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Bulletin of the World Health Organization logoLink to Bulletin of the World Health Organization
. 2009 Jan 29;87(3):216–224. doi: 10.2471/BLT.08.052175

Access to health care and mortality of children under 5 years of age in the Gambia: a case–control study

Accès aux soins de santé et mortalité des enfants de moins de 5 ans en Gambie : étude cas-témoins

Acceso a atención de salud y mortalidad de menores de 5 años en Gambia: estudio de casos y controles

الوصول إلى الرعاية الصحية ووفيات الأطفال دون الخامسة من العمر في غامبيا: دراسة للحالات والشواهد

Merrin E Rutherford a, John D Dockerty a, Momodou Jasseh b, Stephen RC Howie b, Peter Herbison a, David J Jeffries b, Melissa Leach c, Warren Stevens b, Kim Mulholland d, Richard A Adegbola b, Philip C Hill b,
PMCID: PMC2654650  PMID: 19377718

Abstract

Objective

To assess whether traditional measures of access to health care (distance and travel time to a facility) and non-traditional measures (social and financial support indicators) are associated with mortality among children under 5 years of age in the Gambia.

Methods

We conducted a case–control study in a population under demographic surveillance. Cases (n = 140) were children under 5 years of age who died between 31 December 2003 and 30 April 2006. Each case was matched in age and sex to five controls (n = 700). Information was gathered by interviewing primary caregivers. The data were analysed using conditional logistic regression.

Findings

Of traditional measures of access, only rural versus urban/periurban residence was important: children from rural areas were more likely to die (OR: 4.9; 95% confidence interval, CI: 1.2–20.2). For non-traditional measures, children were more likely to die if their primary caregivers lacked help with meal preparation (OR: 2.3; 95% CI: 1.2–4.1), had no one to relax with (OR: 1.8; 95% CI: 1.1–2.9), had no one who could offer good advice (OR: 23.1; 95% CI: 4.3–123.4), had little say over how earned money was spent (OR: 12.7; 95% CI: 1.3–127.6), were unable to cut spending for health care (OR: 2.5; 95% CI: 1.5–4.2) or had to carry out odd jobs to pay for the care (OR: 3.4; 95% CI: 2.1–5.5). A protective effect was observed when the caregiver had other children to care for (OR: 0.2; 95% CI: 0.1–0.5).

Conclusion

Improving access to health-care for children in the Gambia and similar settings is not simply a matter of reducing travel time and distance to a health facility, but requires improvements in caregivers’ support networks and their access to the financial resources they need.

Introduction

Every year approximately 10 million children under 5 years of age die throughout the world, mostly in developing countries.1 Of every 1000 children born in sub-Saharan Africa, approximately 170 die, compared with less than 10 of those who are born in developed countries.2 The fourth Millennium Development Goal is to reduce child and infant mortality in the world by two-thirds by 2015,2 yet current estimates suggest that at least 44 developing countries have less than a 20% chance of achieving the goal.1 An understanding of the risk factors associated with child mortality and the design of appropriate interventions are urgently required.

Population-based studies suggest that poor access to health care, which results in delayed attendance at a health facility or none at all, may be a key determinant of mortality in children under 5 years of age in developing countries.3,4 To assess this relationship, researchers have adopted simple traditional measures, such as distance from the household to a health facility,57 availability of transportation8 and health-care costs.9 Their findings have been inconclusive. Recently, qualitative studies1012 have suggested the need to consider additional barriers, such as lack of social support for primary caregivers, limited caregiver autonomy in decision-making and financial matters, and social exclusion at health clinics. Studies that assess the relationship between these factors and child death are needed. Therefore, we evaluated traditional measures of access to health care in addition to non-traditional measures to study mortality in children under 5 years of age in the Gambia.

Methodology

Population and study design

We conducted a case-control study within the Farafenni Demographic Surveillance System (FDSS), on the North Bank of the River Gambia. The FDSS was established in 1981 as a platform for research, its location being considered particularly ideal for malaria studies. The FDSS covers approximately 17 000 rural and 26 000 urban dwellers belonging to three main ethnic groups (Wolloff, Mandinka and Fula) among which young age, high fertility, low educational levels, frequent polygamy and widespread poverty prevail.13 Water is gathered primarily from communal wells with hand pumps, and 12% of the population utilizes uncovered wells. Pit latrines predominate. Villages have no electricity, and transportation routes are dirt roads.13

The cases were all children under 5 years of age under coverage by the FDSS who had died between 31 December 2003 and 30 April 2006. Children were excluded from the study if their primary caregiver could not be located or had since died or if their cause of death was unrelated to access to health care (e.g. congenital malformations, in-hospital neonatal deaths, immediate death after an injury, etc.). Verbal autopsies, available for 92% of the cases, were conducted within 3 months of death by trained field workers using the standardized INDEPTH form, as part of routine FDSS practice.14 They were assessed by consensus between two physicians.

Controls were children under 5 years of age who were registered in the FDSS and who were alive at the time their respective cases died. They were excluded from the study if the primary caregiver could not be located or had since died. From the FDSS population, 10 controls were randomly identified for and matched with each case by age (within the same birth month) and sex. Only the first five random choices were selected, followed by the next child on the list of random choices in the event of refusal to participate.

On the assumption that 70% of the controls would take at least 30 minutes or more to travel to a health-care facility, we estimated that at least 120 cases and 600 controls were required to detect an odds ratio (OR) of 2.0 for less than or more than 30 minutes of travel time as a binary variable at a power of 80% and an alpha level of 0.05.

Data collection

After written informed consent was obtained from primary caregivers, data were collected from them in their native language between 11 May 2006 and 25 October 2006. Interviews were conducted, whenever possible in private locations, by six trained and experienced Gambian fieldworkers who were familiar with the area and local languages.

The questionnaire had seven sections: (i) demographic characteristics; (ii) child characteristics (such as ethnicity); (iii) child health; (iv) household features, including amenities and wealth; (v) social support; (vi) health-seeking behaviour and (vii) traditional measures of access to health care. A household crowding index was adopted from a previous Gambian study.15 Social and financial questions relevant to accessing health care were identified and refined through a literature review that yielded 11 social support questions from a medical outcomes study16 plus social1720 and economic5,2124 questions from previous studies in the Gambia and elsewhere. These were refined following focus group discussions, two rounds of piloting and expert review. The focus groups were composed of mothers with children from three villages. The mothers of identified cases were excluded. The reference date for each control interview was the day on which the control was the same age as the case child upon death. Personal prompts in relation to the reference dates were developed using an Islamic calendar and significant village-specific events.

To determine which health centres were appropriate and should be used to calculate distance and time from the households, we ascertained when each centre was established, whether it had the capacity to treat a seriously ill child, and what vaccinations and essential medications it had in stock. Respondents were allocated to the nearest centre considered appropriate. Their choice took precedence if it differed from the facility assigned. Using a hand-held global positioning system (Garmin GPS 12 Personal Navigator®), we calculated the distance to each health centre from the centre of each village and the 45 periurban suburbs. Travel time was calculated by replicating the mode of travel each respondent used: walking, horse or donkey cart, bush taxi (van to transport 20 to 30 people), private taxi or car. Transportation costs were obtained from taxi station attendants and respondents.

Data management and analysis

Completed questionnaires were checked immediately and queries were resolved. Available demographic data were extracted from the FDSS database and cross-checked with hard copy questionnaires. Other data from the questionnaires were double entered into a database, verified and analysed using Stata software version 8.0 (Stata Corp, College Station, TX, United States of America). ORs were derived using conditional logistic regression. Confounding factors, in addition to variables felt to be related to access to health care, were incorporated into the questionnaire based on a review of relevant literature and on considerations of plausibility. Such factors included demographic characteristics, breastfeeding history, vaccination status and vitamin A supplementation status. These were considered for inclusion in multivariate models using the change in estimate methodology.25 For each variable, possible confounders were entered singly into a multivariable model. Any variable that caused the crude OR to change by more than 10%, or that made a non-significant result become significant, were selected for the final multivariate model. We applied the likelihood ratio test to detect interactions between variables. Correlation coefficients were calculated separately for social and financial variables.

The Joint Government of the Gambia/Medical Research Council Ethics Committee approved the study.

Results

We recruited 141 of 163 possible cases (Fig. 1). One case was later retrospectively excluded because the death bore no relation to health-care access. We approached 776 randomly selected controls to yield 700 for interview (Fig. 1); 76 were the second choice, and 4 were the third choice. Refusal rates were less than 5%. The child’s mother was the primary caregiver for 135 (96.4%) cases and 690 (98.6%) controls. The mean age of mothers of case children (28 years; range: 16–50) did not differ significantly from that of control children’s mothers. Cases and controls did not differ significantly in either ethnicity or primary caregiver’s educational level.

Fig. 1.

Case and control recruitment process, May–October 2006, for study conducted in the FDSS, the Gambia

FDSS, Farafenni demographic surveillance system.

Fig. 1

Sixty nine (49.3%) cases died before the age of 1 year (Table 1), and more than half the deaths occurred at home (52.9%). The commonest causes of death were fever of unknown origin (23.3%) and diarrhoea (20.2%). The terminal illness lasted less than a week in the majority of cases (84.3%), and 89.3% of the children were seen at a government health facility.

Table 1. Characteristics of children under 5 years of age who died in the FDSS, the Gambia, between 31 December 2003 and 30 April 2006.

Characteristic No. (%)
Age of child at death, in months
0–6 40 (28.6)
7–12 29 (20.7)
13–24 31 (22.1)
25–60 40 (28.6)
Cause of death (n = 129)
Fever of unknown origin 30 (23.3)
Diarrhoea 26 (20.2)
Pneumonia 15 (11.6)
Meningitis or cerebral malaria 17 (13.2)
Neonatal sepsis 6 (4.7)
Vomiting 3 (2.3)
Non-specific/other 32 (24.8)
Place of death
Hospital 45 (32.1)
Health centre 13 (9.3)
Home 74 (52.9)
Other 8 (5.7)
Duration of illness, in days
1–2 76 (54.3)
3–7 42 (30.0)
8–14 10 (7.1)
15–30 6 (4.3)
> 31 6 (4.3)
Highest level of treatment received for illness
Health centre 60 (42.9)
Hospital 65 (46.4)
Village health worker 5 (3.6)
Traditional healer/marabout 5 (3.6)
Private physician/pharmacist/drug shop keeper 4 (2.9)
Unknown 1 (0.7)

FDSS, Farafenni demographic surveillance system.

A longer distance to travel (more than 3 km) and higher costs to reach the health facility (more than 5 dalasi; 1 US dollar = 30 dalasi) were significantly associated with child death in univariate analyses (Table 2). However, after controlling for possible confounding factors (referenced at the bottom of each table), only place of residence retained significance: rural dwellers had a significantly greater likelihood of death than urban dwellers (OR: 4.9; 95% confidence interval, CI: 1.2–20.2).

Table 2. Association between traditional indicators of access to health care and mortality in children under 5 years of age, FDSS, the Gambia.

Variable Cases No. (%) Controls No. (%) Crude OR (95% CI) Adjusted OR (95% CI)
Location of residence
Urban/peri-urban 57 (40.7) 386 (55.1) 1.0 1.0
Rural 83 (59.3) 314 (44.9) 1.8 (1.2–2.6) 4.9 (1.2–20.2)a
Distance to health centre, in km
0–3 62 (44.3) 400 (57.1) 1.0 1.0
> 3 to 6 57 (40.7) 214 (30.6) 1.7 (1.2–2.6) 1.2 (0.5–2.6)
> 6 21 (15.0) 86 (12.3) 1.6 (0.9–2.8) 1.8 (0.6–5.6)b
Distance, in km, and travel time, in minutes, index
< 3 km and < 30 min 51 (36.4) 328 (46.9) 1.0 1.0
> 3 km and < 30 min or < 3 km and > 30 min 33 (23.6) 142 (20.3) 1.5 (0.9–2.4) 1.2 (0.7–2.1)
> 3 km and > 30 min 56 (40.0) 230 (32.9) 1.6 (1.0–2.4) 1.1 (0.7–1.9)c
Cost of reaching health centre, in dalasi
0–4 113 (80.7) 600 (85.7) 1.0 1.0
5–9 20 (14.3) 58 (8.3) 1.8 (1.1–3.2) 0.9 (0.3–3.2)
≥ 10 7 (5.0) 42 (6.0) 0.9 (0.4–2.1) 0.7 (0.2–2.4)d

FDSS, Farafenni demographic surveillance system; OR, odds ratio.
Factors included in multivariate analysis:
a Allocated health centre, distance to a health centre, readily available money, child vitamin A status, child vaccination status;
b Allocated health centre, travel time to a health centre, readily available money, child vitamin A status, child vaccination status;
c Rural residence;
d Travel time to a health centre, distance to a health centre, readily available money, child vitamin A status, vaccination status, rural residence.

In contrast, 10 non-traditional measures of access to health care were significantly associated with child death after controlling for confounders (Table 3 and Table 4). These included measures of primary caregiver social support: not having someone to relax with (OR: 1.8; 95% CI: 1.1–2.9); not having someone else to prepare meals (OR: 2.3; 95% CI: 1.2–4.1); not participating in social groups (OR: 3.6; 95% CI: 1.9–6.9); and not knowing anyone who could provide good advice in a crisis situation (OR: 23.1; 95% CI: 4.3–123.4). Surprisingly, not having someone who showed caring and kindness to the caregiver was protective against child death (OR: 0.4; 95% CI: 0.2–0.9). Moderately strong correlations (r = 0.60–0.69) were found between each of the following: having someone to talk with, having someone to relax with, having someone who understood your problems and having someone who showed caring and kindness. Also, having someone to help with domestic duties and having someone to prepare meals were moderately correlated with each other (r = 0.6).

Table 3. Association between primary caregiver social support indicators and mortality in children under 5 years of age, FDSS, the Gambia.

Variable name Cases No. (%) Controls No. (%) Crude OR (95% CI) Adjusted OR (95% CI)
Had someone who understood your problems
Most or all of the time 97 (69.3) 490 (70.0) 1.0 1.0
Some of the time 35 (25.0) 166 (23.7) 1.1 (0.7–1.6) 1.1 (0.7–1.6)
A little or none of the time 8 (5.7) 44 (6.3) 0.9 (0.4–2.0) 0.9 (0.4–2.0)*
Had someone who showed you kindness and caring (n = 699 due to missing data)
Most or all of the time 91 (65.0) 428 (61.2) 1.0 1.0
Some of the time 41 (29.3) 195 (27.9) 1.0 (0.7–1.5) 0.8 (0.5–1.3)a
A little or none of the time 8 (5.7) 76 (10.9) 0.5 (0.2–1.1) 0.4 (0.2–0.9)a
Had someone to relax with
Most or all of the time 70 (50.0) 340 (48.6) 1.0 1.0
Some of the time 30 (21.4) 248 (35.4) 0.6 (0.4–0.9) 0.5 (0.3–0.9)b
A little or none of the time 40 (28.6) 112 (16.0) 1.7 (1.1–2.7) 1.8 (1.1–2.9)b
Had someone to take you to a doctor (n = 699 due to missing data)
Most or all of the time 130 (92.9) 665 (95.1) 1.0 1.0
Some of the time 7 (5.0) 31 (4.4) 1.1 (0.5–2.6) 1.1 (0.5–2.7)c
A little or none of the time 3 (2.1) 3 (0.4) 5.0 (1.0–24.9) 4.5 (0.9–22.9)c
Had someone to prepare meals if you were unable to
Most or all of the time 103 (73.6) 541 (77.3) 1.0 1.0
Some of the time 18 (12.9) 108 (15.4) 0.9 (0.5–1.5) 0.9 (0.5–1.6)d
A little or none of the time 19 (13.6) 51 (7.3) 2.0 (1.1–3.5) 2.3 (1.2–4.1)d
Had someone to help with domestic duties
Most or all of the time 101 (72.1) 480 (68.6) 1.0 1.0
Some of the time 18 (12.9) 153 (21.9) 0.5 (0.3–0.9) 0.5 (0.3–0.9)e
A little or none of the time 21 (15.0) 67 (9.6) 1.5 (0.9–2.6) 1.8 (1.0–2.9)e
Participation in social groups
Yes 119 (85.0) 639 (91.3) 1.0 1.0
No 21 (15.0) 61 (8.7) 1.8 (1.1–3.1) 3.6 (1.9–6.9)f
Had someone to talk with
Most or all of the time 80 (57.1) 421 (60.1) 1.0 1.0
Some of the time 43 (30.7) 228 (32.6) 1.0 (0.7–1.5) 1.0 (0.7–1.5)
A little or none of the time 17 (12.1) 51 (7.3) 1.7 (1.0–3.2) 1.7 (1.0–3.2)*
Had someone to give good advice in a crisis
Most or all of the time 119 (85.0) 586 (83.7) 1.0 1.0
Some of the time 15 (10.7) 111 (15.9) 0.6 (0.4–1.2) 0.8 (0.4–1.4)g
A little or none of the time 6 (4.3) 3 (0.4) 13.3 (2.7–66.5) 23.1 (4.3–123.4)g

FDSS, Farafenni demographic surveillance system; OR, odds ratio. * Association not altered more than 10% following multivariate analysis.
Factors included in multivariate analysis:
a Primary caregiver ethnicity, allocated health centre, number of members in household;
b Primary caregiver ethnicity, allocated health centre, rural residence;
c Allocated health centre;
d Allocated health centre;
e Rural residence;
f Rural residence, primary caregiver ethnicity, allocated health centre, number of members in household;
g Primary caregiver ethnicity, primary caregiver household position, rural residence, allocated health centre.

Table 4. Association between primary caregiver financial indicators of access to health care and child death, FDSS, the Gambia.

Variable Cases No. (%) Controls No. (%) Crude OR (95% CI) Adjusted OR (95% CI)
Primary caregiver wealth
Amount of income generated by primary caregiver, in dalasi
0 95 (67.9) 383 (54.7) 1.0 1.0
1–500 23 (16.4) 115 (16.4) 0.8 (0.5–1.3) 1.0 (0.5–2.0)a
> 500 22 (15.7) 202 (28.9) 0.4 (0.3–0.7) 0.6 (0.3–1.2)a
Received money from an outside source
Yes 53 (37.9) 286 (40.9) 1.0 1.0
No 87 (62.1) 414 (59.1) 1.1 (0.8–1.6) 1.1 (0.8–1.6)*
Financial autonomy (95 cases and 383 controls had no income)
Could decide how earned money was spent
All 41 (91.1) 306 (96.5) 1.0 1.0
Some, a little, or none 4 (8.9) 11 (3.5) 9.7 (1.0–92.5) 12.7b (1.3–127.6)b
Used own money to pay for health care
Yes 12 (8.6) 36 (5.1) 1.0 1.0
No 128 (91.4) 664 (94.9) 0.6 (0.3–1.2) 0.5 (0.2–1.0)c
Monetary sources used to cover health care costs (indicators of availability)
Savings
Yes 72 (51.4) 393 (56.1) 1.0 1.0
No 68 (48.6) 307 (43.9) 1.2 (0.8–1.7) 1.2 (0.8–1.7)*
Cutting back on spending
Yes 18 (12.9) 186 (26.6) 1.0 1.0
No 122 (87.1) 514 (73.4) 2.5 (1.5–4.2) 2.5 (1.5–4.2)*
Selling goods of livestock
Yes 59 (42.1) 233 (33.3) 1.0 1.0
No 81 (57.9) 467 (66.7) 0.7 (0.5–1.0) 0.9 (0.6–1.3)d
Monetary sources used to cover child death and health care costs (indicators of unavailability)
Doing odd jobs
No 103 (73.6) 640 (91.4) 1.0 1.0
Yes 37 (26.4 60 (8.6) 3.8 (2.4–6.2) 3.4 (2.1–5.5)e
Borrowing from friends
No 133 (95.0) 664 (94.9) 1.0 1.0
Yes 7 (5.0) 36 (5.1) 1.0 (0.4–2.2) 0.7 (0.3–1.7)f
Borrowing from lenders
No 137 (97.9) 682 (97.4) 1.0 1.0
Yes 3 (2.1) 18 (2.6) 0.8 (0.2–2.8) 0.6 (0.2–2.2)g
Time availability
Average amount of time spent working at any occupation, in hours
0–5 9 (6.4) 109 (15.6) 1.0 1.0
6–10 108 (77.1) 511 (73.0) 2.6 (1.3–5.3) 2.9 (0.8–10.2)h
11–15 23 (16.4) 80 (11.4) 3.6 (1.6–8.4) 2.5 (0.6–10.1)h
Number of other children cared for by primary caregiver
0 14 (10.0) 28 (4.0) 1.0 1.0
1–3 90 (64.3) 462 (66.0) 0.4 (0.2–0.8) 0.2 (0.1–0.5)i
≥ 4 36 (25.7) 210 (30.0) 0.3 (0.2–0.7) 0.2 (0.1–0.4)i

FDSS, Farafenni demographic surveillance system; OR, odds ratio. * Association not altered beyond 10% following multivariate analysis.
Factors controlled for in multivariate analysis:
a Allocated health centre, readily available money, vitamin A status, vaccination status, time spent working, rural residence;
b Primary caregiver educational level;
c Primary caregiver ethnicity, primary caregiver age, rural residence, time spent working, primary caregiver education level;
d Rural residence, allocated health centre;
e Rural residence;
f Rural residence, allocated health centre;
g Allocated health centre;
h Rural residence, allocated health centre, vaccination status, vitamin A status;
i Number of pregnancies of primary caregiver.

Children whose primary caregivers had little say over how money was spent (Table 4) were at increased risk of dying compared with those whose caregivers could always decide (OR: 12.7; 95% CI: 1.3–127.6). Children whose primary caregivers could not cut back on spending for health care were at greater risk of dying (OR: 2.5; 95% CI: 1.5–4.2). The same was true of children whose primary caregivers had to do odd jobs to generate money for health care (OR: 3.4; 95% CI: 2.1–5.5). Measures of correlation between financial variables were not greater than r = 0.3 for any comparison. Two significant interactions were identified: for children whose caregivers were unable to cut back on health-care spending but could use their savings to pay for health care, the OR for child death was 0.2 (95% CI: 0.1–0.9) as opposed to 5.3 (95% CI: 2.4–11.5) for children whose caregivers were unable to cut back on health-care spending or to use their savings for this purpose; rural children whose caregivers did not have an outside source of money to pay for health care had an OR for child death of 2.1 (95% CI: 1.2–2.7) when compared with urban children (OR: 1.0; 95% CI: 0.5–1.8).

With respect to time availability, children whose primary caregivers cared for other children were less likely to die than those whose primary caregivers cared for no other children, regardless of the number of children cared for: (1–3 other children: OR: 0.2; 95% CI: 0.1–0.5; 4 or more other children: OR: 0.2; 95% CI: 0.1−0.4).

Discussion

Major findings

After controlling for possible confounders, a rural place of residence was significantly associated with an increased risk of death before the age of 5 years, but no other traditional measure of access to health care retained statistical significance. However, 10 additional, non-traditional variables, including indicators of social support for the primary caregiver, his/her degree of financial autonomy and his/her source of revenue for health-care expenses, were significantly associated with child death. These findings have important implications for the design of new interventions against child death in the Gambia and other developing countries and present new avenues for further research.

Comparison with other studies

The increased risk of death in rural dwellers was not explained by a longer physical distance to a health care facility. It may be that rural dwellers simply take longer to seek appropriate help. In Malawi, rural residence was significantly associated with an increased risk of late medical treatment,26 while in a multicountry analysis of sub-Saharan African countries, sick urban children were more likely to visit a health facility than rural children.27 The lack of a significant association in our study between distance to a health care facility and child death is consistent with the results of studies performed elsewhere in Africa: non-significant increases in the risk of child death in association with increasing distance to health care were reported from Burkina Faso6 and the northern Democratic Republic of the Congo.7 This suggests that in such settings, physical distance to a health facility has little effect on access to health care.

The importance of social support in relation to access to health care has been proposed through qualitative research in Chad,11 the Gambia,18 Guinea12 and India.19 Social support is thought to facilitate health care access through increasing help with domestic tasks, peer encouragement and knowledge-sharing. In Ethiopia, a significant protective association between increased social capital (defined in terms of membership in community groups, evidence of leadership, ability to borrow money, trustworthiness and interpersonal indicators) and child death was identified.20 Some caregivers are also socially excluded at health centres and treated in a discriminatory fashion.18 Thus, impaired access affects even those who attend health facilities.

Financial autonomy is likely to increase the primary caregiver’s ability to access health care and pay for it. Qualitative research in Ghana has drawn attention to the importance of female financial autonomy for household expenditure in terms of the ability to obtain health care,28 while children of Tanzanian women who were the sole decision-makers regarding health care were significantly less likely to die.29 Our findings show that children of caregivers who did not have to do odd jobs to pay for health care or who were able to generate money for health care by cutting back on spending were less likely to die. In Viet Nam, poor people who had to borrow money delayed seeking treatment at health facilities.30 Together, these findings indicate that lack of an available monetary source to cover health care costs delays health care seeking behaviour and increases the risk of death.

When investigating the caregiver’s time availability, having to care for other children besides the one at risk of death showed a protective effect clearly not explained by high maternal parity or overcrowding. In contrast, Van den Broeck et al. showed that the risk of child death in the northern Democratic Republic of the Congo increased with a parity of five or more as a result of having limited time for child care.7 It is possible that primary caregivers that look after more children have greater experience with serious illness and seek help earlier. Previous research has shown that poor symptom recognition delays health care seeking and that caregiver knowledge about health protects against child death.28,31,32

The majority of deaths in this study were caused by infectious diseases. In over 80% of the cases the final illness lasted less than 1 week, and over half the children died at home (53%). According to previous research using verbal autopsies in the Gambia33 and Guinea-Bissau,34 acute diarrhoea and fever are the leading causes of death in children under 5 years of age. Studies in the Gambia,33 Guinea-Bissau34 and the United Republic of Tanzania21 have shown that children most commonly die at home. In this study the number of children who received modern health care (as opposed to traditional treatments) for their final illness is consistent with the findings of recent studies in Guinea-Bissau34 and the United Republic of Tanzania,21 where 93% and 75% of children, respectively, sought modern health care.

Study strengths and weaknesses

Selection from the community at large allowed inclusion of cases and controls who did not utilize health care services. We chose death as the outcome because it represents severe illness, it is clearly defined and measurable, and its risk factors in children under 5 years of age in developing countries are poorly known. Future studies might include other outcome variables. The use of FDSS data for selection ensured that cases and controls were from the same population and that the majority of cases were included, which minimized selection bias. We considered selecting controls who were ill, but frequent illness is extremely common, if not universal, among Gambian children, and both cause-specific and non-cause-specific definitions of illness are problematic. The FDSS population may not be fully representative, as individuals need to have resided in the area for 3 months before being registered, so recent migrants and the transient population may have been excluded. However, because these people are probably the most susceptible to social exclusion, including them would probably have strengthened our findings. Recall bias was minimized by means of personal prompts, and responder bias was reduced by conducting interviews in private locations and not providing response options. Low refusal and drop-out rates made non-participation bias unlikely. We controlled for a wide range of confounding factors by means of multivariate analysis, although we could not assess birth weight.

Conclusion

A simplistic approach to health care provision in countries such as the Gambia, based on distance and travel time to a health facility, may be inadequate. In light of the priority to achieve the fourth Millennium Development Goal by 2015, reductions in child mortality through improved health care access will benefit from a focus on additional measures. The strengthening of social support networks for children’s caregivers might be achieved through community group development and implementation of community systems that can provide them with the support they need when seeking health care.20 It is important to also improve their access to financial resources through tools such as microfinancing35. Further research in other settings is required to confirm these findings. ■

Acknowledgements

We thank the population covered by the FDSS for its time and cooperation; the Gambian Government; Pierre Gomez and Simon Donkor for data management; our fieldworkers and village reporters; and Prof. Charlotte Paul for her useful comments.

Footnotes

Funding: This study was funded by The Medical Research Council of the United Kingdom and the University of Otago, New Zealand.

Competing interests: None declared.

References

  • 1.Murray CJ, Laakso T, Shibuya K, Hill K, Lopez AD. Can we achieve Millennium Development Goal 4? New analysis of country trends and forecasts of under-5 mortality to 2015. Lancet. 2007;370:1040–54. doi: 10.1016/S0140-6736(07)61478-0. [DOI] [PubMed] [Google Scholar]
  • 2.Black RE, Morris SS, Bryce J. Where and why are 10 million children dying every year? Lancet. 2003;361:2226–34. doi: 10.1016/S0140-6736(03)13779-8. [see comment] [DOI] [PubMed] [Google Scholar]
  • 3.Pison G, Trape JF, Lefebvre M, Enel C. Rapid decline in child mortality in a rural area of Senegal. Int J Epidemiol. 1993;22:72–80. doi: 10.1093/ije/22.1.72. [DOI] [PubMed] [Google Scholar]
  • 4.Greenwood BM, Bradley AK, Byass P, Greenwood AM, Menon A, Snow RW, et al. Evaluation of a primary health care programme in the Gambia. II. Its impact on mortality and morbidity in young children. J Trop Med Hyg. 1990;93:87–97. [PubMed] [Google Scholar]
  • 5.Magnani RJ, Rice JC, Mock NB, Abdoh AA, Mercer DM, Tankari K. The impact of primary health care services on under-five mortality in rural Niger. Int J Epidemiol. 1996;25:568–77. doi: 10.1093/ije/25.3.568. [DOI] [PubMed] [Google Scholar]
  • 6.Becher H, Muller O, Jahn A, Gbangou A, Kynast-Wolf G, Kouyate B. Risk factors of infant and child mortality in rural Burkina Faso. Bull World Health Organ. 2004;82:265–73. [PMC free article] [PubMed] [Google Scholar]
  • 7.Van den Broeck J, Eeckels R, Massa G. Maternal determinants of child survival in a rural African community. Int J Epidemiol. 1996;25:998–1004. doi: 10.1093/ije/25.5.998. [DOI] [PubMed] [Google Scholar]
  • 8.Tsay C. Possible effects of transportation on mortality differentials in central Taiwan. Jing Ji Lun Wen. 1985;13:145–66. [PubMed] [Google Scholar]
  • 9.James C, Morris SS, Keith R, Taylor A. Impact on child mortality of removing user fees: simulation model. BMJ. 2005;331:747–9. doi: 10.1136/bmj.331.7519.747. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Baume C, Helitzer D, Kachur SP. Patterns of care for childhood malaria in Zambia. Soc Sci Med. 2000;51:1491–503. doi: 10.1016/S0277-9536(00)00049-6. [DOI] [PubMed] [Google Scholar]
  • 11.Hampshire K. Networks of nomads: negotiating access to health resources among pastoralist women in Chad. Soc Sci Med. 2002;54:1025–37. doi: 10.1016/S0277-9536(01)00078-8. [DOI] [PubMed] [Google Scholar]
  • 12.Gordon AJ, Yoder S, Camara M. Responding to childhood illness in upper Guinea: Ecological approaches, prospective ethnography, and health promotion with IMCI (intergrated management of childhood illness). Paper presented at the conference: Locating the field: the ethnography of medical research in Africa, Kilifi, Kenya, 4–9December2005 [Google Scholar]
  • 13.Farafenni Demographic Surveillance System Report. profile of the Farafenni DSS, the Gambia Farafenni: Medical Research Council; 2004. [Google Scholar]
  • 14.Standardized VA questionnaire (revised August 2003). Available from: http://www.indepth-network.org/index.php?option=com_content&task=view&id=98&Itemid=186 [accessed on 20 May 2008].
  • 15.Hill PC, Stevens W, Hill S, Bah J, Donkor SA, Jallow A, et al. Risk factors for defaulting from tuberculosis treatment: a prospective cohort study of 301 cases in the Gambia. Int J Tuberc Lung Dis. 2005;9:1349–54. [PubMed] [Google Scholar]
  • 16.Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med. 1991;32:705–14. doi: 10.1016/0277-9536(91)90150-B. [DOI] [PubMed] [Google Scholar]
  • 17.Begin F, Frongillo EA, Jr, Delisle H. Caregiver behaviors and resources influence child height-for-age in rural Chad. J Nutr. 1999;129:680–6. doi: 10.1093/jn/129.3.680. [DOI] [PubMed] [Google Scholar]
  • 18.Cassell JA, Leach M, Fairhead JR, Small M, Mercer CH. The social shaping of childhood vaccination practice in rural and urban Gambia. Health Policy Plan. 2006;21:373–91. doi: 10.1093/heapol/czl020. [DOI] [PubMed] [Google Scholar]
  • 19.Households U-KM. Kinship and access to reproductive health care among rural Muslim women in Jaipur. Econ Pol Wkly (Mumbai, India) 1999;34:10. [Google Scholar]
  • 20.Fantahun M, Berhane Y, Wall S, Byass P, Hogberg U. Women’s involvement in household decision-making and strengthening social capital-crucial factors for child survival in Ethiopia. Acta Paediatr. 2007;96:582–9. doi: 10.1111/j.1651-2227.2007.00147.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Armstrong Schellenberg JR, Nathan R, Abdulla S, Mukasa O, Marchant TJ, Tanner M, et al. Risk factors for child mortality in rural Tanzania. Trop Med Int Health. 2002;7:506–11. doi: 10.1046/j.1365-3156.2002.00888.x. [DOI] [PubMed] [Google Scholar]
  • 22.Binka FN, Maude GH, Gyapong M, Ross DA, Smith PG. Risk factors for child mortality in northern Ghana: a case-control study. Int J Epidemiol. 1995;24:127–35. doi: 10.1093/ije/24.1.127. [DOI] [PubMed] [Google Scholar]
  • 23.Pickering H, Hayes RJ, Ng’andu N, Smith PG. Social and environmental factors associated with the risk of child mortality in a periurban community in The Gambia. Trans R Soc Trop Med Hyg. 1986;80:311–6. doi: 10.1016/0035-9203(86)90045-3. [DOI] [PubMed] [Google Scholar]
  • 24.Shier RP, Dollimore N, Ross DA, Binka FN, Quigley M, Smith PG. Drinking water sources, mortality and diarrhoea morbidity among young children in northern Ghana. Trop Med Int Health. 1996;1:334–41. doi: 10.1046/j.1365-3156.1996.d01-55.x. [DOI] [PubMed] [Google Scholar]
  • 25.Maldonado G, Greenland S. Simulation study of confounder-selection strategies. Am J Epidemiol. 1993;138:923–36. doi: 10.1093/oxfordjournals.aje.a116813. [DOI] [PubMed] [Google Scholar]
  • 26.Holtz TH, Kachur SP, Marum LH, Mkandala C, Chizani N, Roberts JM, et al. Care seeking behaviour and treatment of febrile illness in children aged less than five years: a household survey in Blantyre District, Malawi. Trans R Soc Trop Med Hyg. 2003;97:491–7. doi: 10.1016/S0035-9203(03)80003-2. [DOI] [PubMed] [Google Scholar]
  • 27.Fosu GB. Childhood morbidity and health services utilization: cross-national comparisons of user-related factors from DHS data. Soc Sci Med. 1994;38:1209–20. doi: 10.1016/0277-9536(94)90186-4. [DOI] [PubMed] [Google Scholar]
  • 28.Hill Z, Kendall C, Arthur P, Kirkwood B, Adjei E. Recognizing childhood illnesses and their traditional explanations: exploring options for care-seeking interventions in the context of the IMCI strategy in rural Ghana. Trop Med Int Health. 2003;8:668–76. doi: 10.1046/j.1365-3156.2003.01058.x. [DOI] [PubMed] [Google Scholar]
  • 29.Mtango FD, Neuvians D, Broome CV, Hightower AW, Pio A. Risk factors for deaths in children under 5 years old in Bagamoyo district, Tanzania. Trop Med Parasitol. 1992;43:229–33. [PubMed] [Google Scholar]
  • 30.Ensor T, San PB. Access and payment for health care: the poor of Northern Vietnam. Int J Health Plann Manage. 1996;11:69–83. doi: 10.1002/(SICI)1099-1751(199601)11:1&#x0003c;69::AID-HPM414&#x0003e;3.0.CO;2-P. [DOI] [PubMed] [Google Scholar]
  • 31.Reyes H, Perez-Cuevas R, Salmeron J, Tome P, Guiscafre H, Gutierrez G. Infant mortality due to acute respiratory infections: the influence of primary care processes. Health Policy Plan. 1997;12:214–23. doi: 10.1093/heapol/12.3.214. [DOI] [PubMed] [Google Scholar]
  • 32.Velema JP, Alihonou EM, Gandaho T, Hounye FH. Childhood mortality among users and non-users of primary health care in a rural west African community. Int J Epidemiol. 1991;20:474–9. doi: 10.1093/ije/20.2.474. [DOI] [PubMed] [Google Scholar]
  • 33.Greenwood BM, Greenwood AM, Bradley AK, Tulloch S, Hayes R, Oldfield FS. Deaths in infancy and early childhood in a well-vaccinated, rural, West African population. Ann Trop Paediatr. 1987;7:91–9. doi: 10.1080/02724936.1987.11748482. [DOI] [PubMed] [Google Scholar]
  • 34.Sodemann M, Jakobsen MS, Molbak K, Alvarenga IC, Jr, Aaby P. High mortality despite good care-seeking behaviour: a community study of childhood deaths in Guinea-Bissau. Bull World Health Organ. 1997;75:205–12. [PMC free article] [PubMed] [Google Scholar]
  • 35.Pronyk PM, Hargreaves JR, Morduch J. Microfinance programs and better health: prospects for sub-Saharan Africa. JAMA. 2007;298:1925–7. doi: 10.1001/jama.298.16.1925. [DOI] [PubMed] [Google Scholar]

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