Dear All,
I am interested to examine the effect of IPV (Intimate Partner Violence) on my proxy outcome measurement for skilled maternal health care utilisation (Dependent Variable 1 - adequate ANC visits (1) Vs. Inadequate ANC visits (0); and second outcome variable is – Health Facility Delivery (1) Vs. Home delivery (0)); whether it differ by mother education and household wealth status:
Outcome variable: (adequate ANC service (1) or inadequate ANC service (0)), and Health facility delivery (1) or Home delivery (0).
Main exposures: spousal emotional IPV (Yes/No or 1/0) and spousal Physical IPV (Yes/No or 1/0).
Stratified by: (Education status) - Lower education (1) & Higher education (2).
: (Household wealth Index) - Low wealth (1) & High (2).
All other my covariates are also categorical variables. I have fitted multilevel logistic regression because the data is clustered at the survey level.
Model I. Higher education stratified adjusted logistic regression
melogit del_place i.physical_viol1 i.age_catgorey i.husband_educ i.wealth_hh i.mediae_expo i.birth_order i.dma i.V102 i.contextual_r
> egions if educ_mom==2 || psu :,or nolog
Mixed-effects logistic regression Number of obs = 315
Group variable: psu Number of groups = 216
Obs per group:
min = 1
avg = 1.5
max = 4
Integration method: mvaghermite Integration pts. = 7
Wald chi2(15) = 21.39
Log likelihood = -90.381795 Prob > chi2 = 0.1249
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del_place | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
physical_viol1 |
Yes | .2491509 .1665459 -2.08 0.038 .0672161 .9235309
Model II. Lower education stratified adjusted logistic regression
melogit anc_adequacy i.emotional_viol1 i.age_catgorey i.husband_educ i.wealth_hh i.mediae_expo i.birth_order i.dma i.V102 i.contextu
> al_regions if educ_mom==1 || psu :,or nolog
Mixed-effects logistic regression Number of obs = 2,548
Group variable: psu Number of groups = 580
Obs per group:
min = 1
avg = 4.4
max = 12
Integration method: mvaghermite Integration pts. = 7
Wald chi2(15) = 160.53
Log likelihood = -1384.4603 Prob > chi2 = 0.0000
------------------------------------------------------------------------------------------------
anc_adequacy | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
emotional_viol1 |
Yes | .7386871 .0969893 -2.31 0.021 .5710815 .955483
Model III. Low wealth stratified adjusted logistic regression
melogit anc_adequacy i.emotional_viol1 i.age_catgorey i.educ_mom i.husband_educ i.mediae_expo i.birth_order i.dma i.V102 i.contextua
> l_regions if wealth_hh ==1 || psu :,or nolog
Mixed-effects logistic regression Number of obs = 1,929
Group variable: psu Number of groups = 443
Obs per group:
min = 1
avg = 4.4
max = 12
Integration method: mvaghermite Integration pts. = 7
Wald chi2(15) = 62.54
Log likelihood = -997.19729 Prob > chi2 = 0.0000
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anc_adequacy | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
emotional_viol1 |
Yes | .7088675 .1133807 -2.15 0.031 .518106 .9698655
N.B. the results of other covariates omitted.
So, in these models, the main effect of IPV on the outcome variables are quite weak. and we can see that the confidence interval for the association between IPV and both outcomes is so broad while stratified by education and wealth subgroup.
Could anyone can give me something that I should also consider in those models? why the CI are so wide and the main effects quite week, too?
Thank you so much in advance for your quick response.
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