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

Table 7 Models for limited decision-making agency. Binomial logistic regression: odds ratios with 95% confidence intervals and goodness of fit statistics^a

Dependent variable: male decision-making (yes, n = 114, no, n = 814)	M0	M1	M2
*Socioeconomic characteristics and caste*
Education (ref = high school+) Primary		1.23 [0.72–2.11]	1.22 [0.71–2.09]
No education		0.73 [0.39–1.34]	0.72 [0.38–1.33]
Employment (ref = not engaged) Engaged		0.45 [0.25–0.81]	0.44 [0.24–0.79]
Landholdings (ref = more than 50 cents) 50 cents or less		0.89 [0.53–1.50]	0.90 [0.53–1.52]
Caste of head (ref = forward) OBC		1.01 [0.57–1.79]	0.96 [0.54–1.72]
SC/ST		1.35 [0.76–2.40]	1.31 [0.74–2.34]
*SHG participation*
SHG (ref = not member) Early joiner (> 2 years)	1.00 [0.58–1.74]		0.90 [0.53–1.74]
Late joiner (< = 2 years)	0.71 [0.46–1.10]		0.62 [0.39–0.97]
Chi square (df) -2 log likelihood	2.8(2) 688.7	51.3(9)*** 640.2	56.5(11)*** 635.0
Deviation		10.4(2)**

^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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