Information delivery, Nutrition and HIV Treatment: Evidence from a randomized field experiment on women living with HIV in UgandaPatrick Lubega, Frances Nakakawa, Gaia Narciso and Carol Newman

Information delivery, Nutrition and HIV Treatment: Evidence from a randomized field experiment on women living with HIV in Uganda

• The aim is to test the impact of interventions aimed at improving the nutrition of women living with HIV in Uganda.

• We are interested in testing:

1. Their impact on health and welfare outcomes

2. Their impact on behavior related to nutrition

3. Their impact on behavior related to self-employment activities

4. The mechanisms through which changes in behavior occur

• To achieve this we use a randomized controlled trial design

Background• Uganda’s national response to HIV/AIDS is recognised as strong and effective

• Prevalence rate is estimated at 7.4% (UNAIDS, 2014)

• Increased enrolment of people on ART from 570,373 in 2013 to 750,896 in 2014.

• However, an area in need of research is the relationship between HIV treatment outcomes and nutrition

• Ugandan Ministry for Health has produced a training manual to guide practitioners in the management of nutritional aspects of HIV care and provides information on when and how to use RUTFs in the setting of HIV and severe malnutrition.

• But, a significant percentage of those attending for treatment have mild to moderate malnutrition and do not receive supplementary feeding under the present criteria

Experimental designWe randomly selected 4 sub-regions of Uganda;

We randomly selected 24 clinics, 6 in each of the four sub-regions;

At baseline each clinic was visited for two days during the HIV; clinic to recruit participants;

On average 135 women recruited in each clinic;

Baseline survey instrument gathers information on:

» Personal characteristics of woman » Personal characteristics of family members» Food frequency questionnaire» Income » Agricultural production» Enterprise activity» Employment» Housing» Access to credit and savings behavior

Experimental design

• Two separate treatments are considered and randomization of baseline participants occurs at the clinic level;

• Each group includes 8 clinics and is evenly distributed across each of the 4 sub-regions.

Intervention

Group A Nutritional Information campaign

Group B Nutritional Information campaign + recipe demonstration

Group C Control group

Timeline

April-Sept 2014Baseline

Oct-Dec 2014Intervention 1

Jan – Mar 2015Intervention 2

Apr – May 2015Intervention 3/Evaluation 1

July-Aug 2015Evaluation 2

Details on interventions

Nutritional Information Campaign

‒ Delivered by clinic staff at each visit

‒ Content of campaign:

» Information leaflets and posters

» Hands off approach

» Allow clinics to do as they please in attempt to mimic typical campaigns by Ministry of Health

Treatment 1: Nutritional Information Campaign

Treatment 2: Recipe Demonstration

Locally sourced Home-made Nutritious Foods• Nutritionists working in each region to establish locally sourced ingredients

that can be used to prepare a Home-Made Nutritious Food.

• Products tested at Makerere University for nutrient content, taste and aesthetic appeal – similar to bringing product to market

• Intervention takes the form of cookery demonstrations

Outcomes

• Health and education

• Income and livelihoods

• Empowerment

• Anthropometrics

Using our RCT design we can obtain the average impact of a each intervention on outcomes for women in treated clinics by comparing them to the women in the control clinics

‒ Women in cookery clinics more likely to acknowledge that they received access to information.

‒ Positive impact of information only on number of meals per day only.

‒ Cookery has positive impact on number of snacks per day. This is consistent with trying the recipe.

‒ Cookery clinics more likely than information to try the recipe

Behavioural change due to information delivery

Health and education

‒ Lower probability of reporting illness in both information and cookery clinics – effect is bigger in cookery

‒ Lower proportion of children in the household reported as being sick in cookery (no effect of information alone)

‒ Cookery reduces the proportion of children that are absent from school because of failure to pay school fees (no effect of information alone)

Questions: What is mechanism? Is the better well-being of women in the cookery clinics impacting on incomes?

Income and livelihoods

• Cookery has positive impact on

‒ all types of personal income

‒ household income

‒ the decision to start an enterprise.

• This suggests that the increase in well-being associated with the cookery campaign leads to greater earning ability of women.

• This allows them to pay school fees and reduces the proportion of days that children are absent from school.

• The information campaign also increases the health of women possibly because they eat more frequent meals. There are no knock on effects for children or effects on other outcomes such as income.

Income and livelihoods

These results raise new questions

The fact that the same welfare outcomes are not observed in information clinics means that there is something different about the cookery clinics.

There are two possibilities:

i. they become super-nourished because they are eating the recipes

ii. there is something about the way the information is delivered that empowers women to work harder.

Empowerment

‒ We find an increase in control over personal resources in cookery clinics coupled with a decline in the joint control of personal finances

Anthropometrics

Decline in anthropometrics in cookery clinics.

Question: They are working harder so they are losing weight. But overall they are feeling better.

• Is it diversity in diet?

• Consumption of micronutrients?

• More analysis needed.

Conclusions

• Lower probability of reporting illness in both information and cookery clinics – effect is bigger in cookery

• Lower proportion of children in the household reported as being sick in cookery

• Cookery reduces the proportion of children that are absent from school because of failure to pay school fees (no effect of information alone)

• Cookery has positive impact on

‒ all types of personal income

‒ household income

‒ the decision to start an enterprise.

Conclusions

• This suggests that the increase in well-being associated with the cookery campaign leads to greater earning ability of women.

• This allows them to pay school fees and reduces the proportion of days that children are absent from school.

• The information campaign also increases well-being of women but with no knock on effects for children or other welfare outcomes

• Some evidence of increase in control over personal resources in cookery clinics coupled with decline in joint control of personal finances

• Decline in anthropometrics in cookery clinics

Thank You!

Appendix

Econometric specification

is the particular outcome variable of interest for woman i in time period t;

is a dummy indicator for whether woman i is in an information clinic;

is a dummy indicator for whether woman i is in a cookery clinic;

is a dummy indicator for the time period – zero for the baseline and one for the evaluations;

is a vector of time varying control variables;

are woman fixed effects.

1 1 2( * ) ( * )it t i t i t i itO Time Info Time Cook Time itφX

itO

tTime

iInfo

iCook

itφX

i

Behavioural change in relation to information contained in campaign

  (1) (2) (3) (4) (5) (6)  Access to

InformationMeals Snacks Litres of

waterTreated Water Recipe

             Eval*info 0.071 0.182* 0.445 0.271 0.081    (0.176) (0.076) (0.116) (0.104) (0.338)  Eval*cook 0.234*** 0.132 0.609* -0.052 0.038 0.534***  (0.000) (0.214) (0.012) (0.681) (0.083) (0.000)

Evaluation dummy Yes Yes  Yes  Yes   Yes  NoIndividual FE Yes Yes Yes Yes Yes NoControls Yes Yes Yes Yes Yes Yes             Mean control baseline 0.824 2.464 1.125 2.202 0.793 N.A.

Observations 3,900 3,899 3,901 3,905 3,877 1,346R-squared 0.067 0.040 0.086 0.020 0.049 0.262Number of Ind. 1,966 1,966 1,966 1,966 1,966  

Standard errors computed using wild bootstrapping to account for clustering at the clinic level (Cameron, Gelbrach, and Miller, 2008). p-values in parenthesis. *** p<0.01, ** p<0.05, * p<0.1

Health and education  (1) (2) (3) (4) (5)

  Sick % child sick % child absent school

Child absent - school fees

Child absent - sick

           Eval*info -0.085* -0.058 -0.039 -0.047 0.015

  (0.092) (0.116) (0.451) (0.262) (0.539)

Eval*cook -0.145** -0.072** -0.087 -0.048* 0.034

  (0.012) (0.034) (0.136) (0.094) (0.186)

Evaluation dummy Yes  Yes Yes Yes YesIndividual FE Yes Yes Yes Yes Yes

Controls Yes Yes Yes Yes Yes

           Mean control baseline 0.272 0.102 0.362 0.227 0.172

Observations 3,897 2,800 2,800 2,800 2,800

R-squared 0.026 0.021 0.023 0.042 0.010

Number of Ind. 1,966 1,615 1,615 1,615 1,615

Standard errors computed using wild boostrapping to account for clustering at the clinic level (Cameron, Gelbrach, and Miller, 2008). p-values in parenthesis. *** p<0.01, ** p<0.05, * p<0.1

Income and livelihoods  (1) (2) (3) (4) (5) (6) (7)  Personal

incomeOther household

incomeWage income Crop income Livestock

incomeEnterprise

incomeOperates enterprise

               

Eval*info -11,742 -3,760 -2,958 9,182 -2,779 4,560 -0.027

  (0.342) (0.631) (0.288) (0.326) (0.322) (0.511) (0.575)

Eval*cook 47,917*** 26,932* 6,621** 17,321* 2,545* 15,722** 0.283***

  (0.000) (0.086) (0.022) (0.060) (0.052) (0.044) (0.002)

Evaluation dummy Yes Yes Yes Yes Yes Yes Yes

Individual FE Yes Yes Yes Yes Yes Yes Yes

Controls Yes Yes Yes Yes Yes Yes Yes               

Mean control baseline 83,071 50,601 22,154 26,510 5402 19,157 0.262

Observations 3,910 3,910 3,910 3,910 3,910 3,910 3,892

R-squared 0.024 0.029 0.019 0.019 0.013 0.012 0.088

Number of Ind. 1,966 1,966 1,966 1,966 1,966 1,966 1,965

Standard errors computed using wild boostrapping to account for clustering at the clinic level (Cameron, Gelbrach, and Miller, 2008).p-values in parenthesis. *** p<0.01, ** p<0.05, * p<0.1

Empowerment  (1) (2) (3) (4) (5) (6)

  Makes decisions about personal income alone

Husband makes decisions about personal income

Jointly make decisions about personal income

Makes decisions about household

income alone

Husband makes decisions about

household income

Jointly make decisions about

household income

             Eval*info 0.059 0.004 -0.050 0.106 0.012 -0.002

  (0.190) (0.809) (0.266) (0.394) (0.929) (0.947)

Eval*cook 0.214*** -0.009 -0.189*** -0.160 0.067 0.034

  (0.000) (0.400) (0.002) (0.136) (0.483) (0.727)

Evaluation dummy Yes Yes Yes Yes Yes Yes

Individual FE Yes Yes Yes Yes Yes Yes

Controls Yes Yes Yes Yes Yes Yes

             Mean control baseline 0.794 0.050 0.156 0.213 0.328 0.431

Observations 1,197 1,197 1,197 961 961 961

R-squared 0.159 0.028 0.152 0.103 0.026 0.026

Number of Ind. 611 611 611 587 587 587

Standard errors computed using wild boostrapping to account for clustering at the clinic level (Cameron, Gelbrach, and Miller, 2008).p-values in parenthesis. *** p<0.01, ** p<0.05, * p<0.1

Anthropometrics  (1) (2) (3)

  BMI Upper-arm Waist

       

Eval*info -0.410 -0.125 -0.450

  (0.268) (0.775) (0.605)

Eval*cook -0.912*** -0.596 -3.088***

  (0.006) (0.108) (0.010)

Evaluation Dummy Yes Yes Yes

Individual FE Yes Yes Yes

Controls Yes Yes Yes

       

Mean control baseline 22.27 27.22 80.57

Observations 3,862 3,871 3,696

R-squared 0.032 0.093 0.114

Number of Ind. 1,964 1,962 1,908

Standard errors computed using wild boostrapping to account for clustering at the clinic level (Cameron, Gelbrach, and Miller, 2008).p-values in parenthesis. *** p<0.01, ** p<0.05, * p<0.1