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 3 District estimates for access to improved water 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
Bara	1.000	1.000	< 0.001	↓-0.014	< 0.001	< 0.001
Bardiya	1.000	0.995	0.002	↓-0.012	< 0.001	< 0.001
Dhading	1.000	0.987	0.027	↑0.013	0.009	0.008
Dhanusa	1.000	1.000	< 0.001	↓-0.014	< 0.001	< 0.001
Dolpa	1.000	1.000	0.012	−0.002	0.001	0.001
Gorkha	1.000	1.000	< 0.001	↓-0.013	< 0.001	< 0.001
Kailali	1.000	1.000	0.008	−0.005	0.001	0.001
Kapilbastu	1.000	1.000	0.008	−0.005	< 0.001	< 0.001
Mahottari	1.000	1.000	< 0.001	↓-0.013	< 0.001	< 0.001
Manang	1.000	–	< 0.001	↓-0.014	< 0.001	< 0.001
Morang	1.000	0.992	0.003	↓-0.010	< 0.001	< 0.001
Myagdi	1.000	0.902	0.004	↓-0.009	< 0.001	< 0.001
Parbat	1.000	1.000	0.001	↓-0.012	< 0.001	< 0.001
Parsa	1.000	1.000	< 0.001	↓-0.014	< 0.001	< 0.001
Rasuwa	1.000	0.987	< 0.001	↓-0.014	< 0.001	< 0.001
Rautahat	1.000	1.000	0.003	↓-0.010	< 0.001	< 0.001
Rupandehi	1.000	0.993	0.002	↓-0.011	< 0.001	< 0.001
Saptari	1.000	1.000	< 0.001	↓-0.013	< 0.001	< 0.001
Sarlahi	1.000	1.000	0.016	0.003	0.001	0.001
Siraha	1.000	1.000	0.001	↓-0.012	< 0.001	< 0.001
Sunsari	1.000	1.000	0.002	↓-0.011	< 0.001	< 0.001
Chitawan	0.999	0.960	0.013	−0.001	< 0.001	< 0.001
Nawalparasi	0.993	0.936	0.020	0.005	0.001	0.001
Nuwakot	0.991	–	0.028	↑0.012	0.004	0.004
Mustang	0.990	–	0.010	−0.006	< 0.001	< 0.001
Makwanpur	0.989	0.775	0.025	↑0.009	0.004	0.003
Syangja	0.987	1.000	0.019	0.003	0.001	0.001
Baglung	0.987	0.997	0.020	0.004	0.001	0.001
Rolpa	0.984	0.939	0.012	−0.005	< 0.001	< 0.001
Taplejung	0.979	0.985	0.016	−0.002	0.001	< 0.001
Jhapa	0.978	0.860	0.016	−0.002	< 0.001	< 0.001
Bhaktapur	0.969	0.963	0.015	−0.004	< 0.001	< 0.001
Kanchanpur	0.968	0.996	0.036	↑0.015	0.002	0.002
Solukhumbu	0.966	0.943	0.021	0.001	0.001	0.001
Udayapur	0.960	0.927	0.035	↑0.013	0.002	0.002
Kavrepalanchok	0.948	0.953	0.037	↑0.013	0.005	0.004
Lamjung	0.947	1.000	0.045	↑0.020	0.005	0.004
Banke	0.946	0.990	0.061	↑0.037	0.020	0.017
Khotang	0.945	1.000	0.029	0.005	0.002	0.002
Pyuthan	0.940	0.974	0.033	↑0.007	0.002	0.002
Sindhupalchok	0.930	0.887	0.018	↓-0.010	0.001	0.001
Rukum	0.915	0.985	0.050	↑0.019	0.005	0.004
Dolakha	0.915	0.880	0.022	↓-0.009	0.001	0.001
Baitadi	0.910	1.000	0.061	↑0.029	0.010	0.009
Darchula	0.909	0.919	0.040	↑0.008	0.003	0.003
Palpa	0.906	0.974	0.072	↑0.039	0.014	0.012
Ramechhap	0.866	0.849	0.028	↓-0.013	0.001	0.001
Kaski	0.862	0.866	0.025	↓-0.017	0.002	0.002
Sindhuli	0.858	0.645	0.065	↑0.022	0.008	0.007
Mugu	0.851	0.977	0.021	↓-0.023	0.001	0.001
Terhathum	0.839	0.869	0.036	↓-0.011	0.002	0.002
Dang	0.835	0.791	0.050	0.003	0.005	0.004
Humla	0.831	0.683	0.024	↓-0.024	0.001	0.001
Okhaldhunga	0.830	0.614	0.035	↓-0.013	0.002	0.002
Lalitpur	0.825	0.767	0.058	↑0.009	0.005	0.005
Ilam	0.823	0.600	0.038	↓-0.012	0.002	0.002
Panchthar	0.811	0.700	0.036	↓-0.016	0.002	0.002
Tanahu	0.805	0.809	0.089	↑0.035	0.012	0.012
Salyan	0.782	0.563	0.097	↑0.038	0.017	0.016
Jumla	0.765	0.725	0.044	↓-0.018	0.003	0.003
Dadeldhura	0.763	0.734	0.076	0.014	0.011	0.010
Dhankuta	0.740	0.716	0.044	↓-0.023	0.003	0.003
Bajura	0.739	0.904	0.089	↑0.021	0.013	0.012
Gulmi	0.710	–	0.123	↑0.050	0.024	0.023
Kathmandu	0.702	0.702	0.110	↑0.035	0.022	0.020
Bajhang	0.701	0.711	0.072	−0.003	0.008	0.008
Kalikot	0.669	0.704	0.053	↓-0.029	0.004	0.004
Surkhet	0.649	0.670	0.068	↓-0.017	0.007	0.007
Bhojpur	0.622	0.333	0.113	↑0.022	0.019	0.020
Jajarkot	0.622	0.256	0.088	−0.003	0.012	0.013
Arghakhanchi	0.616	0.380	0.126	↑0.033	0.024	0.024
Sankhuwasabha	0.613	0.563	0.137	↑0.044	0.029	0.029
Achham	0.581	0.535	0.079	↓-0.021	0.012	0.011
Dailekh	0.492	0.349	0.060	↓-0.058	0.006	0.006
Doti	0.417	0.340	0.103	↓-0.030	0.019	0.020

^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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