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Reproductive and Overall Health Outcomes and Their Economic Consequences for Households in Accra, Ghana Allan Hill and Günther Fink Harvard Center for Population & Development Studies Ernest Aryeetey and Isaac Osei-Akoto Institute for Statistical, Social and Economic Research Third Annual Research Conference on Population, Reproductive Health and Economic Development Dublin, Jan 16-18, 2009
Research Questions Broad question: What are the economic consequences of ill health? Original Research Questions: • How do spells of ill health affect household income and consumption in urban Sub-Saharan Africa? • How does household composition affect the coping mechanisms chosen by the household in the short run? • How does ill health affect household composition in the short and medium run?
Empirical challenges… • Identifying the causal effect of ill health on economic outcomes in the presence of unobserved heterogeneity • Distinguishing “reproductive” morbidity from general ill-health • Measuring the indirect effects of women’s RH morbidity • Childhood illness and women’s work • Other adult illnesses in the household • “Openness” of household support (e.g. Ga non-residence of spouses; extended family transfers; national health insurance) • Capturing the co-incidence of a set of individually “minor” RH conditions which are nonetheless additive….
Baseline Sample Women’s Health Study of Accra 2003: • Representative sample of 3200 women aged 18+ from the Accra Metropolitan Area • Over-sampling of elderly • Stratification by social class based on census data • Detailed home interview with focus on general and reproductive health • Blood tests and hospital visit for a sub-sample of the women (Korle Bu Teaching Hospital)
Findings from 2003 • Heavy burden of non-communicable diseases – strong association with age • Obesity • Cholesterol levels • Diabetes • Depression and mental illness • Women of reproductive age in good general health • TFR=2.1 • Clustering of minor reproductive health conditions (co-morbidities c.f. Giza Study) • RH conditions additive…
Physical examination • Measurement of height, weight and girth • Measurement of visual acuity • Measurement of blood pressure, heart rate and temperature • Complete physical examination: head to toe
Study Design • Sub-sample of 1000 households indexed to women interviewed both in 2003 and 2008 (in progress) • Each households is followed over 12 weeks with at least one visit per week • Rolling sample to guarantee regional coverage of all four socioeconomic residence types in each season
Accra Metropolitan Area • Total population estimate 1.6-2.9 Millions (about 10% of total population) • 1741 enumeration areas (EA) in 6 sub-metros – 200 randomly selected
Rolling Sample Time Line 12 weeks Week 1 IV 1 round 1 Week 2 IV 2 round 1 Week 3 IV 3 round 1 • Each “cohort” consists of • 20-25 households • 3-5 different EAs IV 11: round 4 IV 12: round 4 Week 52 IV 13: round 4 December 09 October 08
Background Information Collected • Householdstructure and arrangements (week 1) • Detailed schooling information for all children in the houshold (week 7) • Detailed job information for all adult household members (week 10) • Detailed health history of index woman and her family (WHSA II)
Main Health Information Collected • Health Module: During each of the 12 weekly visits, a log about sickness spells in the household is kept. If any acute sickness occurred in previous 6 days, the following information is collected:uration of sickness • Health facility name and location • Medication used • Direct cost to the household: prescriptions & doctor fees • Indirect private cost: number of hours/days not able to work • Indirect HH cost: number of hours other HH members stayed home to take care of sick person
Additional Health Information Collected • Daily time use and health diaries: selected household members are trained to fill out daily diaries containing: • Principal activity for each 30 minute time block • Overall self-health assessment each day
Discussion Diary Data Main benefits: • allows to verify household response from health modules: how does daily routine change for individuals during health problems of any HH member? • Provides interesting picture of everyday life in an modern African urban environment – how do individuals spend their time? • Allows limited risk factor analysis: work distance, commuting and health; work/leisure balance and health Concerns: • Large potential error in self-reports • Major sample selection problem: literacy!
Data Collection: Status and Projection More coming soon…