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Table 3 Unadjusted and fully adjusted odds ratios of women’s circumcision across selected covariates (Senegal, DHS 2005 & 2010)

From: Trends in female genital mutilation/cutting in Senegal: what can we learn from successive household surveys in sub-Saharan African countries?

Variable

Women 2005

Women 2010-11

Unadjusted OR & 95%CIa

Fully adjusted POR & 95% CIb

Unadjusted OR & 95%CIa

Fully adjusted POR & 95% CIb

Age

 15–19 years

0.93(0.81, 1.07)

 

1.00(0.86,1.15)

 

 20–24 years

1.00(0.86, 1.15)

See Fig. 4 left

0.93(0.80,1.08)

 

 25–29 years

1.00

 

1.00

 

 30–34 years

1.08(0.92, 1.27)

 

0.94(0.80,1.10)

 

 35–39 years

1.08(0.91, 1.27)

 

1.12(0.95, 1.33)

 

 40–44 years

1.08(0.91, 1.29)

 

1.02(0.85, 1.23)

 

 45–49 years

1.09(0.90, 1.32)

 

1.08(0.88, 1.33)

 

Age Partner

 15–30 years

1.00

See Fig. 4 right

1.01(0.88,1.16)

 

 31–49 years

0.80

 

1.00

 

 50–60 years

0.82

 

0.98(0.86, 1.12)

 

  > 61 years

1.10

 

1.28(1.06, 1.54)

 

Place of residence

 Urban

1.00

1.00

1.00

1.00

 Rural

2.09(1.94, 2.25)

1.47(1.31, 1.65)

1.42(1.32, 1.53)

0.78(0.70, 0.87)

Married

 Yes

2.22(1.99, 2.47)

 

1.47(1.33, 1.63)

 

 No

1.00

 

1.00

 

Education

 No education

2.05(1.13, 3.70)

3.26(1.04, 10.1)

4.10(2.57, 6.53)

1.86(0.74, 4.65)

 Primary education

1.42(0.78, 2.57)

3.11(0.99, 9.73)

3.55(2.21, 5.68)

1.77(0.71, 4.45)

 Secondary educ.

0.93(0.51, 1.71)

2.41(0.76, 7.63)

2.87(1.79, 4.61)

1.62(0.64, 4.13)

 Higher education

1.00

1.00

1.00

1.00

Partner’s education

 No education

1.96(1.44, 2.68)

1.30(0.87, 1.93)

1.69(1.18, 2.43)

1.21(0.81, 1.80)

 Primary education

1.58(1.12, 2.22)

1.58(1.12, 2.22)

1.55(1.04, 2.30)

1.45(0.95, 2.21)

 Secondary educ.

1.33(0.94, 1.88)

1.33(0.94, 1.88)

1.48(0.98, 2.23)

1.43(0.92, 2.22)

 Higher education

1.00

1.00

1.00

1.00

Wealth Index

 Poorest

5.03(4.30, 5.88)

4.60(3.61, 5.86)

5.21(4.42, 6.14)

5.77(4.55, 7.33)

 Poorer

5.37(4.59, 6.29)

4.52(3.57, 5.72)

3.05(2.58, 3.60)

3.35(2.64, 4.27)

 Middle

3.42(2.92, 4.02)

2.44(1.94, 3.07)

2.22(1.87, 2.64)

2.16(1.70, 2.73)

 Richer

1.97(1.64, 2.37)

1.79(1.37, 2.33)

1.51(1.25, 1.83)

1.37(1.05, 1.79)

 Richest

1.00

1.00

1.00

1.00

Family size

 Small (1–4 children)

0.60(0.50, 0.73)

0.98(0.79, 1.23)

1.00

1.00

 Middle (5-7children)

0.66(0.53, 0.83)

0.90(0.70, 1.16)

1.22(1.08, 1.37)

1.16(1.00, 1.33)

 Large (8+ children)

1.00

1.00

1.46(1.19, 1.80)

1.11(0.88, 1.42)

Ethnicity

 Wolof

1.00

1.00

1.00

1.00

 Poular

1.79(1.67, 1.93)

23.9(20.1, 28.5)

129(98.6, 169)

19.9(16.9, 23.5)

 Serer

0.02(0.01, 0.03)

0.22(0.14, 0.36)

2.56(1.70, 3.85)

0.39(0.26, 0.60)

 Mandingu

2.96(2.36, 3.72)

67.3(45.4, 99.6)

478(326, 702)

89.4(55.5, 144)

 Diola

1.53(1.26, 1.87)

20.3(14.3, 28.6)

125(89.6, 174)

29.4(20.0, 43.3)

 Soninke

3.70(2.62, 5.21)

75.4(44.1, 129)

185(123, 280)

31.2(17.1, 56.6)

 Not Senegalese

2.49(1.69, 3.67)

33.9(20.6, 55.9)

168(107, 264)

24.8(15.4, 39.9)

 Other

0.64(0.54, 0.75)

11.2(8.41, 14.9)

50.1(36.8, 68.3)

9.22(6.88, 12.3)

Religion

 Muslim

3.54(2.70, 4.64)

3.02(2.11, 4.34)

4.10(2.92, 5.77)

2.52(1.61, 3.96)

 Other

1.00

1.00

1.00

1.00

Region of residence

 Dakar

0.22(0.19, 0.25)

 

0.26(0.23, 0.31)

 

 Diourbel

1.00

 

1.00

 

 Fatick

0.07(0.05, 0.08)

 

0.11(0.09, 0.13)

 

 Kaffrine

New state in 2010

 

0.12(0.10, 0.15)

 

 Kaolack

0.14(0.12, 0.16)

See Fig. 2

0.08(0.06, 0.10)

 

 Kédougou

New state in 2010

 

14.5(10.4, 20.4)

 

 Kolda

16.5(13.2, 20.6)

 

7.10(6.02, 8.39)

 

 Louga

0.05(0.04, 0.07)

 

0.05(0.04, 0.05)

 

 Matam

18.2(14.0, 23.7)

 

8.65(7.12, 10.5)

 

 Saint Louis

0.88(0.84, 0.93)

 

0.78(0.72, 0.85)

 

 Sédhiou

New state in 2010

 

8.29(6.90, 9.94)

 

 Tambacounda

6.98(5.95, 8.19)

 

7.32(6.20, 8.63)

 

 Thiès

0.08(0.07, 0.10)

 

0.04(0.03, 0.05)

 

 Ziguinchor

2.32(2.08, 2.58)

 

1.59(1.40, 1.80)

 
  1. aUnadjusted marginal odds ratio (OR) from standard logistic regression models.
  2. bAdjusted posterior odds ratio (POR) from Bayesian geo-additive regression models