Unintended childbearing and family welfare in rural malawi
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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.

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Unintended childbearing and family welfare in rural malawi

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


Unintended childbearing and family welfare in rural malawi1
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 malawi2
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


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


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
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 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


Data continuous registration system
Data:Continuous Registration System

Schedule of staggered start of

reporting groups and

their monthly

reporting session

VILLAGE INFORMANT


Data dss and the census sero survey already contains info on
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).


Data this project
Data: This project: on:

  • 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
Measures of Fertility Preference on:

  • 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.


Proposed methods
Proposed methods on:

  • 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 on:

  • 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
Expected Outcomes on:

  • 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
Progress so far: on:

  • 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
Next steps: on:

  • 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..


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