 Southern Asia Nepal 2001 DHS 1,285 0.21 0.18 0.24 1,999 0.25 0.22 0.28 1,475 0.26 0.23 0.29 Southern Asia Nepal 2006 DHS 659 0.27 0.22 0.32 983 0.34 0.29 0.38 474 0.34 0.28 0.40 Southern Asia Nepal 2011 DHS 679 0.38 0.32 0.44 906 0.42 0.37 0.47 487 0.43 0.36 0.50 Southern Asia Pakistan 2006 DHS 1,877 0.56 0.53 0.59 2,495 0.67 0.64 0.70 1,590 0.67 0.64 0.71 Southern Asia Pakistan 2012 DHS 2,293 0.75 0.72 0.78 3,907 0.79 0.77 0.82 2,129 0.80 0.77 0.82 Southern Asia Tajikistan 2000 MICS 61 0.74 0.54 0.94 50 0.60 0.43 0.77 South-Eastern Asia Indonesia 2000 MICS 122 0.79 0.71 0.87 South-Eastern Asia Indonesia 2002 DHS 1,498 0.52 0.47 0.56 4,018 0.57 0.55 0.60 1,340 0.61 0.57 0.66 South-Eastern Asia Indonesia 2007 DHS 2,536 0.58 0.55 0.61 5,802 0.67 0.65 0.69 2,175 0.66 0.63 0.70 South-Eastern Asia Indonesia 2012 DHS 2,500 0.65 0.62 0.68 5,366 0.74 0.72 0.76 1,919 0.75 0.72 0.78 South-Eastern Asia Cambodia 2000 DHS 1,579 0.22 0.19 0.25 2,839 0.34 0.32 0.37 1,522 0.37 0.33 0.40 South-Eastern Asia Cambodia 2005 DHS 1,450 0.41 0.37 0.45 2,692 0.48 0.45 0.51 1,265 0.50 0.46 0.55 South-Eastern Asia Cambodia 2010 DHS 1,134 0.59 0.55 0.63 2,080 0.76 0.73 0.79 830 0.76 0.72 0.81 South-Eastern Asia Lao PDR 2000 MICS 148 0.45 0.36 0.53 49 0.48 0.30 0.66 South-Eastern Asia Lao PDR 2006 MICS 618 0.31 0.26 0.36 189 0.50 0.41 0.60 

 (Continued...) 

40 
Appendix A − Continued

Treatment seeking for 

diarrhea 

Treatment seeking for 

fever 

Treatment seeking for 

symptoms of ARI 

UN Region Country Year Survey n Proportion 95% CI n Proportion 95% CI n Proportion 95% CI South-Eastern Asia Lao PDR 2012 MICS 1,550 0.57 0.53 0.61 366 0.57 0.49 0.66 South-Eastern Asia Myanmar 2000 MICS 251 0.60 0.52 0.69 South-Eastern Asia Philippines 2000 MICS 358 0.66 0.61 0.71 South-Eastern Asia Philippines 2003 DHS 746 0.33 0.29 0.36 1,675 0.47 0.44 0.50 728 0.55 0.51 0.60 South-Eastern Asia Philippines 2008 DHS 571 0.34 0.29 0.39 1,481 0.39 0.36 0.43 654 0.46 0.42 0.51 South-Eastern Asia Thailand 2005 MICS 378 0.86 0.80 0.91 South-Eastern Asia Timor-Leste 2009 DHS 1,388 0.72 0.69 0.76 1,760 0.73 0.70 0.76 389 0.71 0.66 0.77 South-Eastern Asia Vietnam 2000 MICS 416 0.40 0.36 0.44 268 0.72 0.65 0.80 South-Eastern Asia Vietnam 2002 DHS 137 0.60 0.49 0.71 255 0.71 0.64 0.79 South-Eastern Asia Vietnam 2006 MICS 448 0.60 0.54 0.67 171 0.90 0.85 0.96 South-Eastern Asia Vietnam 2010 MICS 581 0.80 0.76 0.84 122 0.84 0.76 0.92 Western Asia Armenia 2000 DHS 129 0.26 0.19 0.34 261 0.26 0.20 0.32 186 0.26 0.18 0.34 Western Asia Armenia 2005 DHS 224 0.32 0.23 0.41 189 0.23 0.14 0.32 104 0.38 0.25 0.51 Western Asia Armenia 2010 DHS 127 0.43 0.31 0.55 159 0.55 0.45 0.65 106 0.60 0.46 0.75 Western Asia Azerbaijan 2000 MICS 258 0.32 0.26 0.38 55 0.42 0.29 0.55 Western Asia Azerbaijan 2006 DHS 231 0.34 0.25 0.42 230 0.41 0.32 0.49 98 0.38 0.23 0.52 Western Asia Georgia 2005 MICS 59 0.74 0.59 0.88 Western Asia Iraq 2000 MICS 2,349 0.63 0.60 0.66 954 0.79 0.75 0.82 Western Asia Iraq 2006 MICS 2,367 0.88 0.86 0.89 Western Asia Iraq 2011 MICS 3,800 0.85 0.83 0.87 Western Asia Jordan 2002 DHS 900 0.46 0.41 0.50 544 0.61 0.56 0.66 355 0.65 0.59 0.72 Western Asia Jordan 2007 DHS 1,659 0.55 0.51 0.60 1,250 0.70 0.66 0.74 653 0.71 0.64 0.78 Western Asia Jordan 2012 DHS 1,540 0.56 0.51 0.61 1,709 0.69 0.65 0.73 1,164 0.74 0.70 0.78 Western Asia Syria 2006 MICS 588 0.88 0.85 0.91 

 (Continued...) 

41 
Appendix A − Continued

Treatment seeking for 

diarrhea 

Treatment seeking for 

fever 

Treatment seeking for 

symptoms of ARI 

UN Region Country Year Survey n Proportion 95% CI n Proportion 95% CI n Proportion 95% CI Western Asia Turkey 2003 DHS 1,858 0.42 0.39 0.45 1,298 0.45 0.42 0.49 Western Asia Yemen 2006 MICS 495 0.63 0.57 0.69 Eastern Europe Belarus 2005 MICS 339 0.90 0.86 0.94 Eastern Europe Belarus 2012 MICS 230 0.93 0.90 0.97 Eastern Europe Moldova 2000 MICS 24 0.82 0.66 0.97 Eastern Europe Moldova 2006 DHS 131 0.40 0.31 0.49 246 0.55 0.48 0.61 116 0.60 0.50 0.70 Eastern Europe Ukraine 2012 MICS 142 0.94 0.90 0.98 Southern Europe Albania 2000 MICS 21 0.87 0.69 1.06 Southern Europe Albania 2008 DHS 81 0.61 0.48 0.74 119 0.71 0.63 0.80 141 0.70 0.59 0.81 Southern Europe Bos & Herz 2000 MICS 40 0.80 0.67 0.93 Southern Europe Bos & Herz 2006 MICS 137 0.91 0.87 0.95 Southern Europe Bos & Herz 2011 MICS 91 0.87 0.80 0.94 Southern Europe Montenegro 2006 MICS 320 0.93 0.90 0.97 Southern Europe Macedonia 2011 MICS 37 0.83 0.67 1.00 Southern Europe Malta 2005 MICS 32 0.98 0.92 1.03 Southern Europe Serbia 2005 MICS 202 0.93 0.89 0.98 Southern Europe Serbia 2010 MICS 201 0.93 0.86 1.00 Melanesia Vanuatu 2007 MICS 133 0.74 0.64 0.84 42 0.72 0.54 0.90 

42 
43 

Appendix B: Loess regression and linear regression results for trends in treatment seeking 

for diarrhea by subregions 
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Appendix C: Loess regression and linear regression results for trends in treatment seeking 

for fever by subregions 
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Appendix D: Loess regression and linear regression results for trends in treatment seeking 

for symptoms of ARI by subregions 
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Appendix E: Results of subregional and global meta-analyses of predictors of treatment 

seeking for diarrhea
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Appendix F: Results of subregional and global meta-analyses of predictors of treatment 

seeking for fever 

 
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Appendix G: Results of subregional and global meta-analyses of predictors of treatment 

seeking for symptoms of ARI 
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