SlideShare a Scribd company logo
1 of 41
Key Gender and Livelihood Issues in Livestock
   Production, Management and Marketing

                         Jemimah Njuki
             Team Leader: Poverty, Gender and Impact

 FAO-ILRI Workshop on Integrating Gender in Livestock Projects and
       Programs, ILRI, Addis Ababa, 22-25 November 2011
Key Gender and Livestock Issues

• Livestock’s contribution to
  household assets
• Livestock’s contribution to income
• Patterns of livestock ownership
• Men and Women’s role in livestock
  keeping
• Access to services, information
  and technologies
• Men and Women’s participation in
  livestock markets
• Links between
  gender, livestock, food
  security, nutrition and health
Livestock as an Asset
Livestock as an asset?

 Livestock, especially small stock, form a critical
  rung on the asset ladder out of poverty
 Livestock are among the few assets women can
  own
 Livestock are “productive” assets; livestock and
  their products contribute to food and income
  security
 Livestock as a social asset..
Contribution of livestock to household assets
   •    Livestock an important asset contributing 55% of the total asset index for all households (52.7%
        male headed households and 68% for female headed households) in Kenya
   •    Similar trends in Tanzania, with livestock contributing to 69% of all households asset index, and
        68% and 75% for male and female headed households respectively.

                                                                                     Total domestic       % of
                              Total HH     Total livestock                            and livestock   livestock to
           Household Type      index           index                                      index        total index
Kenya      Male-headed         97.14           51.28           Kenya        Men          41.01            21.5
           Female-headed        43.07          29.31                      Women          16.68           22.5
           Total                83.35          45.67                        Joint        60.35              36
Tanzania   Male-headed          105.6           72.2          Tanzania      Men          41.80           46.6
           Female-headed         49.9           37.6                      Women          11.42           18.3
           Total                 95.7            66                         Joint        58.47           24.2


   •    Within male headed households, women held 10.2% and 13.9% of the total domestic and
        livestock assets in Tanzania and Kenya respectively.
   •    For women, this represented 22.5% and 18.3% of the non land asset index under their
        ownership
   •    Gender asset disparity of 0.27 in Tanzania and 0.41 in Kenya. This does not take into account
        jointly held assets
Household ownership of livestock – Male and Female
    headed households




•  Local chickens and dairy cows were the most commonly owned livestock
  species in Kenya
• In Tanzania, local chicken, goats and pigs were the most common species
• There were no big differences in proportion of male and female headed
  households owning different species.
Livestock holdings in male and female headed
households
  Kenya
                   Male-   Female-               • Female headed households had
                  headed   headed
     Livestock     Mean     Mean        T-         significantly smaller numbers of
                                     statistic     cattle, chicken (local, improved)
 Bee Hives         3.71      3        0.966
 Dairy Cattle      2.64     2.08     2.074**       compared to their male
 Exotic chicken    187       14      2.487**       counterparts
 (Broilers)
 Exotic chicken   56.32     11.4     2.26**
 (Layers)
 Goats             6.15     4.64      0.752      • Similar results in Tanzania
 Local chicken    13.43     8.98     1.859**
 Other cattle      2.47     2.75     -0.182
 Pigs              6.33     5.5       0.195
 Sheep             4.06     3.28      1.011
Livestock ownership: Men and women within male
headed households
  Kenya                                            Tanzania
                 Men and women in male headed                    Men and women in male headed
                          households                             households
                  Men      Women       Joint    Livestock type     Men      women      Jointly
 Bee Hives        3.8        1.3       3.5
                                                Bee Hives           7.8       3.0       21.3
 Dairy Cattle     3.0        1.5       2.6      Dairy Cattle        3.5       4.0        6.1
 Exotic
                  8.0       350.0     191.0     Exotic chicken
 (Broilers)                                                        258.0     156.7     100.0
                                                (Broilers)
 Exotic
                  70.0      56.5       48.3
 (Layers)
                                                Exotic chicken
 Goats            11.2       3.9       4.7                         200.0       -       346.5
                                                (Layers)
 Local chicken
                  19.1      15.7       9.9      Goats              8.6        3.4        8.9
                                                Local chicken      22.8      39.7       23.3
 Other cattle     1.7        1.0       2.7
                                                Other cattle       9.1        2.0        5.4
 Pigs             5.7         -        7.0
                                                Pigs               4.0        2.4        4.1
 Sheep            4.4        2.3       3.8      Sheep              5.2        6.0        6.3

 In the two countries, women had lower numbers of every livestock species than men in
 male headed households with the exception of chicken in Kenya and Tanzania and Dairy in
 Tanzania.
How do women gain and maintain
     control over livestock?

• Women are less likely than men to
  acquire animals in the
  marketplace.
• Threats:
   – Drought and disease
   – Dissolution of the household
   – Commercialization?
Means of acquisition of livestock by women

• Despite other
  evidence, across species, the
  main means of livestock
  acquisition by women was
  through purchase

• In Tanzania, overall, about
  50% of livestock owned by
  women was through
  purchase

• For, goats, other cattle and
  local chicken, born into the
  herd was a common source
  for women
Livestock as a source of income
Contribution of livestock to household cash income

                        • Livestock contributed 35% of
                          cash income in Tanzania and 55%
                          in Kenya

                        • Contributed more to income in
                          female headed households than
                          male headed households

                        • Variation in contribution by
                          income quartile across the 2
                          countries
Men and Women’s Roles in
   Livestock Keeping
• Women provide a large share of the labor in
  livestock keeping, especially in mixed
  systems and poor households
• Women’s priorities and constraints are
  often, but not always, different from men’s
Women’s role in livestock keeping

• Women often control                    70
  products even where                    60

  they don’t control                     50




                          % housheolds
                                         40
  animals                                30


• For example, women                     20

                                         10
  often control some or                  0

  all milk even if they                       Morning Milk

                                                             Male   Female   Mixed
                                                                                     Evening Milk



  can’t decide where
  the cow is grazed or
  whether it is sold.
Roles
• Division of rights and responsibilities
  affects incentive and ability to adopt
  new technologies and practices to
  increase production and productivity.

• We need to understand this better to
  develop appropriate technologies and
  design more effective interventions.
Access to services, information
      and technologies
Participation & registration in
Cooperatives
-Few dairy farmers registered in
Cooperative




                                   Very few women
                                   participated in
                                   Cooperatives
                                      -None in Uganda
                                      -27% of registered
                                      members in Kenya
Men and Women’s Participation
     in Livestock Markets
Women’s participation in markets
• Sale of livestock and
  livestock products are
  often an important
  source of income for
  women
• Men and women face
  different constraints in
  marketing
• Women are more likely to sell in informal, local
  markets
• Women’s marketing costs are often higher than
  men’s:
  – Information—women face higher costs, but
    groups can help
  – Most often have to pay male intermediaries
Who mainly sold livestock and livestock
                          products?




•   High participation of women in sale of livestock products (eggs and milk) and very low
    participation in sale of livestock (cattle, sheep, goats)

•   Differentiation between ownership and management. Even in cases where women do not
    own the livestock, they are involved in the sale of products but not the sale of the livestock
    itself
Common markets accessed by men and women-
                Tanzania
Common markets accessed by men and women

            •   Most commonly sold to markets by women
                were sales at farm gate to other farmers or
                traders (for chicken, eggs, milk and honey)

            •   Women rarely made sales to city markets, or
                delivered to shops, collection centres or chilling
                plants ( milk)

            •   Men made more deliveries to shops/ hotels
                /kiosks and other outlets

            •   In Kenya women had more options for markets
                than in Tanzania

            •   Chicken, eggs and milk had more market options
                than products such as honey
Income management by men, women in male
           headed households


                       • In Kenya, low income
                         management by women across
                         species and products



                       • In Tanzania, more income from
                         chicken, milk and honey
                         managed by women compared
                         to Kenya
Variation in income share depending on where sold

                                 • Women managed a
                                   higher income share
                                   when product was sold
                                   at farm gate compared
                                   to when sold at village
                                   markets or delivered to
                                   traders



                                 • Differences less clear for
                                   sales of sheep, goats
                                   and cattle due to
                                   ownership patterns
Variation in income share depending on who sold




• When women sold (physically or did the transaction), they managed a higher
  income share (for both products and species)
Gender, Livestock, Nutrition and
            Health
Gender, Livestock, and Nutrition
"Even small additional amounts of meat and milk can
   provide the same level of nutrients, protein, and
   calories to the poor that a large and diverse amount
   of vegetables and cereals could provide”
 “The Cow Turns Green,” Newsweek, September 7, 2009

• Livestock ownership alone is not sufficient to ensure
  consumption of animal source foods (ASF)
• Women play a key role in household choices about
  food consumption, dietary quality, and intra-
  household allocation.
• Women’s status is key to making good choices here
Women, Livestock and Health
• Many important diseases are zoonotic, and
  food safety can be a major issue with animal
  source foods
• A gendered risk assessment found:
   – Women’s higher exposure to high-risk activities
     such as feeding, milking, and cleaning of livestock
   – Women and men exposed to different diseases, by
     species
   – Women much more exposed to food-borne
     diseases because of role in food and by-product
     processing, food preparation, and selling ready to
     eat
Livestock production and human
      nutrition? What do we know?
Its complex!                                                                  test



                                                                                                    Land allocation
                                                                                                       to feed                                                   -
                                                                                                +
                                                                                                                                                           -
                                                                                                                                                           +         Food crop
                                                                                                    Traction, nutrient                                               production
                                                                                                         cycling
                                                                                                +
                                                                                                                               Animal &                                     +
                                                                                                                    +        product sales
                                                                                                  Animal                                                   Food crop sales
                                                                                                production                                   +
                                                                    Animals                +
                                  +                                 owned                                                                      HH      +
                Labor allocated                                                                                                              Income
                  to livestock                                                                                                                                          +       Food crop
                                                                                                                                                                                purchases
                                                         Health           +                                                                                +                                         test
                                      +                                         Chronic
                                                         inputs               disease risk          +                                                 ASF purchases
                         Probability of                                                                                                          +
                       zoonotic disease                                                                    +                     HH ASF
                                               +                               Environmental toxin                             consumption                                                    +
                                                                                 concentration                                                                                          +
                                          Water                                                                          +
                                      contamination                                                                                                                                      HH crop
                                                                                                           Food-borne                                                                  consumption
                                                                                                            diseases
                                                                +     -   -                                +                                                           +
                                                                               -
                                                            -                                                                  +
                                                                                                                                                       Dietary
                                                        -       Human health                                Human                                      intake
                                                                   status                                  nutritional
                                                                                                        (growth) status                                          +

                                                                                   +
                                           +
                                                   Total labor                                                                               +   Level of care/feeding
                                                   demands                                                                                             behavior

                                                                                       +
                                                                                               Labor demands on
                                                                                               (female) caregiver



Figure. Hypothesized causal linkages between livestock keeping and human nutrition and health outcomes among the poor
(adapted from Nicholson et al., 2003). ASF = animal-source food; HH = household (Randolph et al. 2007)
Direct Nutrition Benefits


   Intermediate determinants of child
    nutritional status
   Breast Feeding and weaning practices
   Food intake patterns and practices (diet
    diversity and food frequencies)
   Intra-household food allocation
   Nutrition knowledge, attitudes and
    practices
Intensification and Household Consumption

• Key indicators
   – Proportion of milk kept for consumption from total
     production
   – Proportion of evening milk kept for consumption

                                                            Emerging     Advanced

 Mean daily milk production, in liters                             3.2        10.8

 Mean daily milk consumption, in liters                            2.0         4.9
 Proportion of households keeping all of evening milk for         93.5        74.2
 consumption
GENDER, LIVESTOCK AND FOOD SECURITY

 Livestock and food security: Calculated variables
 • Household/Individual dietary diversity score
   (HDDS/IDDS)
    – Takes a value of 0-1 and is measured based on a 24 hour recall
    – Can also be used to calculate proportion of households consuming
      at least one animal source food per day
 • Food consumption score
    – Based on consumption of food groups
    – Each food group is weighted
    – Contribution of meat, fish and milk to the food consumption score
 • Months of adequate household food provisioning
   (MAHFP)-
    – Measured over a 12 month recall period
Women’s ownership of livestock and food
                             security
Tanzania                        HDDS                                MIHFP
                                                                                          • Women’s ownership
                               women                                 women                  of dairy cattle and
                  women                                  women
                                do not                                do not
                    own
                                 own
                                           T-values        own
                                                                       own
                                                                              T-values      chicken influenced
                 livestock                              livestock
                              livestock                             livestock               HDDS in both Kenya
Dairy cattle       0.69         0.55       1.44**          11         8.77    3.67 **       and Tanzania
Exotic chicken     0.58         0.55       2.8 ***        11.5        8.77     5.08*
Local chicken      0.63         0.55        0.92          8.84        8.67     0.416
Goats              0.51         0.56        0.35           8.5        8.83     0.51
                                                                                          • In Kenya ownership
Kenya                            HDDS                                 MIHFP                 of local chicken and
                   women        women        t-values    women women           t-values     goats also
                     own         do not                    own      do not                  influenced HDDS
                  livestock       own                    livestoc    own
                               livestock                     k    livestock


Dairy cattle        0.73          0.65      3.105***        4.3        5.8     2.272**
Exotic chicken      0.82          0.66      4.376***        3.7        5.5      1.689
Local chicken       0.71          0.66      2.118**         5.3        5.4      0.242
Goats               0.61          0.69      2.564**         5.1        5.4      0.403
Household Economics
                       Changes in income
                        and income share
                        generated by dairy
                        activities

                       Income
                        expenditure on
                        food

                       Allocation of milk
                        production to own
                        consumption vs
                        sale
Gender mediated interventions

                Changes in women’s roles with
                 introduction /intensification of livestock
                 production especially in terms of time
                 allocation (care giver time)

                Decision making in relation to use of
                 milk and income allocation

                Expenditure patterns-food and health
                 input purchases

                Access to training, nutrition
                 information, livestock assets
Impact of Dairy on Primary Caregiver’s Time:
Time spent on daily activities over intensification levels

      Average Time Spent on Daily Activities (in minutes)

                             No Cow      Emerging Advanced

Childcare Activities         201.0       227.5      219.4


Income Generating            281.9       283.9      275.5
Activities
Cattle Activities            15.3        112.1      56.9
Public Health
     Health related determinants of
      child nutritional status (healthcare
      expenditure and health seeking
      behaviour

     Disease risk profiling

     Syndromic surveillance

     Access to public health services
      and information

More Related Content

What's hot

ICTs along the agriculture value chain
ICTs along the agriculture value chainICTs along the agriculture value chain
ICTs along the agriculture value chain
Nawsheen Hosenally
 
Participatory extension.
Participatory extension.Participatory extension.
Participatory extension.
PankajOjha31
 

What's hot (20)

Gender in Agricultural Development
Gender in Agricultural DevelopmentGender in Agricultural Development
Gender in Agricultural Development
 
Women and Agricultural Technology Use
Women and Agricultural Technology UseWomen and Agricultural Technology Use
Women and Agricultural Technology Use
 
Integrating Gender In Agricultural Programs
Integrating Gender In Agricultural ProgramsIntegrating Gender In Agricultural Programs
Integrating Gender In Agricultural Programs
 
Gender mainstreaming in agricultural research for development: Experiences fr...
Gender mainstreaming in agricultural research for development: Experiences fr...Gender mainstreaming in agricultural research for development: Experiences fr...
Gender mainstreaming in agricultural research for development: Experiences fr...
 
main streaming gender in extension- issues and perspectives
main streaming gender in extension- issues and perspectivesmain streaming gender in extension- issues and perspectives
main streaming gender in extension- issues and perspectives
 
Participatory approaches manjuprakash
Participatory approaches manjuprakashParticipatory approaches manjuprakash
Participatory approaches manjuprakash
 
ICTs along the agriculture value chain
ICTs along the agriculture value chainICTs along the agriculture value chain
ICTs along the agriculture value chain
 
B.sc. agri i bo a unit 4 women in agriculture
B.sc. agri i bo a unit 4 women in agricultureB.sc. agri i bo a unit 4 women in agriculture
B.sc. agri i bo a unit 4 women in agriculture
 
Nutrition Sensitive
Nutrition SensitiveNutrition Sensitive
Nutrition Sensitive
 
Master Seminar On ARYA: Luring Youth Back To Agriculture
Master Seminar  On  ARYA: Luring Youth Back To Agriculture Master Seminar  On  ARYA: Luring Youth Back To Agriculture
Master Seminar On ARYA: Luring Youth Back To Agriculture
 
Agricultural Innovation Systems: ‘Introduction 100,001’
Agricultural Innovation Systems: ‘Introduction 100,001’Agricultural Innovation Systems: ‘Introduction 100,001’
Agricultural Innovation Systems: ‘Introduction 100,001’
 
Gender and Climate Smart Agricultural Practices: Evidence from Bangladesh
Gender and Climate Smart Agricultural Practices: Evidence from BangladeshGender and Climate Smart Agricultural Practices: Evidence from Bangladesh
Gender and Climate Smart Agricultural Practices: Evidence from Bangladesh
 
Participatory extension.
Participatory extension.Participatory extension.
Participatory extension.
 
Livelihoods and Food Security
Livelihoods and Food SecurityLivelihoods and Food Security
Livelihoods and Food Security
 
Climate Smart Agriculture
Climate Smart AgricultureClimate Smart Agriculture
Climate Smart Agriculture
 
Multi-stakeholder platforms strengthening the selection and use of fodder opt...
Multi-stakeholder platforms strengthening the selection and use of fodder opt...Multi-stakeholder platforms strengthening the selection and use of fodder opt...
Multi-stakeholder platforms strengthening the selection and use of fodder opt...
 
E-extension- C.Thatchinamoorthy Agricultural Extension
 E-extension- C.Thatchinamoorthy Agricultural Extension E-extension- C.Thatchinamoorthy Agricultural Extension
E-extension- C.Thatchinamoorthy Agricultural Extension
 
Role of Social media in extension
Role of Social media in extensionRole of Social media in extension
Role of Social media in extension
 
Role of rural youth in agriculture
Role of rural youth in agricultureRole of rural youth in agriculture
Role of rural youth in agriculture
 
rapid rural appraisal and participatory rural appraisal
rapid rural appraisal and participatory rural appraisalrapid rural appraisal and participatory rural appraisal
rapid rural appraisal and participatory rural appraisal
 

Viewers also liked

UN Day of Families 2014
UN Day of Families 2014UN Day of Families 2014
DH 150 Final Project Presentation
DH 150 Final Project PresentationDH 150 Final Project Presentation
DH 150 Final Project Presentation
Stephanie Wong
 

Viewers also liked (10)

New maina
New mainaNew maina
New maina
 
Amnesty International Facebook campaign
Amnesty International Facebook campaignAmnesty International Facebook campaign
Amnesty International Facebook campaign
 
The change initiative
The change initiativeThe change initiative
The change initiative
 
The great invocation
The great invocationThe great invocation
The great invocation
 
A strategy for mainstreaming gender: An example from a dairy feed value chain...
A strategy for mainstreaming gender: An example from a dairy feed value chain...A strategy for mainstreaming gender: An example from a dairy feed value chain...
A strategy for mainstreaming gender: An example from a dairy feed value chain...
 
UN Day of Families 2014
UN Day of Families 2014UN Day of Families 2014
UN Day of Families 2014
 
DH 150 Final Project Presentation
DH 150 Final Project PresentationDH 150 Final Project Presentation
DH 150 Final Project Presentation
 
2015 Upload Campaigns Calendar - SlideShare
2015 Upload Campaigns Calendar - SlideShare2015 Upload Campaigns Calendar - SlideShare
2015 Upload Campaigns Calendar - SlideShare
 
What to Upload to SlideShare
What to Upload to SlideShareWhat to Upload to SlideShare
What to Upload to SlideShare
 
Getting Started With SlideShare
Getting Started With SlideShareGetting Started With SlideShare
Getting Started With SlideShare
 

Similar to Key livelihood and gender issues in livestock

Similar to Key livelihood and gender issues in livestock (20)

Livestock ownership, market participation and household cash income
Livestock ownership, market participation and household cash incomeLivestock ownership, market participation and household cash income
Livestock ownership, market participation and household cash income
 
Breeding systems
Breeding systemsBreeding systems
Breeding systems
 
Jon Hoek - Transparency and Agri-Tourism
Jon Hoek - Transparency and Agri-TourismJon Hoek - Transparency and Agri-Tourism
Jon Hoek - Transparency and Agri-Tourism
 
Goats: Sustainable Production Overview
Goats: Sustainable Production OverviewGoats: Sustainable Production Overview
Goats: Sustainable Production Overview
 
Dairy sector in India: Changing dynamics
Dairy sector in India: Changing dynamicsDairy sector in India: Changing dynamics
Dairy sector in India: Changing dynamics
 
Economic Analysis of Challenges in Development of High-Value Agriculture: The...
Economic Analysis of Challenges in Development of High-Value Agriculture: The...Economic Analysis of Challenges in Development of High-Value Agriculture: The...
Economic Analysis of Challenges in Development of High-Value Agriculture: The...
 
Reproduction and the Bottom Line
Reproduction and the Bottom LineReproduction and the Bottom Line
Reproduction and the Bottom Line
 
Dairy Cattle Husbandry
Dairy Cattle HusbandryDairy Cattle Husbandry
Dairy Cattle Husbandry
 
Insects as human food
Insects as human foodInsects as human food
Insects as human food
 
Animal fattening and fodders
Animal fattening and foddersAnimal fattening and fodders
Animal fattening and fodders
 
Use of artcificial insemination to improve goat meat production in nepal. n. ...
Use of artcificial insemination to improve goat meat production in nepal. n. ...Use of artcificial insemination to improve goat meat production in nepal. n. ...
Use of artcificial insemination to improve goat meat production in nepal. n. ...
 
Goat breeds of india history, development and classification
Goat breeds of india   history, development and classificationGoat breeds of india   history, development and classification
Goat breeds of india history, development and classification
 
Characterization of local chicken production and management systems in Babati...
Characterization of local chicken production and management systems in Babati...Characterization of local chicken production and management systems in Babati...
Characterization of local chicken production and management systems in Babati...
 
Morphometric characteristics and a little about performance –barbari and chokla
Morphometric characteristics and a little about performance –barbari and chokla Morphometric characteristics and a little about performance –barbari and chokla
Morphometric characteristics and a little about performance –barbari and chokla
 
Animal production for pigs
Animal production for pigsAnimal production for pigs
Animal production for pigs
 
A framework for exploring rural futures through collective learning. M Wedder...
A framework for exploring rural futures through collective learning. M Wedder...A framework for exploring rural futures through collective learning. M Wedder...
A framework for exploring rural futures through collective learning. M Wedder...
 
Gender in Smallholder Pig Value Chains—ILRI approach Uganda
Gender in Smallholder Pig Value Chains—ILRI approach UgandaGender in Smallholder Pig Value Chains—ILRI approach Uganda
Gender in Smallholder Pig Value Chains—ILRI approach Uganda
 
Internal Parasite Management in Pasture-Based Sheep
Internal Parasite Management in Pasture-Based SheepInternal Parasite Management in Pasture-Based Sheep
Internal Parasite Management in Pasture-Based Sheep
 
Presentation dhaka2
Presentation dhaka2Presentation dhaka2
Presentation dhaka2
 
Experiences with breeding structures for genetic improvement of small ruminants
Experiences with breeding structures for genetic improvement of small ruminants Experiences with breeding structures for genetic improvement of small ruminants
Experiences with breeding structures for genetic improvement of small ruminants
 

More from ILRI

More from ILRI (20)

How the small-scale low biosecurity sector could be transformed into a more b...
How the small-scale low biosecurity sector could be transformed into a more b...How the small-scale low biosecurity sector could be transformed into a more b...
How the small-scale low biosecurity sector could be transformed into a more b...
 
Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...
Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...
Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...
 
Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...
Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...
Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...
 
A training, certification and marketing scheme for informal dairy vendors in ...
A training, certification and marketing scheme for informal dairy vendors in ...A training, certification and marketing scheme for informal dairy vendors in ...
A training, certification and marketing scheme for informal dairy vendors in ...
 
Milk safety and child nutrition impacts of the MoreMilk training, certificati...
Milk safety and child nutrition impacts of the MoreMilk training, certificati...Milk safety and child nutrition impacts of the MoreMilk training, certificati...
Milk safety and child nutrition impacts of the MoreMilk training, certificati...
 
Preventing the next pandemic: a 12-slide primer on emerging zoonotic diseases
Preventing the next pandemic: a 12-slide primer on emerging zoonotic diseasesPreventing the next pandemic: a 12-slide primer on emerging zoonotic diseases
Preventing the next pandemic: a 12-slide primer on emerging zoonotic diseases
 
Preventing preventable diseases: a 12-slide primer on foodborne disease
Preventing preventable diseases: a 12-slide primer on foodborne diseasePreventing preventable diseases: a 12-slide primer on foodborne disease
Preventing preventable diseases: a 12-slide primer on foodborne disease
 
Preventing a post-antibiotic era: a 12-slide primer on antimicrobial resistance
Preventing a post-antibiotic era: a 12-slide primer on antimicrobial resistancePreventing a post-antibiotic era: a 12-slide primer on antimicrobial resistance
Preventing a post-antibiotic era: a 12-slide primer on antimicrobial resistance
 
Food safety research in low- and middle-income countries
Food safety research in low- and middle-income countriesFood safety research in low- and middle-income countries
Food safety research in low- and middle-income countries
 
Food safety research LMIC
Food safety research LMICFood safety research LMIC
Food safety research LMIC
 
The application of One Health: Observations from eastern and southern Africa
The application of One Health: Observations from eastern and southern AfricaThe application of One Health: Observations from eastern and southern Africa
The application of One Health: Observations from eastern and southern Africa
 
One Health in action: Perspectives from 10 years in the field
One Health in action: Perspectives from 10 years in the fieldOne Health in action: Perspectives from 10 years in the field
One Health in action: Perspectives from 10 years in the field
 
Reservoirs of pathogenic Leptospira species in Uganda
Reservoirs of pathogenic Leptospira species in UgandaReservoirs of pathogenic Leptospira species in Uganda
Reservoirs of pathogenic Leptospira species in Uganda
 
Minyoo ya mbwa
Minyoo ya mbwaMinyoo ya mbwa
Minyoo ya mbwa
 
Parasites in dogs
Parasites in dogsParasites in dogs
Parasites in dogs
 
Assessing meat microbiological safety and associated handling practices in bu...
Assessing meat microbiological safety and associated handling practices in bu...Assessing meat microbiological safety and associated handling practices in bu...
Assessing meat microbiological safety and associated handling practices in bu...
 
Ecological factors associated with abundance and distribution of mosquito vec...
Ecological factors associated with abundance and distribution of mosquito vec...Ecological factors associated with abundance and distribution of mosquito vec...
Ecological factors associated with abundance and distribution of mosquito vec...
 
Livestock in the agrifood systems transformation
Livestock in the agrifood systems transformationLivestock in the agrifood systems transformation
Livestock in the agrifood systems transformation
 
Development of a fluorescent RBL reporter system for diagnosis of porcine cys...
Development of a fluorescent RBL reporter system for diagnosis of porcine cys...Development of a fluorescent RBL reporter system for diagnosis of porcine cys...
Development of a fluorescent RBL reporter system for diagnosis of porcine cys...
 
Practices and drivers of antibiotic use in Kenyan smallholder dairy farms
Practices and drivers of antibiotic use in Kenyan smallholder dairy farmsPractices and drivers of antibiotic use in Kenyan smallholder dairy farms
Practices and drivers of antibiotic use in Kenyan smallholder dairy farms
 

Recently uploaded

Hyatt driving innovation and exceptional customer experiences with FIDO passw...
Hyatt driving innovation and exceptional customer experiences with FIDO passw...Hyatt driving innovation and exceptional customer experiences with FIDO passw...
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
FIDO Alliance
 
Harnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptx
Harnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptxHarnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptx
Harnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptx
FIDO Alliance
 
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdfBreaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
UK Journal
 
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
panagenda
 

Recently uploaded (20)

Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
 
Using IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & IrelandUsing IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & Ireland
 
TopCryptoSupers 12thReport OrionX May2024
TopCryptoSupers 12thReport OrionX May2024TopCryptoSupers 12thReport OrionX May2024
TopCryptoSupers 12thReport OrionX May2024
 
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
Hyatt driving innovation and exceptional customer experiences with FIDO passw...Hyatt driving innovation and exceptional customer experiences with FIDO passw...
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
 
Design Guidelines for Passkeys 2024.pptx
Design Guidelines for Passkeys 2024.pptxDesign Guidelines for Passkeys 2024.pptx
Design Guidelines for Passkeys 2024.pptx
 
Harnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptx
Harnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptxHarnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptx
Harnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptx
 
Working together SRE & Platform Engineering
Working together SRE & Platform EngineeringWorking together SRE & Platform Engineering
Working together SRE & Platform Engineering
 
How we scaled to 80K users by doing nothing!.pdf
How we scaled to 80K users by doing nothing!.pdfHow we scaled to 80K users by doing nothing!.pdf
How we scaled to 80K users by doing nothing!.pdf
 
Collecting & Temporal Analysis of Behavioral Web Data - Tales From The Inside
Collecting & Temporal Analysis of Behavioral Web Data - Tales From The InsideCollecting & Temporal Analysis of Behavioral Web Data - Tales From The Inside
Collecting & Temporal Analysis of Behavioral Web Data - Tales From The Inside
 
WebAssembly is Key to Better LLM Performance
WebAssembly is Key to Better LLM PerformanceWebAssembly is Key to Better LLM Performance
WebAssembly is Key to Better LLM Performance
 
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
 
The Value of Certifying Products for FDO _ Paul at FIDO Alliance.pdf
The Value of Certifying Products for FDO _ Paul at FIDO Alliance.pdfThe Value of Certifying Products for FDO _ Paul at FIDO Alliance.pdf
The Value of Certifying Products for FDO _ Paul at FIDO Alliance.pdf
 
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdfIntroduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
 
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdfBreaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
 
2024 May Patch Tuesday
2024 May Patch Tuesday2024 May Patch Tuesday
2024 May Patch Tuesday
 
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
 
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
 
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdfHow Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
 
Long journey of Ruby Standard library at RubyKaigi 2024
Long journey of Ruby Standard library at RubyKaigi 2024Long journey of Ruby Standard library at RubyKaigi 2024
Long journey of Ruby Standard library at RubyKaigi 2024
 
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdfLinux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
 

Key livelihood and gender issues in livestock

  • 1. Key Gender and Livelihood Issues in Livestock Production, Management and Marketing Jemimah Njuki Team Leader: Poverty, Gender and Impact FAO-ILRI Workshop on Integrating Gender in Livestock Projects and Programs, ILRI, Addis Ababa, 22-25 November 2011
  • 2. Key Gender and Livestock Issues • Livestock’s contribution to household assets • Livestock’s contribution to income • Patterns of livestock ownership • Men and Women’s role in livestock keeping • Access to services, information and technologies • Men and Women’s participation in livestock markets • Links between gender, livestock, food security, nutrition and health
  • 4. Livestock as an asset?  Livestock, especially small stock, form a critical rung on the asset ladder out of poverty  Livestock are among the few assets women can own  Livestock are “productive” assets; livestock and their products contribute to food and income security  Livestock as a social asset..
  • 5. Contribution of livestock to household assets • Livestock an important asset contributing 55% of the total asset index for all households (52.7% male headed households and 68% for female headed households) in Kenya • Similar trends in Tanzania, with livestock contributing to 69% of all households asset index, and 68% and 75% for male and female headed households respectively. Total domestic % of Total HH Total livestock and livestock livestock to Household Type index index index total index Kenya Male-headed 97.14 51.28 Kenya Men 41.01 21.5 Female-headed 43.07 29.31 Women 16.68 22.5 Total 83.35 45.67 Joint 60.35 36 Tanzania Male-headed 105.6 72.2 Tanzania Men 41.80 46.6 Female-headed 49.9 37.6 Women 11.42 18.3 Total 95.7 66 Joint 58.47 24.2 • Within male headed households, women held 10.2% and 13.9% of the total domestic and livestock assets in Tanzania and Kenya respectively. • For women, this represented 22.5% and 18.3% of the non land asset index under their ownership • Gender asset disparity of 0.27 in Tanzania and 0.41 in Kenya. This does not take into account jointly held assets
  • 6. Household ownership of livestock – Male and Female headed households • Local chickens and dairy cows were the most commonly owned livestock species in Kenya • In Tanzania, local chicken, goats and pigs were the most common species • There were no big differences in proportion of male and female headed households owning different species.
  • 7. Livestock holdings in male and female headed households Kenya Male- Female- • Female headed households had headed headed Livestock Mean Mean T- significantly smaller numbers of statistic cattle, chicken (local, improved) Bee Hives 3.71 3 0.966 Dairy Cattle 2.64 2.08 2.074** compared to their male Exotic chicken 187 14 2.487** counterparts (Broilers) Exotic chicken 56.32 11.4 2.26** (Layers) Goats 6.15 4.64 0.752 • Similar results in Tanzania Local chicken 13.43 8.98 1.859** Other cattle 2.47 2.75 -0.182 Pigs 6.33 5.5 0.195 Sheep 4.06 3.28 1.011
  • 8. Livestock ownership: Men and women within male headed households Kenya Tanzania Men and women in male headed Men and women in male headed households households Men Women Joint Livestock type Men women Jointly Bee Hives 3.8 1.3 3.5 Bee Hives 7.8 3.0 21.3 Dairy Cattle 3.0 1.5 2.6 Dairy Cattle 3.5 4.0 6.1 Exotic 8.0 350.0 191.0 Exotic chicken (Broilers) 258.0 156.7 100.0 (Broilers) Exotic 70.0 56.5 48.3 (Layers) Exotic chicken Goats 11.2 3.9 4.7 200.0 - 346.5 (Layers) Local chicken 19.1 15.7 9.9 Goats 8.6 3.4 8.9 Local chicken 22.8 39.7 23.3 Other cattle 1.7 1.0 2.7 Other cattle 9.1 2.0 5.4 Pigs 5.7 - 7.0 Pigs 4.0 2.4 4.1 Sheep 4.4 2.3 3.8 Sheep 5.2 6.0 6.3 In the two countries, women had lower numbers of every livestock species than men in male headed households with the exception of chicken in Kenya and Tanzania and Dairy in Tanzania.
  • 9. How do women gain and maintain control over livestock? • Women are less likely than men to acquire animals in the marketplace. • Threats: – Drought and disease – Dissolution of the household – Commercialization?
  • 10. Means of acquisition of livestock by women • Despite other evidence, across species, the main means of livestock acquisition by women was through purchase • In Tanzania, overall, about 50% of livestock owned by women was through purchase • For, goats, other cattle and local chicken, born into the herd was a common source for women
  • 11. Livestock as a source of income
  • 12. Contribution of livestock to household cash income • Livestock contributed 35% of cash income in Tanzania and 55% in Kenya • Contributed more to income in female headed households than male headed households • Variation in contribution by income quartile across the 2 countries
  • 13. Men and Women’s Roles in Livestock Keeping
  • 14. • Women provide a large share of the labor in livestock keeping, especially in mixed systems and poor households • Women’s priorities and constraints are often, but not always, different from men’s
  • 15. Women’s role in livestock keeping • Women often control 70 products even where 60 they don’t control 50 % housheolds 40 animals 30 • For example, women 20 10 often control some or 0 all milk even if they Morning Milk Male Female Mixed Evening Milk can’t decide where the cow is grazed or whether it is sold.
  • 16. Roles • Division of rights and responsibilities affects incentive and ability to adopt new technologies and practices to increase production and productivity. • We need to understand this better to develop appropriate technologies and design more effective interventions.
  • 17. Access to services, information and technologies
  • 18. Participation & registration in Cooperatives -Few dairy farmers registered in Cooperative Very few women participated in Cooperatives -None in Uganda -27% of registered members in Kenya
  • 19.
  • 20.
  • 21. Men and Women’s Participation in Livestock Markets
  • 22. Women’s participation in markets • Sale of livestock and livestock products are often an important source of income for women • Men and women face different constraints in marketing
  • 23. • Women are more likely to sell in informal, local markets • Women’s marketing costs are often higher than men’s: – Information—women face higher costs, but groups can help – Most often have to pay male intermediaries
  • 24. Who mainly sold livestock and livestock products? • High participation of women in sale of livestock products (eggs and milk) and very low participation in sale of livestock (cattle, sheep, goats) • Differentiation between ownership and management. Even in cases where women do not own the livestock, they are involved in the sale of products but not the sale of the livestock itself
  • 25. Common markets accessed by men and women- Tanzania
  • 26. Common markets accessed by men and women • Most commonly sold to markets by women were sales at farm gate to other farmers or traders (for chicken, eggs, milk and honey) • Women rarely made sales to city markets, or delivered to shops, collection centres or chilling plants ( milk) • Men made more deliveries to shops/ hotels /kiosks and other outlets • In Kenya women had more options for markets than in Tanzania • Chicken, eggs and milk had more market options than products such as honey
  • 27. Income management by men, women in male headed households • In Kenya, low income management by women across species and products • In Tanzania, more income from chicken, milk and honey managed by women compared to Kenya
  • 28. Variation in income share depending on where sold • Women managed a higher income share when product was sold at farm gate compared to when sold at village markets or delivered to traders • Differences less clear for sales of sheep, goats and cattle due to ownership patterns
  • 29. Variation in income share depending on who sold • When women sold (physically or did the transaction), they managed a higher income share (for both products and species)
  • 31. Gender, Livestock, and Nutrition "Even small additional amounts of meat and milk can provide the same level of nutrients, protein, and calories to the poor that a large and diverse amount of vegetables and cereals could provide” “The Cow Turns Green,” Newsweek, September 7, 2009 • Livestock ownership alone is not sufficient to ensure consumption of animal source foods (ASF) • Women play a key role in household choices about food consumption, dietary quality, and intra- household allocation. • Women’s status is key to making good choices here
  • 32. Women, Livestock and Health • Many important diseases are zoonotic, and food safety can be a major issue with animal source foods • A gendered risk assessment found: – Women’s higher exposure to high-risk activities such as feeding, milking, and cleaning of livestock – Women and men exposed to different diseases, by species – Women much more exposed to food-borne diseases because of role in food and by-product processing, food preparation, and selling ready to eat
  • 33. Livestock production and human nutrition? What do we know? Its complex! test Land allocation to feed - + - + Food crop Traction, nutrient production cycling + Animal & + + product sales Animal Food crop sales production + Animals + + owned HH + Labor allocated Income to livestock + Food crop purchases Health + + test + Chronic inputs disease risk + ASF purchases Probability of + zoonotic disease + HH ASF + Environmental toxin consumption + concentration + Water + contamination HH crop Food-borne consumption diseases + - - + + - - + Dietary - Human health Human intake status nutritional (growth) status + + + Total labor + Level of care/feeding demands behavior + Labor demands on (female) caregiver Figure. Hypothesized causal linkages between livestock keeping and human nutrition and health outcomes among the poor (adapted from Nicholson et al., 2003). ASF = animal-source food; HH = household (Randolph et al. 2007)
  • 34. Direct Nutrition Benefits  Intermediate determinants of child nutritional status  Breast Feeding and weaning practices  Food intake patterns and practices (diet diversity and food frequencies)  Intra-household food allocation  Nutrition knowledge, attitudes and practices
  • 35. Intensification and Household Consumption • Key indicators – Proportion of milk kept for consumption from total production – Proportion of evening milk kept for consumption Emerging Advanced Mean daily milk production, in liters 3.2 10.8 Mean daily milk consumption, in liters 2.0 4.9 Proportion of households keeping all of evening milk for 93.5 74.2 consumption
  • 36. GENDER, LIVESTOCK AND FOOD SECURITY Livestock and food security: Calculated variables • Household/Individual dietary diversity score (HDDS/IDDS) – Takes a value of 0-1 and is measured based on a 24 hour recall – Can also be used to calculate proportion of households consuming at least one animal source food per day • Food consumption score – Based on consumption of food groups – Each food group is weighted – Contribution of meat, fish and milk to the food consumption score • Months of adequate household food provisioning (MAHFP)- – Measured over a 12 month recall period
  • 37. Women’s ownership of livestock and food security Tanzania HDDS MIHFP • Women’s ownership women women of dairy cattle and women women do not do not own own T-values own own T-values chicken influenced livestock livestock livestock livestock HDDS in both Kenya Dairy cattle 0.69 0.55 1.44** 11 8.77 3.67 ** and Tanzania Exotic chicken 0.58 0.55 2.8 *** 11.5 8.77 5.08* Local chicken 0.63 0.55 0.92 8.84 8.67 0.416 Goats 0.51 0.56 0.35 8.5 8.83 0.51 • In Kenya ownership Kenya HDDS MIHFP of local chicken and women women t-values women women t-values goats also own do not own do not influenced HDDS livestock own livestoc own livestock k livestock Dairy cattle 0.73 0.65 3.105*** 4.3 5.8 2.272** Exotic chicken 0.82 0.66 4.376*** 3.7 5.5 1.689 Local chicken 0.71 0.66 2.118** 5.3 5.4 0.242 Goats 0.61 0.69 2.564** 5.1 5.4 0.403
  • 38. Household Economics  Changes in income and income share generated by dairy activities  Income expenditure on food  Allocation of milk production to own consumption vs sale
  • 39. Gender mediated interventions  Changes in women’s roles with introduction /intensification of livestock production especially in terms of time allocation (care giver time)  Decision making in relation to use of milk and income allocation  Expenditure patterns-food and health input purchases  Access to training, nutrition information, livestock assets
  • 40. Impact of Dairy on Primary Caregiver’s Time: Time spent on daily activities over intensification levels Average Time Spent on Daily Activities (in minutes) No Cow Emerging Advanced Childcare Activities 201.0 227.5 219.4 Income Generating 281.9 283.9 275.5 Activities Cattle Activities 15.3 112.1 56.9
  • 41. Public Health  Health related determinants of child nutritional status (healthcare expenditure and health seeking behaviour  Disease risk profiling  Syndromic surveillance  Access to public health services and information

Editor's Notes

  1. In Kenya, in 89%, 71% and 63% of the households eggs milk and chicken were mainly sold by women. In Tanzania, in 66.7%, 53.3% and 40.7% of the households, eggs, milk and chicken were mainly sold by women.In very few households did women sell live animals (11.1% for cattle and 8.8% for sheep and goats)
  2. For example 46% of income from milk was managed by women in Tanzania
  3. Present hypotheses first and the logic behind focus and hypotheses
  4. Slide on pathwayHypothesis of pathwayHow it was tested/key indicatorsFGD (overall conclusion and support from FGD and survey)QuantitativeConclusions<25 slides for the presentation