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Assessing Health Inequality in Mongolia. Group work & plenary discussion. Q1. Reports have produced by the NSO and MOH contain health data disaggregated by : - age and sex – by administrative and sample survey - education – by administrative and sample survey
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Assessing Health Inequality in Mongolia Group work & plenary discussion
Q1. Reports have produced by the NSO and MOH contain health data disaggregated by: - age and sex – by administrative and sample survey - education – by administrative and sample survey - province/districts - by administrative and sample survey - rural/urban areas - by administrative and sample survey - health status (disability) - by sample survey - income/wealth – by sample survey - employment – by sample survey
Q2. Following health indicators produced by the NSO and MOH disaggregated by: - morbidity by diseases: - by age and sex - education - province/districts - rural/urban areas - mortality, by diseases and causes - by age and sex - education - province/districts - rural/urban areas
Q2. Following health indicators produced by the NSO and MOH disaggregated by: • - births • - by age and education of mothers • - province/districts • - rural/urban areas • - by sex /for new born babies/ • - weight, by sex • - still and alive births • prenatal care • 1st 3 months • 3-6 months • above 7 months • coverage of medical tests for pregnant mothers
Q2. Following health indicators produced by the NSO and MOH disaggregated by: - infant and child mortality rate - neonatal and post natal mortality rate - under five mortality rate -by regions/provinces/districts - by ICD /for IMR/ - maternal mortality - by actual number - by rate for 100000 live births -by regions/provinces/districts -by causes -accessibility of health - health personnel
Q3. Following stratifiers are: - age and sex - geographical areas - urban and rural residences
Q4. Data sources are: - Administrative records - Household based sample surveys /eg., MICS, HSES and LFS etc./ - Population and housing census - only number disabled persons
Q5. We are using for data visualization: - tables - graphs - infograph – just new - Measures inequality - rate - ratio - differences of absolute numbers
Q6. Example: - Survey on health inequality under support of the ADB /sampled 7 provinces/ in 2012 – 2000 households - Guidelines of health service delivery for disadvantaged persons approved by the MOH at the end of 2013 - Structural adjustment for the MOH – a staff-in charge of inequality for health services
Q7. Obstacles: - this issue is quite new for us - data utilization is weak - is not widely recognized - is not any data related minority of population