Unintended childbearing and family welfare in rural Malawi

1. Hewlett/ESRC Joint Proposal Scheme Unintended childbearing and family welfare in rural Malawi Angela Baschieri, John Cleland, Albert Dube, Neil French, Anna Molesworth, Sian Floyd, Judith Glynn Date: 16-17 January, Dublin, Ireland. Third Annual Research Conference on Population, Reproductive Health, and Economic Development

2. Unintended childbearing and family welfare in rural Malawi • Project scope, aims and objectives • Background Malawi • Karonga Prevention Study • Data: Karonga DSS  This study • Progress so far: data collection • Progress so far: analysis. • Next steps.

3. Unintended childbearing and family welfare in rural Malawi THE BIG QUESTION in development! • We all agree: accumulation of human capital sustainable economic growth FAMILY WELFARE: • Child nutritional growth • Schooling outcomes • Mother’s nutritional status OBJECTIVES: To What extent greater contraceptive use and lower fertility will enhance investments in human capitalWhat are the consequences of unwanted or unintended childbearing on children’s life chances

4. Unintended childbearing and family welfare in rural Malawi • Conduct a study linked to an on-going Demographic Surveillance Site in Karonga District in Northern Malawi • Ideal setting to study the relationship between family planning and fertility and investments in children schooling and nutrition • Longitudinal data and methodologies (event history, survival, IVR, simultaneous..) to deepen understanding of the causal linkages b/w demographic dynamics, FP and investment in future generation

5. Aims • To gain a better understanding of the consequences of the ‘intendness’ status on the survival and growth of the index child as well as the effect of a short birth interval on the growth of the index child. • To assess the consequences of unintended and intended births on the physical growth and schooling outcomes of older siblings. • To measure the effects of an ‘unintended’ birth on mother’s health

6. Background: Malawi • One of the poorest countries in the world. • In 2006, ranked 166 out of 177, HDI. • TFR 6, 26.3 % using any method of contraception • ½ women with 6 children said would ideally have liked less than 6. • 80% children 6-13 attend school BUT 11 % of 14-17 years old attend a secondary • 50% are moderately stunted to short for their age (20% severely stunted)

7. Karonga Prevention Study • Karonga: district northern Malawi • Approx. 236,000 people live in 280 villages • Subsistence agriculture • Fish Lake Malawi DSS SITE its History in a nutshell: 1979-85 LEP 1) 1986-89 (LEP 2) 1990-1996 vaccine trial follow up 1996-2001 Welcome trust 2002-2004 baseline census DSS cover 30,000 population In 135 KM2

8. Data:Continuous Registration System Schedule of staggered start of reporting groups and their monthly reporting session VILLAGE INFORMANT

9. Data: DSS and the census sero-survey already contains info on: It is possible to link children To their biological parents • Vital events: (birth and death) (on-going). • Demographic: information of each member of the hh (on-going). • The identification number of each individual • Data on children’s schooling.: school attendance, reasons for non-attendance, attainment of school leaving certificate, who is paying for each child’s school fees, (annually). • Socio-economic status of the household: livestock assets, household assets, characteristics of dwelling, source of income, food and nutrition security information, subjective poverty measure (annually). • Economic activities of each hh member aged 10+ (annually).

10. Data: This project: • Strengthen the measures of fertility preferences for women and add similar questions to the men’s questionnaire. To the added to the Adult behavioral Survey (MEN and WOMEN). • The collection of anthropometric measures (height and weight) of children under 10 years old over three waves (2008, 2009, 2010). (with the Socio-Economic questionnaire). • The collection of mid-upper arm circumference for women, over the three waves. • Improve measures of school drop out/attendance.

11. Measures of Fertility Preference • Retrospective measures • Prospective measures • Men • Women This will allow: • The comparison of responses between couples. • The comparison of their predictive power. • The identification of births unwanted by both of the parents.

12. Proposed methods • Careful study of the temporal sequencing of events will help to identify causal relationship  Survival analysis, event history  instrumental variables methods  simultaneous equation modeling technique

13. Collaboration with APHRC in Nairobi • Collaboration with APHRC in Nairobi • Nairobi Urban Demographic Surveillance Site • Two workshops will be organized (Y1 and Y3) and a research from the APHRC will work on the NUDSS providing doc. and preparing data for comparative analysis b/w the two sites.

14. Expected Outcomes • New evidence concerning the effect of unintended (and intended) births on the nutritional status of mothers and on the growth and schooling of older siblings. • New robust measures of unwanted fertility and unmet need for family planning. • Information on the physical growth of children especially in the understudies 5-9 yrs old (remedial policy; free or subsidised school meals). • Analysis of school enrolment, poverty-school drop out.

15. Progress so far: • Recruitment of interviewers and research scientist. • Shipment of motorcycles, equipments. • Ethical approval from NSRC of Malawi, and LSHTM ethical committee. DATA COLLECTION: • Logistics of data collection. • Questionnaire design, pilot, start of data collection ANALYSIS OF DATA: • Fertility Monograph, Indepth Network • Analysis of couple’s agreement and disagreement on fertility intention in polygamous community.

16. Next steps: • Monitor data collection. • Carry out analysis on couple’s agreement and disagreement on fertility intention. • Carry out analysis of anthropometric failure. • Share findings with the Malawian National Science and Research Committee, Malawian Governments. • Organize 1st workshop with Nairobi partners. • Etc..