Geographical heterogeneity and inequality of access to improved drinking water supply and sanitation in Nepal

He, Wen-Jun; Lai, Ying-Si; Karmacharya, Biraj M.; Dai, Bo-Feng; Hao, Yuan-Tao; Xu, Dong Roman

doi:10.1186/s12939-018-0754-8

International Journal for Equity in Health

Table 2 District estimates for access to improved sanitation and summaries of inequity coefficient

From: Geographical heterogeneity and inequality of access to improved drinking water supply and sanitation in Nepal

Districts	Model Estimate(JMP adj)	Raw coverage^a	Gini	RGI score^b	Theil L	Theil T
Kathmandu	1.000	0.983	0.004	↓-0.043	0.000	0.000
Bhaktapur	1.000	0.963	0.006	↓-0.045	0.001	0.001
Lalitpur	0.989	1.00	0.026	− 0.025	0.003	0.002
Dolpa	0.885	0.973	0.061	−0.010	0.007	0.007
Chitawan	0.885	0.903	0.047	−0.023	0.005	0.005
Kaski	0.884	0.946	0.083	0.012	0.015	0.014
Morang	0.811	0.854	0.114	↑0.029	0.024	0.022
Syangja	0.769	0.839	0.061	↓-0.032	0.008	0.008
Jhapa	0.747	0.623	0.088	−0.009	0.030	0.022
Sunsari	0.738	0.818	0.163	↑0.065	0.068	0.056
Palpa	0.725	0.795	0.081	−0.019	0.016	0.014
Kavrepalanchok	0.721	0.698	0.126	↑0.024	0.031	0.027
Nawalparasi	0.711	0.779	0.123	0.020	0.035	0.029
Mustang	0.710	–	0.110	0.007	0.020	0.021
Dolakha	0.709	0.703	0.110	0.006	0.023	0.021
Myagdi	0.687	0.561	0.088	−0.019	0.012	0.013
Surkhet	0.684	0.739	0.064	↓-0.044	0.006	0.006
Gorkha	0.678	0.726	0.090	↓-0.019	0.013	0.012
Makwanpur	0.674	0.609	0.129	0.019	0.042	0.034
Baglung	0.674	0.754	0.192	↑0.081	0.082	0.067
Parbat	0.665	0.846	0.184	↑0.072	0.073	0.063
Humla	0.637	0.561	0.041	↓-0.076	0.003	0.003
Mugu	0.636	0.886	0.073	↓-0.044	0.008	0.008
Khotang	0.629	0.753	0.111	−0.007	0.023	0.021
Taplejung	0.612	0.632	0.094	↓-0.028	0.017	0.016
Darchula	0.608	0.651	0.050	↓-0.073	0.005	0.005
Tanahu	0.604	0.671	0.147	↑0.024	0.034	0.033
Rupandehi	0.603	0.753	0.249	↑0.126	0.178	0.121
Lamjung	0.590	0.512	0.060	↓-0.065	0.006	0.006
Pyuthan	0.587	0.746	0.135	0.008	0.050	0.040
Rolpa	0.585	0.351	0.194	↑0.067	0.082	0.066
Jajarkot	0.565	0.538	0.025	↓-0.105	0.001	0.001
Baitadi	0.551	0.592	0.070	↓-0.063	0.013	0.011
Manang	0.530	–	0.001	↓-0.136	0.000	0.000
Udayapur	0.522	0.553	0.229	↑0.091	0.097	0.085
Saptari	0.520	0.457	0.316	↑0.178	0.211	0.167
Salyan	0.520	0.400	0.111	↓-0.028	0.027	0.023
Dang	0.518	0.570	0.163	↓0.024	0.054	0.046
Rukum	0.516	0.470	0.054	↓-0.085	0.009	0.008
Sindhuli	0.508	0.474	0.290	↑0.149	0.162	0.137
Dhankuta	0.499	0.770	0.139	−0.004	0.031	0.030
Kanchanpur	0.492	0.576	0.246	↑0.102	0.126	0.101
Sindhupalchok	0.488	0.450	0.092	↓-0.052	0.014	0.014
Bara	0.470	0.479	0.220	↑0.072	0.101	0.083
Dadeldhura	0.464	0.429	0.099	↓-0.050	0.021	0.019
Kailali	0.463	0.577	0.276	↑0.126	0.128	0.118
Dhading	0.460	0.354	0.163	0.013	0.043	0.043
Parsa	0.458	0.619	0.247	↑0.097	0.128	0.107
Ilam	0.453	0.448	0.182	↑0.031	0.052	0.052
Rautahat	0.452	0.676	0.173	↑0.022	0.051	0.047
Arghakhanchi	0.448	0.380	0.063	↓-0.089	0.006	0.006
Ramechhap	0.447	0.209	0.142	−0.010	0.033	0.032
Kapilbastu	0.442	0.426	0.136	↓-0.017	0.035	0.031
Banke	0.440	0.564	0.284	↑0.130	0.185	0.141
Dailekh	0.420	0.362	0.218	↑0.061	0.081	0.074
Jumla	0.420	0.288	0.136	↓-0.021	0.029	0.029
Gulmi	0.411	–	0.102	↓-0.057	0.018	0.019
Bardiya	0.405	0.363	0.127	↓-0.033	0.030	0.029
Nuwakot	0.388	–	0.145	−0.019	0.035	0.038
Sankhuwasabha	0.369	0.463	0.140	↓-0.027	0.030	0.031
Siraha	0.352	0.320	0.041	↓-0.129	0.004	0.004
Panchthar	0.343	0.250	0.107	↓-0.065	0.019	0.019
Bhojpur	0.330	0.090	0.246	↑0.072	0.092	0.096
Bajhang	0.327	0.364	0.121	↓-0.054	0.022	0.023
Rasuwa	0.325	0.208	0.078	↓-0.097	0.009	0.009
Doti	0.301	0.313	0.239	↑0.060	0.093	0.089
Okhaldhunga	0.288	0.227	0.090	↓-0.092	0.014	0.015
Terhathum	0.280	0.250	0.093	↓-0.091	0.013	0.013
Bajura	0.274	0.247	0.279	↑0.094	0.125	0.121
Achham	0.267	0.258	0.276	↑0.090	0.119	0.118
Solukhumbu	0.243	0.090	0.206	0.015	0.065	0.068
Dhanusa	0.205	0.243	0.201	0.003	0.064	0.063
Kalikot	0.195	0.136	0.165	↓-0.034	0.045	0.050
Sarlahi	0.186	0.160	0.143	↓-0.058	0.033	0.036
Mahottari	0.181	0.264	0.204	0.002	0.066	0.073

^a4 districts—Mustang, Guimi, Nuwakot and Manang—have no raw coverage as no samples are located in those areas
^bThe RGI score measures relative inequality when given coverage levels. Negative values indicate a lower than expected inequality, while positive values indicate greater than expected inequality. ↓means a score significantly lower than 0, while ↑means significantly higher than 0

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