Background
More than ten million children under five years die every year [
1]. Most of these deaths are in developing countries and roughly two-thirds could be prevented by interventions that are already available. The leading causes of these deaths are malaria, pneumonia, respiratory infections and deaths during the neonatal period due to pre-term birth, infections, and birth asphyxia. Malnutrition is the most common underlying cause of child deaths. These hard facts continue to shock, and have led to calls for action to prevent child deaths and reduce inequities in child survival [
2,
3]. The Millennium Development Goal (MDG) for child survival is intended to encourage national governments to focus both policies and finances on child health issues, but progress in sub-Saharan Africa is trailing behind that in other parts of the world [
4].
Why are life-saving interventions not reaching poor mothers and children? Interventions need a delivery system and health systems are often weakest where child mortality is highest [
5]. New interventions and initiatives are often developed with little attention given to how they would be delivered, particularly to the poorest or most marginalised groups, and with relatively little investment directed at the health system itself [
6,
7]. An analysis of current funding priorities for research to address the leading causes of death in children showed that the National Institutes of Health and the Bill and Melinda Gates Foundation allocated 97% of funding for research to develop better technologies and just 3% for delivering interventions to those who need them [
8].
Although it is no great surprise that poorer children are more likely than their better-off peers to be exposed to health risks [
9], action to redress these inequities has been slow. Not only does poverty lead to conditions that increase exposure and reduce resistance to infection, but also poorer children tend to have worse care-seeking for both curative and preventive services than those who are better-off; and the chances of getting the preventive and curative interventions they need are also worse [
6]. The "equity lens" approach of analyzing child health indicators by socio-economic status, sex or ethnicity, to look at inequalities in child health issues, can reveal gaps in coverage in certain groups that cannot be redressed without policy change [
10,
11]. In particular, universal coverage is only possible if the poorest children are reached.
Tanzania, with a population over 36 million people, is one of the poorest countries in the world [
12]. Recent trends in infant survival are encouraging, with a drop in infant mortality rate (IMR) from 99 in 1994–9 to 68 in 2000–2004 [
13]. National figures, however, obscure local variations: in the 20 regions of the country infant mortality varies widely with estimates for 1999 ranging from 41 per 1000 live births for Arusha Region to 129 for Lindi Region in 1999 [
12]. The health system has broader reach than in many sub-Saharan African countries, with one health facility for every 9,000 people. Health sector and local government reform is ongoing, and local councils have increased autonomy and control over their own health budgets and plans. The Ministry of Health and development partners (at the time of this study, the World Bank and the Governments of Denmark, Ireland, the Netherlands, Norway, Switzerland and the UK) pool resources in a common "basket" from which funds are then directly disbursed to districts through special accounts of the Council Health Management Teams. A limited amount of this donor-supported "basket" funding from the health Sector-Wide Approach is therefore available for local councils to implement their own plans. Nationally, spending on health is estimated to be $11.34 per capita, of which almost half is contributed by households [
14].
In Tanzania, as in many developing countries, vital registration and routine health information are incomplete. Cross-sectional household surveys are often used to estimate levels and trends in mortality, morbidity and intervention coverage from the community perspective. More rarely, cross-sectional health facility surveys are used to assess aspects of the structure and function of the health system, including quality of care. As an example, consider a poor rural family who happen to live close to a peripheral dispensary. They may take their children to this clinic for vaccination, but unless effective drugs and trained well-motivated staff are also there when they are sick, they will not receive the interventions they need. Large-scale linked data from both household and health facility perspectives provide an opportunity to study the health delivery system in parallel with health and social issues at community level.
The aim of this paper is to provide a comprehensive description of a rural malaria endemic area, including the health systems context, in which integrated malaria control strategies can be implemented and tested for community effectiveness and equity effectiveness. We present information on health in children under two years and on infant survival from both household and health facility perspectives, using information from a 21,000-household survey in five districts of southern Tanzania and a census of health facilities serving this population. We assess evidence of inequalities by sex, ethnic group, socio-economic status and distance to health service providers. Describing differentials in intervention coverage and infant mortality is important because reducing inequalities in health has been singled out as the major challenge to be addressed in order to improve global health [
15]. Of particular relevance is the finding that interventions for promoting child health may in fact increase inequalities before they reduce them [
16]. The surveys were part of the baseline work of an effectiveness study of Intermittent Preventive Treatment for malaria in infants (IPTi), within the IPTi Consortium [
17].
Results
During the household survey in July and August 2004 we visited 21,474 households in 720 clusters. In 497 households (2%) no-one was present to give consent and in a further 91 (0.4%) the household head was not willing to participate. Characteristics of the remaining 20,886 households are shown in Table
1. Mean household size was 3.9 people and one-fifth of all households had more than six residents. Makonde and Mwera were the most common ethnic groups, with over 80% of all household heads coming from these two groups. The majority of household heads were male (76%). The median distance to the nearest health facility was 3.2 km with an inter-quartile range from 0.8 km to 5.2 km.
Table 1
Distribution of the households and women studied: demographic, outcome of pregnancy and antenatal care (source: household survey)
| 4–5 | 7,346 | 35% |
| 6 and over | 4,144 | 20% |
Ethnic group of household head* | Makonde | 8,828 | 42% |
| Mwera | 8,518 | 41% |
| Yao | 1,009 | 5% |
| Other | 2,530 | 12% |
Sex of household head | Male | 15,794 | 76% |
| Female | 5,092 | 24% |
Distance to nearest health facility** | Under 5 km | 14,183 | 71% |
| 5 km and over | 5,712 | 29% |
Women aged 15–49 years | Total resident | 19,935 | |
| Interviewed | 19,007 | 95% |
| Gave birth in previous 3 years | 7,413 | 39% |
Experience of at least one child (under 5 years) death | Yes | 7,157 | 38% |
| No | 11,850 | 62% |
Place of delivery for the most recent birth | Health Facility | 4,029 | 39% |
| Elsewhere | 6,255 | 61% |
Antenatal clinic use in most recent pregnancy§
| Yes | 2,431 | 88% |
| No | 345 | 12% |
IPTp in most recent pregnancy§
| Yes | 1,662 | 60% |
| No | 1,114 | 40% |
Net last night in current pregnancy§§
| Yes | 271 | 25% |
| No | 800 | 75% |
Ever-treated net last night in current pregnancy§§
| Yes | 92 | 9% |
| No | 979 | 91% |
We attempted to interview all 19,935 women aged 15–49 years living in these households (Table
1). About one-quarter had no formal education (28%), but of those who had been to school most had completed primary education (73%). We did a birth history interview with 19,007 (95%) of the women, and found that 38% had experienced at least one child death. Only 39% of the most recent births took place in a health facility, with the majority taking place at home. Nevertheless, antenatal clinic attendance was very common, with 88% of women having attended clinic during their most recent (completed) pregnancy. Sixty percent of the women said they had taken one or more doses of antimalarials as Intermittent Preventive Treatment of malaria in pregnancy (IPTp), although only 42% recalled that they had been given sulphadoxine-pyrimethamine (SP) as IPTp. We asked women who said they were pregnant at the time of the survey whether they had slept under a mosquito net the previous night, and if so whether it was treated. One-quarter of pregnant women (25%) said they had used a net the previous night and just 9% had used a net ever treated with insecticide.
A summary of the assets owned by households in each quintile of the socio-economic status score from principal components analysis is shown in Table
2. Typically, a household in the poorest quintile would have no bicycle, radio, or poultry, and would have a thatched roof. A typical household in the least poor quintile would own a bicycle and radio, a few chickens or ducks, and a tin roof.
Table 2
Asset ownership for households in each socio-economic status quintile (source: household survey)
Most poor | 4,419 | 21% | -1.354 | 0% | 0% | 0% | 100% | 0% | 9% | 0% | 0% |
Very poor | 4,622 | 22% | -0.875 | 0% | 13% | 21% | 100% | 11% | 62% | 0% | 0% |
Poor | 3,341 | 16% | -0.272 | 9% | 30% | 37% | 100% | 13% | 75% | 0% | 21% |
Less poor | 4,121 | 20% | 0.486 | 6% | 72% | 74% | 99% | 18% | 65% | 0% | 21% |
Least poor | 4,125 | 20% | 2.164 | 15% | 83% | 87% | 82% | 37% | 78% | 4% | 70% |
All
|
20,628
|
100%
| |
6% |
39% |
43% |
96% |
16% |
57% |
1% |
22% |
| | |
Factor loadings
|
0.22
|
0.42
|
0.43
|
0.38
|
0.26
|
0.28
|
0.32
|
0.45
|
Availability of staff, vaccines and drugs on a single day in October 2004 in the health facilities serving this population is shown in Table
3. Of 118 facilities supplying vaccination services, 77% had Bacille Calmette-Guerrin (BCG), Diptheria-Pertussis-Tetanus-Hepatitis B (DPT-HepB), oral polio vaccine (OPV), measles and tetanus toxoid (TT) vaccine in stock and almost all (97%) had a fridge. However, as a rough indication of how effective the fridges were, only about half of all facilities had a fridge that would freeze water (54%). Most of the 134 facilities providing treatment services had oral rehydration solution (ORS) (93%) and SP (93%) in stock and slightly fewer had co-trimoxazole (73%). Less than half (42%,) had all seven 'essential oral treatments' available, ie. ORS, SP, co-trimaxazole, vitamin A, ferrous sulphate, paracetamol and mebendazole. Water was only available in 22% of the facilities. Injectable treatment for pre-referral care was available in roughly half of both dispensaries and health centres (52% and 43% respectively). We assessed human resources at health centres and dispensaries in terms of qualified prescribers and nurses. Only three-quarters of dispensaries had at least one prescriber and a similar proportion had at least one nurse (75% and 76% respectively). Furthermore, absenteeism was common in both nursing and prescribing cadres: only about 40% of dispensaries had a prescriber or a nurse present on the day of the survey (41% and 43% respectively). The most common reasons for absence were official travel (including meetings and seminars), leave and long-term training. Most facilities had received a supervision visit in the 6 months prior to the survey (84%, 112/134) but only a few recalled supervision visits including observation of case-management (17%, 23/134). (It should be noted that some under-reporting of this issue is possible: on a few occasions the interviewee was not the person in-charge of the facility and they may not have been present during all supervision visits.) Transport for referral care was rarely available, either by bicycle or ambulance (16%, 21/134), and one-quarter of those in-charge of a health facility said that they had wanted to refer a sick child at some point but had been unable to (25%, 34/134).
Table 3
Availability of staff, vaccines and drugs in health facilities on a single day in October 2004 (source: health facility survey)
All essential vaccines available (BCG, DPT-HepB, OPV, Measles, TT) | 91/118 | 77% | 68,84 |
Fridge | | Available | 115/118 | 97% | 93,99 |
| | Available & freezes | 64/118 | 54% | 45,63 |
ORAL AND INJECTABLE DRUGS (in all 134 facilities) |
Essential oral treatments available (ORS, SP, co-trimoxazole, vitamin A, ferrous sulphate, paracetamol, mebendazole) (SP was the first-line antimalarial drug at the time of the survey) | All available | 57/134 | 42% | 34,51 |
| | ORS | 125/134 | 93% | 88,97 |
| | SP | 124/134 | 93% | 87,96 |
| | Co-trimoxazole | 98/134 | 73% | 65,80 |
Water available | 30/134 | 22% | 16,30 |
Injectable treatment for pre-referral care (quinine, gentamicin or ampicillin or chloramphenicol, benzylpenicillin or cristapen or PPF (procaine penillin)) | In dispensaries | 59/113 | 52% | 43,62 |
| | In health centres | 6/14 | 43% | 18,71 |
HUMAN RESOURCES (in all 127 health centres & dispensaries) |
Prescribers (Medical Officers, Assistant Medical Officer, Clinical Officer or Assistant Clinical Officer) | Dispensaries | Present | 46/113 | 41% | 32,50 |
| | Employed | 85/113 | 75% | 66,83 |
| Health Centres | Present | 8/14 | 57% | 29,82 |
| | Employed | 12/14 | 86% | 57,98 |
Nurses (Nursing Officer, Nurse Midwife, Public Health Nurse 'B' or Maternal and Child Health Aides) | Dispensaries | Present | 49/113 | 43% | 34,53 |
| | Employed | 86/113 | 76% | 67,84 |
| Health Centres | Present | 11/14 | 79% | 49,95 |
| | Employed | 13/14 | 93% | 66,100 |
SUPERVISION & REFERRAL (in all 134 facilities) |
At least one supervision visit in previous 6 months | 112/134 | 84% | 76,89 |
At least one supervision involving case-management observation in previous 6 months | 23/134 | 17% | 11,25 |
Transport for referral (bicycle or ambulance) | 21/134 | 16% | 10,23 |
Has the in-charge ever wanted to refer a sick child but been unable to? | 34/134 | 25% | 18,34 |
During the household survey we interviewed mothers of all 1,414 children under two years about preventive care and recent illness in a randomly selected sub-group of 27% of households (192 clusters out of 720). Vaccine coverage was high, with 80–90% of all children aged 12–23 months having received BCG, three doses of DPT, and at least three doses of OPV before one year of age (Table
4). Measles vaccine coverage was slightly lower at 69%. Almost one-third of children had slept under a mosquito net the night before the survey (30%) but most of these nets were untreated. This is a conservative estimate because net use is likely to be a few percentage points higher in the rainy season, when mosquito densities are higher (unpublished observations). Only about one in ten children used a net that had ever been treated with insecticide (11%) or one which had been treated in the last year (9%). Malaria parasitaemia due to
P falciparum was found in 62% of children under two years and severe anaemia (Hb < 8 g/dL) in 31%. Almost half of all children had been ill in the two weeks before the survey (48%), and of those who had been ill almost half had sought care from a so-called "Western-style" care provider such as a hospital, health centre, or dispensary (46%). Roughly one in every 6 children had been admitted to a health centre or hospital for care in the year before the survey (16%), with malaria being the most common reported primary cause (52%) followed by diarrhoea (15%), pneumonia and anaemia (11% each). Exclusive breastfeeding in children under six months of age was reported in only one-quarter of children (24%). Roughly one-third of all under-two-year-olds were underweight, with a weight-for-age z-score of minus 2 or lower (32%).
Table 4
Preventive care and recent illness in children under two years (source: household survey)
VACCINE COVERAGE & VITAMIN A (in children aged 12–23 months) |
BCG before 12 months of age | 647/724 | 89% |
DPT-HepB3 before 12 months of age | 588/724 | 81% |
OPV3 before 12 months of age | 657/724 | 91% |
Measles before 12 months of age | 496/724 | 69% |
Vitamin A in previous 6 months | 500/710 | 70% |
MOSQUITO NETS (in children aged 0–23 months) |
Slept under a net last night | 417/1,401 | 30% |
Slept under a treated net last night | 159/1,401 | 11% |
Slept under a recently-treated net last night | 125/1,401 | 9% |
MALARIA AND ANAEMIA (in children aged 0–23 months) |
Malaria parasitaemia | 780/1,254 | 62% |
Severe anaemia (Hb < 8 g/dL) | 384/1,256 | 31% |
RECENT ILLNESS AND CARE-SEEKING (in children aged 0–23 months) |
Illness in the last two weeks | 674/1,410 | 48% |
Sought care from a Western-style health care provider (hospital, health centre, dispensary etc) | 309/674 | 46% |
Admissions in the previous year | 227/1,414 | 16% |
NUTRITION |
Exclusive breastfeeding in children under 6 months old | 79/332 | 24% |
Underweight (weight-for-age z-score under -2) in children 0–23 months old | 400/1,243 | 32% |
We looked for inequalities in indicators of preventive care and recent illness by sex, ethnic group of the household head, household socio-economic status and distance from health facilities. We found little evidence of inequalities by sex, although admissions in the previous year were slightly more common in boys than girls (19% vs 13%, p = 0.008, Table
5). Children living in Makonde-headed households were less likely to be anaemic and to be underweight than those in other groups (Table
6: 25% vs 34%–37% for severe anaemia, p = 0.007; 29% vs 37% for underweight, p = 0.04). Coverage of all vaccines was 10% to 20% lower in the poorest households than in the least poor, with the trend of lower coverage in poorer children reaching statistical significance for DPT-HepB3 and measles vaccine (Table
7: ratio of poorest to least poor 0.8 – 0.9, p for trend < 0.05). Mosquito net use was 70% to 80% lower in the poorest children than in the least poor, for both treated and untreated nets (ratio of poorest to least poor 0.2 – 0.3, p for trend < 0.0001). Malaria parasitaemia was more common in the poorest children compared to the least poor (68% in poorest compared with 50% in least poor, ratio 1.4, p for trend < 0.0001). There was an even more marked inequality for severe anaemia (Hb < 8 g/dL), which was found in 46% of the poorest children but only in 21% of the least poor (ratio 2.2, p for trend < 0.0001). In contrast, there was little evidence of inequality in recent illness, care-seeking or admissions in the previous year by socio-economic status. Exclusive breastfeeding in children under 6 months was almost twice as common in the poorest children compared to the least poor, with the trend not quite reaching statistical significance (p for trend = 0.09, ratio poorest to least poor 1.8). Underweight (weight-for-age z-score < -2) was 1.7 times more common in the poorest children compared to the least poor (P for trend = 0.001). Inequalities by distance from the nearest health facility were also apparent: coverage of all vaccines was 5 to 11 percentage points lower in households further than 5 km from their nearest facility than in those living closer (Table
8: p < 0.05). Mosquito net use was also more common in children living closer to health facilities (33% for those living under 5 km away and 25% in others: p = 0.05). Although illness in the last two weeks was equally common in those living nearer and further from a health facility, appropriate care-seeking was more common in those living closer to health facilities (51% and 37%, p = 0.002). Despite this, admissions in the previous year showed no disparity by distance from the nearest health facility (15% and 14%, p = 0.62).
Table 5
Inequalities by sex in preventive care and illness in children under two years (source: household survey)
VACCINE COVERAGE & VITAMIN A (in children aged 12–23 months) |
BCG before 12 months of age | 647/724 | 88% | 91% | 0.17 |
DPT-HepB3 before 12 months of age | 588/724 | 82% | 80% | 0.37 |
OPV3 before 12 months of age | 657/724 | 90% | 92% | 0.40 |
Measles before 12 months of age | 496/724 | 66% | 71% | 0.19 |
Vitamin A in previous 6 months | 500/710 | 71% | 70% | 0.87 |
MOSQUITO NETS (in children aged 0–23 months) |
Slept under a net last night | 417/1,401 | 32% | 28% | 0.11 |
Slept under a treated net last night | 159/1,401 | 13% | 10% | 0.19 |
Slept under a recently-treated net last night | 125/1,401 | 11% | 7% | 0.03 |
MALARIA AND ANAEMIA (in children aged 0–23 months) |
Malaria parasitaemia | 780/1,254 | 62% | 62% | 0.90 |
Severe anaemia (Hb < 8 g/dL) | 384/1,256 | 67% | 72% | 0.07 |
RECENT ILLNESS AND CARE-SEEKING (in children aged 0–23 months) |
Illness in the last two weeks | 674/1,410 | 49% | 47% | 0.53 |
Sought care from a Western-style health care provider (hospital, health centre, dispensary etc) | 309/674 | 44% | 48% | 0.28 |
Admissions in the previous year | 227/1,414 | 19% | 13% | 0.008 |
NUTRITION
|
Exclusive breastfeeding in children under 6 months old | 79/332 | 23% | 25% | 0.68 |
Underweight (weight-for-age z-score under -2) in children 0–23 months old | 400/1,243 | 34% | 31% | 0.32 |
Table 6
Inequalities by ethnic group in preventive care and illness in children under two years (source: household survey)
VACCINE COVERAGE & VITAMIN A (in children aged 12–23 months) |
BCG before 12 months of age | 644/721 | 92% | 86% | 92% | 89% | 0.19 |
DPT-HepB3 before 12 months of age | 586/721 | 84% | 79% | 88% | 77% | 0.24 |
OPV3 before 12 months of age | 654/721 | 90% | 91% | 88% | 90% | 0.96 |
Measles before 12 months of age | 496/721 | 71% | 67% | 65% | 68% | 0.61 |
Vitamin A in previous 6 months | 499/707 | 74% | 67% | 68% | 68% | 0.35 |
MOSQUITO NETS (in children aged 0–23 months) |
Slept under a net last night | 415/1,395 | 28% | 28% | 35% | 39% | 0.07 |
Slept under a treated net last night | 159/1,395 | 12% | 9% | 10% | 16% | 0.19 |
Slept under a recently-treated net last night | 125/1,395 | 10% | 7% | 6% | 12% | 0.19 |
MALARIA AND ANAEMIA (in children aged 0–23 months) |
Malaria parasitaemia | 779/1,249 | 61% | 62% | 65% | 65% | 0.82 |
Severe anaemia (Hb < 8 g/dL) | 383/1,251 | 25% | 34% | 37% | 37% | 0.007 |
RECENT ILLNESS AND CARE-SEEKING (in children aged 0–23 months) |
Illness in the last two weeks | 673/1,404 | 44% | 51% | 58% | 49% | 0.07 |
Sought care from a Western-style health care provider (hospital, health centre, dispensary etc) | 308/673 | 42% | 47% | 71% | 45% | 0.02 |
Admissions in the previous year | 226/1,408 | 17% | 15% | 17% | 16% | 0.41 |
NUTRITION
|
Exclusive breastfeeding in children under 6 months old | 78/330 | 30% | 20% | 9% | 21% | 0.11 |
Underweight (weight-for-age z-score under -2) in children 0–23 months old | 398/1,238 | 29% | 37% | 37% | 27% | 0.04 |
Table 7
Inequalities by socio-economic status in preventive care and illness in children under two years (source: household survey)
VACCINE COVERAGE & VITAMIN A (in children aged 12–23 months) |
BCG before 12 months of age | 642/719 | 84 | 89 | 93 | 88 | 92 | 0.9 | 0.15 |
DPT-HepB3 before 12 months of age | 584/719 | 76 | 79 | 86 | 75 | 90 | 0.8 | 0.03 |
OPV3 before 12 months of age | 652/719 | 87 | 90 | 94 | 90 | 92 | 0.9 | 0.25 |
Measles before 12 months of age | 495/719 | 61 | 68 | 68 | 71 | 74 | 0.8 | 0.02 |
Vitamin A in previous 6 months | 499/705 | 67 | 64 | 75 | 72 | 76 | 0.9 | 0.15 |
MOSQUITO NETS (in children aged 0–23 months) |
Slept under a net last night | 413/1,389 | 16 | 21 | 28 | 29 | 50 | 0.3 | <0.0001 |
Slept under a treated net last night | 159/1,389 | 4 | 5 | 11 | 10 | 25 | 0.2 | <0.0001 |
Slept under a recently-treated net last night | 125/1,389 | 3 | 4 | 6 | 9 | 20 | 0.2 | <0.0001 |
MALARIA AND ANAEMIA (in children aged 0–23 months) |
Malaria parasitaemia | 778/1,244 | 68 | 67 | 68 | 64 | 50 | 1.4 | 0.0001 |
Severe anaemia (Hb < 8 g/dL) | 383/1,246 | 46 | 31 | 33 | 29 | 21 | 2.2 | <0.0001 |
RECENT ILLNESS AND CARE-SEEKING (in children aged 0–23 months) |
Illness in the last two weeks | 670/1,398 | 44 | 50 | 51 | 47 | 47 | 0.9 | 0.90 |
Sought care from a Western-style health care provider (hospital, health centre, dispensary etc) | 307/670 | 44 | 47 | 45 | 42 | 49 | 0.9 | 0.81 |
Admissions in the previous year | 226/1,402 | 20 | 13 | 13 | 18 | 17 | 1.2 | 0.77 |
NUTRITION |
Exclusive breastfeeding in children under 6 months old | 77/327 | 30 | 20 | 33 | 21 | 17 | 1.8 | 0.09 |
Underweight (weight-for-age z-score under -2) in children 0–23 months old | 397/1,233 | 43 | 32 | 30 | 35 | 25 | 1.7 | 0.001 |
Table 8
Inequalities by distance from the nearest health facility in preventive care and illness in children under two years (source: household survey)
VACCINE COVERAGE & VITAMIN A (in children aged 12–23 months) |
BCG before 12 months of age | 558/619 | 93 | 83 | 0.0001 |
DPT-HepB3 before 12 months of age | 567/619 | 93 | 88 | 0.04 |
OPV3 before 12 months of age | 507/619 | 85 | 76 | 0.02 |
Measles before 12 months of age | 429/619 | 73 | 62 | 0.01 |
Vitamin A in previous 6 months | 433/606 | 73 | 67 | 0.18 |
MOSQUITO NETS (in children aged 0–23 months) |
Slept under a net last night | 362/1,207 | 33 | 25 | 0.05 |
Slept under a treated net last night | 137/1,207 | 12 | 9 | 0.23 |
Slept under a recently-treated net last night | 105/1,207 | 10 | 6 | 0.06 |
MALARIA AND ANAEMIA (in children aged 0–23 months) |
Malaria parasitaemia | 671/1,082 | 60 | 66 | 0.11 |
Severe anaemia (Hb < 8 g/dL) | 334/1,083 | 29 | 35 | 0.06 |
RECENT ILLNESS AND CARE-SEEKING (in children aged 0–23 months) |
Illness in the last two weeks | 599/1,215 | 49 | 50 | 0.82 |
Sought care from a Western-style health care provider (hospital, health centre, dispensary etc) | 277/599 | 51 | 37 | 0.002 |
Admissions in the previous year | 182/1,219 | 15 | 14 | 0.62 |
NUTRITION
|
Exclusive breastfeeding in children under 6 months old | 70/290 | 25 | 23 | 0.69 |
Underweight (weight-for-age z-score under -2) in children 0–23 months old | 324/1,069 | 29 | 32 | 0.31 |
We elicited information about dates of birth, sex of the child, whether they were singleton or twin births, and the date of death for any child who had died of the 7,413 women (39%) who gave birth in the three years prior to the survey, in order to estimate infant survival rates from July 2001 – June 2004. Neonatal mortality per 1000 live births was 43.2 (336/7,779) and infant mortality per 1000 live births was 76.4 (594/7,779). We also calculated infant mortality rates per 1000 per year and looked for trends in this indicator over time and differentials by other factors. Between July 2001 and June 2004 the infant mortality rate per 1000 per year was 82.5 (CI 75.6 – 90.1), and there was no evidence that it had changed over this time period (Table
9, P = 0.72). Infant mortality was almost 40% higher for teenage mothers than for older women (rate ratio (RR) 1.37, CI 1.1 – 1.7, p = 0.005), and 20% higher for mothers who had no formal education (RR 1.2, CI 1.0 – 1.4, p = 0.004). Boys and girls had similar infant mortality rates (RR 1.03, p = 0.70) and rates were also similar in male-headed and female-headed households (RR 0.93, p = 0.48). Twins had more than four times the infant mortality rate of singleton births (RR 4.59, CI 3.4 – 6.2, p < 0.0001). Neonatal mortality per 1000 child-years was more than ten times the mortality rate in children aged 1–11 months (RR = 15.1, p < 0.0001). There was some evidence of differences in infant mortality by ethnic group, with the rate in Makonde being 71.5 per 1000 CYAR and that in the Mwera and in the combined other ethnic groups being 20 to 50% higher (RR for Mwera = 1.2, RR for others = 1.5, compared with Makonde, P = 0.01). There was no evidence of inequality in infant mortality by socio-economic status (84.4/1000 child-years-at-risk (CYAR) in the poorest and 79.3/1000 CYAR in the least poor quintiles, RR = 0.94, P for trend = 0.90). However, there was evidence that infant mortality rates were higher in those living more than 5 km from the health facility compared to those living closer (95.1/1000 CYAR and 76.0/1000 CYAR respectively, RR = 1.25, P = 0.02).
Table 9
Differentials in infant mortality rates (source: household survey)
Year (July–June) | 2001–2 | 184 | 2,218.8 | 82.9 | 1 | | 0.72 (for trend P = 0.75) |
| 2002–3 | 183 | 2,324.7 | 78.7 | 0.95 | 0.8 – 1.2 | |
| 2003–4 | 227 | 2,659.8 | 85.3 | 1.03 | 0.8 – 1.3 | |
Mother's age at delivery | 20–29 | 261 | 3,398.7 | 76.8 | 1 | | 0.005 |
| 30–39 | 124 | 1,702.2 | 72.8 | 0.95 | 0.8 – 1.2 | |
| 40–49 | 27 | 364.5 | 74.1 | 0.96 | 0.6 – 1.4 | |
| Under 20 | 181 | 1,718.8 | 105.3 | 1.37 | 1.1 – 1.7 | |
Mother's education | One or more years | 399 | 5,123.9 | 77.9 | 1 | | 0.038 |
| None | 194 | 2,063.6 | 94.0 | 1.21 | 1.0 – 1.4 | |
Sex | Girls | 287 | 3,537.7 | 81.1 | 1 | | 0.70 |
| Boys | 307 | 3,665.5 | 83.8 | 1.03 | 0.9 – 1.2 | |
Twins | Singleton | 518 | 6,980.1 | 74.2 | 1 | | <0.0001 |
| Twin | 76 | 223.2 | 340.5 | 4.59 | 3.4 – 6.2 | |
Age | 0–27 days | 337 | 574.2 | 586.9 | 1 | | <0.0001 |
| 28–365 days | 257 | 6,629.0 | 38.8 | 0.07 | 0.06 – 0.08 | |
Ethnic group of household head | Makonde | 220 | 3,075.8 | 71.5 | 1 | | 0.01 |
| Mwera | 246 | 2,867.3 | 85.8 | 1.20 | 1.0 – 1.4 | |
| Yao | 29 | 318.7 | 91.0 | 1.27 | 0.8 – 2.0 | |
| Other | 99 | 926.2 | 106.9 | 1.49 | 1.2 – 1.9 | |
Gender of household head | Male | 478 | 5,695.9 | 83.9 | 1 | | 0.48 |
| Female | 116 | 1,493.2 | 77.7 | 0.93 | 0.7 – 1.1 | |
SES quintile of household | Poorest | 109 | 1,291.1 | 84.4 | 1 | | 0.90 (test for trend) |
| Very poor | 122 | 1,577.9 | 77.3 | 0.92 | 0.7 – 1.2 | |
| Poor | 102 | 1,182.1 | 86.3 | 1.02 | 0.8 – 1.4 | |
| Less poor | 129 | 1,540.9 | 83.7 | 0.99 | 0.8 – 1.3 | |
| Least poor | 120 | 1,513.7 | 79.3 | 0.94 | 0.7 – 1.2 | |
Distance to nearest health facility | <5 km | 363 | 4,778.9 | 76.0 | 1 | | 0.02 |
| ≥ 5 km | 196 | 2,061.2 | 95.1 | 1.25 | 1.0 – 1.5 | |
Effect of child's age on the relationship between twinning and mortality:
|
Twins under 28 days (neonates) | Singleton | 280 | 556.6 | 503.0 | 1 | | <0.0001 |
| Twin | 57 | 17.6 | 3,242.6 | 6.45 | 4.5 – 9.2 | |
Twins over 28 days (1–11 m) | Singleton | 238 | 6,423.4 | 37.1 | 1 | | <0.0001 |
| Twin | 19 | 205.6 | 92.4 | 2.49 | 1.5 – 4.0 | |
Effect of child's age on the relationship between maternal education and mortality:
|
In neonates: Mother's education | ≥ 1 year | 238 | 407.4 | 584.3 | 1 | | 0.93 |
| None | 98 | 165.9 | 590.8 | 1.01 | 0.8 – 1.3 | |
In 1–11 month olds: Mother's education | ≥ 1 year | 161 | 4,716.7 | 34.1 | 1 | | 0.003 |
| None | 96 | 1,897.8 | 50.6 | 1.48 | 1.1 – 1.9 | |
Effect of distance from the health facility on the relationship between maternal education and mortality
|
In those living < 5 km from a health facility: mothers education | ≥ 1 year | 239 | 3,466. | 68.9 | 1 | | |
| None | 123 | 1,305.3 | 94.2 | 1.4 | 1.1 – 1.7 | 0.005 |
In those living ≥ 5 km from a health facility: mothers education | ≥ 1 year | 140 | 1,421.5 | 98.5 | 1 | | |
| None | 56 | 637.9 | 87.8 | 0.9 | 0.7 – 1.2 | 0.47 |
Of the tests for effect modification, three were statistically significant, (a) age and twinning, (b) age and mother's education, and (c) distance to the health facility and mother's education (p-value for interaction between age and twinning 0.002, between age and education 0.039, between distance and mother's education p = 0.03). These findings are explained in turn below.
Firstly, we found strong evidence that the neonatal period is particularly risky for twins, with the neonatal mortality rate for twins being over 6 times higher than that for singleton babies (RR = 6.45, CI 4.5 – 9.2, p < 0.0001). The mortality rate for twins aged 1–11 months was 2.5 times higher than that for singleton babies (RR = 2.49, CI 1.5 – 4.0, p = 0.0002).
Secondly, we found some evidence that the effect of maternal education was different in neonates and in older infants. Neonatal mortality was similar among mothers with no formal education and those who had studied (RR = 1.01, CI 0.8 – 1.3, p = 0.93), but the rate of mortality in the post-neonatal period (1–11 months of age) was about 1.5 times higher for those with no education than for mothers who had spent one or more years at school (RR = 1.48, CI 1.1 – 1.9, p = 0.003).
Thirdly, we found that the positive effect of maternal education was only apparent in families living less than 5 km from the health facility (RR = 1.4, CI 1.1 – 1.7, p = 0.005). For those living more than 5 km from the health facility there was no evidence of any association between maternal education and infant survival (RR = 0.9, CI 0.7 – 1.2, p = 0.47).
Discussion
Most current global health efforts, including those for malaria, HIV and vaccine-preventable diseases, need to deliver in the context of rural health systems like the one described here. By including a functional and structural assessment of the health system itself, it is possible to gain insights into why some interventions work while others do not. The "staircase effect" denotes the reduction in effect at the community level of an efficacious intervention due to factors such as coverage, availability and compliance [
21]. The size of the steps can differ between socio-economic groups: the poorest tend to have worse access, diagnosis, compliance and adherence, meaning that efficacious interventions do not result in equitable community effectiveness [
22,
23]. Delivery systems that reduce the gap between poorest and least poor are needed. The relatively short distances to health facilities, high antenatal care and good vaccine coverage suggest that peripheral health facilities have huge potential to make a difference to health and survival at the household level in rural Tanzania, even with current human resources. Nevertheless, drug shortages, staff absenteeism and water supply problems show that there is a long way to go before facilities are able to optimise the quality of care they provide.
This broad-based cross-sectional study includes both facility-based and household-based aspects of health and health care in a poor rural Tanzanian population. We had limited ability to reveal the reasons behind some of our findings. More in-depth research is needed to investigate why, for example, children born in households headed by Makonde are at lower risk of anaemia, malnutrition and infant death than those in households headed by other common ethnic groups. Although the Makonde are slightly less poor on average than other ethnic groups, the tendency for better infant survival among the Makonde was seen in all socio-economic status (SES) quintiles (data not shown). The Makonde are socially the deepest-rooted ethnic group in the area, and this may give them better social status and networks that influence well-being other than through better socio-economic status. In-depth qualitative work is ongoing that may explain what behaviours might be responsible for these findings. Furthermore, our analysis involved a large number of significance tests and thus findings should be treated with caution as it is possible that some results may be due to chance alone.
The health facility survey revealed particular problems with staff absence and drug stocks. Staff absences were common, with only about two-third of all employed staff present on the day of the survey. A group of seven essential oral treatments was found in less than half of all facilities. District-level health staff are responsible both for supportive supervision visits and drug supplies, and it seems that these aspects of their work are not prioritised. Referral is often difficult given large distances to referral centres and the lack of transport: the lack of pre-referral drugs, which may be given when referral is not possible, is of particular concern. Given the staff absences and drug shortfalls, and the fact that only about one-fifth of all facilities had a supply of clean water, it could be considered surprising that as many as 39% of women give birth in health facilities. In contrast, both childhood vaccine coverage and antenatal clinic attendance are almost universal, which means that universal coverage of preventive interventions may be an achievable goal.
We found that 38% of all women had personally experienced a child death. This is a stark illustration of how "ordinary" child deaths are in this area, as in much of sub-Saharan Africa: when a child dies, it is no great surprise. Infant and neonatal mortality rates are in keeping with findings from other sources [
12,
13] and although we found no evidence of a change from 2001–2004 our results are compatible with a drop in mortality around 1999–2001 [
13].
In keeping with previous studies our results show that infants born to teenage mothers are at particularly high risk, as are twins, and infants born to mothers with no formal education [
24,
25]. More surprisingly, perhaps, we found little evidence that neonatal mortality rates were associated with maternal education, in contrast to the post-neonatal period, when mortality rates were 50% higher for mothers with no formal education compared with those who had had at least one year of schooling. In the first few days of life newborn babies and their mothers are often confined indoors at home (M Mrisho, unpublished data): it is possible that this behaviour, together with a general lack of knowledge of how to prevent newborn deaths, is the reason for similar newborn survival among babies born to mothers who had, and had not, been to school.
We found that the neonatal period is especially risky for twins, who have over six times the mortality rate of single births. A similar pattern has been reported elsewhere: in studies conducted in Nepal and Bangladesh, the neonatal mortality rate was respectively 7 times and 15 times higher than for singleton babies [
26,
27].
We found some evidence of disparities in vaccination coverage by socio-economic status, with ratios of coverage in the poorest to least poor of 0.8 to 0.9, as reported elsewhere [
28]. We also found stark inequalities in the use of mosquito nets, parasitaemia and anaemia, similar to those found before a social marketing program for nets in another part of the country [
29]. Inequalities in underweight were also in keeping with a previous survey in another part of rural Tanzania (J Schellenberg unpublished data). However, we were surprised to find no evidence of socio-economic disparities in either care-seeking for mild illness, admission to hospital, or infant survival, in contrast to findings both nationally [
28] and locally [
6,
29‐
31]. This seems unlikely to be due to a lack of power as we had over 100 child deaths in each quintile. The most likely explanation is that the communities we studied are relatively homogeneous with regards to factors that influence care-seeking, such as knowledge, beliefs and means to travel.
Distance to health facilities has long been described as a barrier to their use [
32‐
36]. In our study, children living over 5 km from a health facility had lower vaccine coverage, fewer nets, more anaemia, poorer care-seeking and higher infant mortality than those living closer. This is despite the Tanzanian public health system which reaches to village level and is relatively well used for child illness: neighbouring Uganda, for example, has roughly twice the population per health facility and care-seeking for recent childhood illness is just 8% compared with 40% in Tanzania [
37,
38]. The Tanzanian advantage is that three-quarters of the population live within about 5 km of their nearest facility.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
The study was conceived & designed by JRMAS, MM, PLA, HM, MT and DS. Substantial contributions to acquisition of the data were made by JRMAS, MM, FM, KS, CM, AKM and DS. Initial analysis and interpretation of the data was done by JRMAS, MM, KS, SCK and DS. The manuscript was drafted by JRMAS and MM. All authors were involved in critical revision for important intellectual content and approved the final version of the manuscript.