Bulletin of the World Health Organization

A systematic review of inequalities in the use of maternal health care in developing countries: examining the scale of the problem and the importance of context

Lale Say, Rosalind Raine

Volume 85, Number 10, October 2007, 812-819

Table 2. Inequalities in the use of medical settings for delivery

Study Country Sample size Comparison groups OR(95% CI orsignificance) Adjusted analysis donea Qualityb Contextual issuesc
Urban-rural variations
Addai (1998)
Ghana
4562
Urban, rural
1.76 (P < 0.01),1.00
+


Bhatia (1995)
India
3595
Urban, rural
2.57 (P < 0.01),1.00
+
+
Limited physical access to facilities for rural women. Self-reported hygiene emerged as a significant factor. Increasing importance of private sector due to poor reputation of government hospitals.
Bolam (1998)
Nepal
334
Urban, rural
0.90 (0.52–1.56), 1.00



Falkingham (2003)
Tajikistan
1982
Urban, rural
2.67 (1.76–4.08), 1.00
+
+
Deterioration of economy and health services since independence; rural women disproportionately affected.
Gertler (1993)
Jamaica
823
Urban, rural
Higher in urban (P < 0.01)
+
++
Accessibility (transport, work responsibilities) is limited for poor and rural women, and informal care alternatives exist. Midwives’ advice as to the place of delivery is not followed because of what some subjects call their authoritarian attitudes.
Hotchkiss (2003)
Morocco
1609
Urban, rural
2.13 (1.21–3.76), 1.00
+
+
Low geographical accessibility and costs of services limited use. Women living in households with another adult woman are more likely to give birth in hospitals because they can get advice and are accompanied to the hospital.
Magadi (2000)
Kenya
5290
Urban, rural
2.66 (P < 0.05),1.00
+


Navaneetham (2002)
India Andra Pradesh
1571
Urban, rural
2.21 (P < 0.01),1.00
+
+
Different patterns between states due to differential availability and accessibility of services. General lack of access for socially excluded (caste) communities because of residential segregation and limited availability of services.
Karnataka
1925
2.41 (P < 0.01),1.00
Kerala
1101
1.65 (NS),1.00
Tamil Nadu
1416
3.64 (P < 0.01),1.00
Stupp (1994)
Belize
977
Urban, rural
7.14 (P < 0.001),1.00
+


Tsui (2002) Paraguay
722
Urban, rural
NS
+


Uganda
1224
Higher in urban (P < 0.10)
United Republic of Tanzania
4055
Higher in urban (P < 0.10)

India
3165
NS
Economic variations
Anson (2004)
China
4273
Continuous
0.96 (NS)
+


Barbhuiya (2001)
Bangladesh
505
Lower, higher
1.00,2.43 (1.29–4.59)



Bhatia (1995)
India
3595
Low, middle, high
1.00,1.23 (P < 0.05),1.55 (P < 0.001)
+
+
Increasing importance of private sector and decreased functioning of public services. Those who cannot afford private care do not deliver at facilities. Differences by caste show segregation of some groups.
Duong (2004)
Viet Nam
200
Continuous
NS
+


Falkingham(2003)
Tajikistan
1840
Poorest,2nd quintile,3rd quintile,4th quintile,Richest
NS
+
+
Deterioration of economy and health services since independence; quality of care is very low. Women, particularly those who are wealthier, perceive giving birth at home as safer than in hospitals that lack running water or heating.
Gertler (1995)
Jamaica
823
Continuous
Higher with high (P < 0.01)
+
++
Accessibility (transport, work responsibilities) is limited for poor and rural women; informal care alternatives exist. Midwives’ advice as to the place of delivery is not followed because of what some subjects call their authoritarian attitudes.
Glei (1999)
Guatemala
3253
Continuous
1.00
+
+
Other factors (clinical risk, openness to outside world) in particular cultural differences between ethnic groups (for example, indigenous women prefer traditional midwives because of the social support they provide) determine maternal health-care use.
Hodgkin (1996)
Kenya
149
Continuous
Higher with high (P < 0.10)
+


Hotchkiss (2003)
Morocco
1609
Lower half,higher half
1.00,2.94 (1.45–6.04)
+
+
User fees limit access for poor people. Women living in households with another adult woman are more likely to give birth in hospitals, because they can get advice and are accompanied to the hospital.
Kavitha (1997)
India
172
1000,1001–2000,> 2000
NS
+


Navaneetham (2002)
India,Andra Pradesh
1571
Low, medium,high
1.00,1.40 (P < 0.05),3.37 (P < 0.01)
+
+
Different patterns between states due to differential availability and accessibility of services. General lack of access for socially excluded communities (caste) due to residential segregation and limited availability of services.
Karnataka
1925
1.00,1.72 (P < 0.01),3.61 (P < 0.01)
Kerala
1101
1.00,1.85 (P < 0.01),4.92 (P < 0.05)
Tamil Nadu
1416
1.00,1.33 (P < 0.01),3.91 (P < 0.01)
Toan (1996)
Viet Nam
1151
Not good,good
1.00,1.26 (0.97–1.63)



Tsui (2002)
Paraguay
722
Low, medium,high
Higher in high (P < 0.10)
+


United Republic of Tanzania
4055
Higher in high (P < 0.10)
India
3165
Higher in high (P < 0.10)
Van der Heuvel (1999)
Zimbabwe
235
Lower, low,middle
NS,NS
+


Wagle (2004)
Nepal
308
Low, high
4.4 (1.8–10.6)
+


Home delivery
Letamo (2003)
Botswana
1184
Low, medium,high
4.14 (3.45–4.96),1.28 (1.06–1.54),1.00
+


Magadi (2000) Kenya 5290 Low, medium,high 1.00,0.54 (P < 0.05),0.19 (P < 0.05) +

CI, confidence interval; NS, not significant; OR, odds ratio.a Includes a range of factors related to the individual (e.g. age, marital status, number of children, education, autonomy, health beliefs), community (e.g. type of roads, village) and health service (distance/time to care, availability of doctors), varying across studies.b Indicates how well the study was done to minimize the risk of bias or confounding, and to establish an association between exposure (examined non-clinical factor) and effect (outcome measure). Code: ++ high quality; + moderate quality; – low quality.c Contextual influences that could explain the differences found in studies of moderate and high quality.