Can microcredit help improve the health of poor women? Some findings from a cross-sectional study in Kerala, India

Table 5 Models for exclusion to health care. Binomial logistic regression: odds ratios with 95% confidence intervals and goodness of fit statistics^a

Dependent variable: exclusion to health care (yes, n = 325, no, n = 603)	M0	M1	M2
*Socioeconomic characteristics and caste*
Education (ref = high school+) Primary		0.92 [0.63–1.35]	0.90 [0.61–1.32]
No education		1.40 [0.96–2.05]	1.35 [0.91–1.99]
Employment (ref = not engaged) Engaged		0.82 [0.59–1.14]	0.81 [0.58–1.14]
Landholdings (ref = more than 50 cents) 50 cents or less		1.52 [1.05–2.20]	1.52 [1.05–2.21]
Caste of head (ref = forward) OBC		1.57 [1.06–2.34]	1.52 [1.02–2.27]
SC/ST		1.08 [0.72–1.63]	1.11 [0.73–1.68]
*SHG participation*
SHG (ref = not member) Early joiner (> 2 years)	0.56 [0.36–0.86]		0.60 [0.39–0.94]
Late joiner (< = 2 years)	0.57 [0.41–0.79]		0.58 [0.41–0.80]
(Not member but SHG in household)	(0.58) ([0.35–0.94])		(0.53) ([0.32–0.90])
Chi square (df) -2 log likelihood	13.3 (3)** 1188.6	24.3(9)** 1177.6	36.4(12)*** 1165.5
Deviation		24.2(3)***

^a Notes: Models are adjusted for age and women's household position. Results in bold are statistically significant, *p < 0.05, **p < 0.01, ***p < 0.001
OBC = Other Backward Caste, SC/ST = Scheduled Caste/Scheduled Tribe.

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