Unintended childbearing Unintended childbearing and family welfare in and family welfare in

rural Malawirural 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

Hewlett/ESRC Joint Proposal Scheme

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.

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

To What extent greater contraceptive use and lower fertility will enhance investments in human capitalWhat are the consequences of unwanted or unintended childbearing on children’s life chances

OBJECTIVES:

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

Unintended childbearing and family welfare in rural Malawi

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

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)

Karonga Prevention Study

Karonga: district northern Malawi Approx. 236,000 people live in 280 villages Subsistence agriculture Fish Lake Malawi

its History in a nutshell:1979-85 LEP 1)1986-89 (LEP 2)1990-1996 vaccine trial follow up1996-2001 Welcome trust 2002-2004 baseline census

DSS cover 30,000 populationIn 135 KM2

DSS SITE

Data: Continuous Registration System

Schedule of staggered start ofreporting groups and their monthly reporting session

VILLAGE INFORMANT

Data: DSS and the census sero-survey already contains info on:

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).

It is possible to link childrenTo their biological parents

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.

Measures of Fertility Preference

Retrospective measures Prospective measures Men Women

This will allow:

1. The comparison of responses between couples.

2. The comparison of their predictive power.

3. The identification of births unwanted by both of the parents.

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

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.

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.

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.

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..