Women's Work in Agriculture and Infant Nutrition (WWAN)
The Relationship Between Women's Workload in Agriculture and Infant Nutritional Status in Rural Sindh, Pakistan
Background Over the last 10 years there has been an increase in the female agriculture labour force, in Pakistan, resulting in a feminisation of agriculture; which could have either a positive or negative impact on maternal and young child nutrition. It could have a positive impact through increased female wage earnings that improve her bargaining/decision-making power within the household. Women are more likely than men to make pro-nutrition choices with regards to household expenditure. Conversely, women's involvement in agricultural work may have a negative impact on infant or maternal nutrition by reducing time available for child care, through increased expenditure of physical energy without compensatory increases in food consumption or exposure to harmful toxins present in pesticides and other chemicals used in farming. Understanding the dynamics of these pathways, in a specific context, is important to ensure agriculture programmes and policies do not disadvantage women or their children.
Overall aim To provide insights into positive and negative pathways between women's work in agriculture and maternal and child nutritional status, in different agriculture workload contexts, to inform agriculture interventions and policies in Pakistan.
Specific Objectives
- To determine whether the number of hours a mother participates in agriculture work is associated with maternal body mass index and infant nutrition.
- To identify factors that modify the influence of maternal participation in agriculture work on maternal and infant nutritional status.
Study Design A cohort study was conducted from September 2015 in irrigated rural areas of Pakistan. Infant-mother dyads were recruited when the infant was between 2 and 12 weeks of age inclusive. Anthropometric measurements (maternal and infant height / recumbent length and weight), interviewer administered questionnaires and spot observations were collected at recruitment (Time 1) and again when the infants were between 9-15 months of age (Time 2). The interviewer administered questionnaires were collected from each infant's mother (or the household head if the father was not present). A one page questionnaire was also completed at recruitment to record the numbers of women who agreed to participate in the study, the number who were approached but were not recruited into the study and the reasons they were not eligible to participate or their reasons for refusal.
Study Overview
Status
Status
Conditions
Conditions
Detailed Description
Study Design This study is an longitudinal observational study which was used to generate hypotheses rather than testing them. Mother-infant dyads were recruited between December 2015 and February 2016; and were followed up between November 2016 and January 2017.
Sampling The sample size (n=1000) was calculated to detect an increase/decrease in maternal BMI of around 0.18 for every additional hour worked with 80% power at a 5% level of significance. To estimate it, simulations were run to explore the power we would have to detect the relationship between maternal BMI and number of hours worked. It was based on a mean number of working hours of 6 and a standard deviation of 4 and a within cluster variation of 0.2 . This is a small effect size and suggests that the proposed sample size will provide adequate power to allow us to explore proposed relationships and generate hypotheses.
Participants were selected via systematic random cluster sampling. Initially, administrative villages with perennial canal irrigation were selected; villages with a population<10% or >90% of average village size were excluded, and random sampling was used to select villages from the eligible villages (n=2,909). All dyads, in the selected villages (n=62) were invited to participate in the study if: (i) the infant was a singleton birth ≥2 weeks and ≤ 12 weeks of age on the day of the first interview; healthy without congenital deformations that would impact on their ability to eat and (ii) the primary caregiver (i.e. the biological mother) intended to reside in the study area over the next 10 months.
To recruit these dyads, all recent births in the identified village were listed through a systematic multi-stage community profiling procedure using local key informants/resource persons including: health workers, midwives, doctors and paramedics, and locally well-informed individuals. In the first stage, several key informants per village were asked to exhaustively list all kinship groups or castes and localities within the village. Then they were asked to list all births from within those castes/localities within a given time period. Probes were used at both stages to counter exclusions. Afterwards a team of recruiters visited each of the listed mothers to confirm eligibility (i.e. correct age of the new born). Recruiters also probed for other births within the locality, to identify new cases through this snowballing technique. All dyads in the village who fulfilled this condition and met the inclusion criteria were recruited and actual date of birth was recorded.
Procedures and Methodology At each of the two data collection periods, interviewer administered questionnaires were collected from the mothers; and included questions related to socio-demographic status, health, dietary intakes, maternal agency and nutrition knowledge. These questionnaires were pilot tested and modified to ensure each questionnaire took less than 60 minutes per respondent to complete. For mothers, questions related to infant feeding, immunisation and pregnancy varied between the first and second data collection periods to reflect differences in infant age and maternal status. All data were entered directly into an android tablet.
Anthropometric measurements of maternal height and weight and infant weight and recumbent length were done in duplicate by trained anthropometrists using high quality equipment. If the first and second measurements did not agree to within a specified limit (e.g., 0.5 kg or 0.5 cm) a third measurement was taken. These data were entered directly into an android tablet to allow consistency checks for quality assurance. Spot observations were also done to determine housing materials and the hygienic conditions of the environment, which were entered directly into an android tablet.
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
-
-
-
Karachi, Pakistan
- Collective for Social Science Research
-
-
-
-
-
London, United Kingdom, WC1E 7HT
- London School of Hygiene & Tropical Medicine
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- Infant aged ≥ 2 weeks and ≤ 12weeks of age on the day of the first interview
- Infant is apparently healthy without congenital deformations that effect their ability to eat and grow
- The primary caregiver (i.e. biological mother) intended to reside in the study area over the next 10 months.
Exclusion Criteria:
- Infant aged ≤ 2 weeks and ≥ 12weeks of age on the day of the first interview
- Infant with congenital deformations that effect their ability to eat and grow
- The primary caregiver is not the biological mother)
- The primary caregiver not intending to reside in the study area over the next 10 months.
Study Plan
How is the study designed?
Design Details
- Observational Models: Ecologic or Community
- Time Perspectives: Prospective
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Body mass index
Time Frame: First survey (December 2015-February 2016)
|
maternal weight divided by height squared
|
First survey (December 2015-February 2016)
|
|
Body mass index
Time Frame: Second survey (November-January 2017)
|
maternal weight divided by height squared
|
Second survey (November-January 2017)
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Change in length-for-age Z-score
Time Frame: first survey (December 2015-February 2016) and second survey (November 2016-January 2017)
|
infant length
|
first survey (December 2015-February 2016) and second survey (November 2016-January 2017)
|
|
Infant and young child minimum dietary diversity (IYCMDD) score
Time Frame: second survey (November 2016-January 2017)
|
Scale measures the number of food groups in the infant's diet; the scale range is from 0 to 7 with higher values representing a better outcome.
|
second survey (November 2016-January 2017)
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 9647 (Other Identifier: Fred Hutch/University of Washington Cancer Consortium)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
Clinical Trials on Malnutrition
-
NCT07504133CompletedMalnutrition (Calorie) | Protein-energy Malnutrition
-
NCT06976827Not yet recruitingMalnutrition Severe | Malnutrition; Moderate
-
NCT03032237CompletedMalnutrition; Protein | Protein Malnutrition
-
NCT06965699RecruitingMalnutrition Elderly | Protein Malnutrition
-
NCT07254897Not yet recruitingMalnutrition or Risk of Malnutrition
-
NCT02616289CompletedMalnutrition | Malnutrition in Children | Child Malnutrition
-
NCT03355313Unknown
-
NCT07636369Not yet recruitingMalnutrition or Risk of Malnutrition | Anorexia of Aging
-
NCT06038071RecruitingModerate Acute Malnutrition | Severe Acute Malnutrition