Health education impact on knowledge and management of arboviral diseases in Kenya: Evidence from randomised control trials

Figures & data

Figure 1. Health education training sites in Baringo, Kwale, and Kilifi Counties, Kenya. Source: icipe GIS unit.

Table 1. Baseline household socio-demographic characteristics.

Variables	Means			t-Test value
	Pooled sample (n = 629)	Control (n = 256)	Treatment (n = 373)
Household demographic characteristics
Education of household head (years)	6.88	7.02	6.79	0.674
	(4.20)	(4.10)	(4.28)
Gender (proportion of male heads-%)	81.56	82.81	80.70	0.671
Religion (1 = Yes, 0 = No)
Others	0.18	0.27	0.13	1.255
Christianity	0.63	0.71	0.57	3.290***
Islam	0.35	0.26	0.41	−3.700***
Access to information
Experience
Proportion of households that suffered from RVF (%)	29.78	23.53	34.43	−2.113**
Proportion of households that suffered from chikungunya fever (%)	46.88	34.17	54.92	−3.533**
Proportion of households that suffered from dengue fever (%)	22.79	21.95	23.16	−0.153
Distance to the nearest health facility in walking minutes	31.67	40.55	25.58	6.326***
Social capital
Group membership (proportion of households belonging to a health promotion group)	7.15	6.64	7.51	−0.413
Asset endowment
Livestock ownership (tropical livestock units – TLU)	3.69	2.45	4.54	−2.824**
	(9.18)	(5.93)	(10.78)
Income from all enterprises (1000 KES)	142.70	138.44	145.63	−0.284
	(312.44)	(247.73)	(350.29)

Notes: Standard deviation in parenthesis; 1US$ = KES 102 at the survey time; *** and ** show that the mean values for training participants are significantly different from those of non-participants at the 1% and 5% levels, respectively.

Figure 2. Trends in AD knowledge and management scores before and after treatment.

Table 2. Changes in knowledge and management scores before and after training.

		Baringo			Kwale			Kilifi
		Baseline	Follow-up	Change	Baseline	Follow-up	Change	Baseline	Follow-up	Change
Knowledge	RVF	0.393	0.415	0.022*	0.080	0.404	0.324***	0.216	0.341	0.125***
		(0.120)	(0.111)		(0.031)	(0.206)		(0.179)	(0.172)
	Chikungunya fever	0.429	0.487	0.058	0.415	0.612	0.197***	0.333	0.577	0.244***
		(0.000)	(0.126)		(0.131)	(0.199)		(0.148)	(0.193)
	Dengue fever	–	0.399	–	0.324	0.545	0.221***	0.321	0.472	0.151***
			(0.090)		(0.140)	(0.176)		(0.201)	(0.159)
Management	RVF	0.200	0.431	0.231***	0.204	0.546	0.342***	0.203	0.485	0.282***
		(0.139)	(0.156)		(0.147)	(0.188)		(0.163)	(0.170)
	Chikungunya fever	0.286	0.561	0.275	0.447	0.612	0.165***	0.346	0.558	0.212***
		(0.000)	(0.165)		(0.189)	(0.155)		(0.175)	(0.153)
	Dengue fever	–	0.563	–	0.381	0.621	0.240***	0.319	0.557	0.238***
			(0.158)		(0.185)	(0.153)		(0.187)	(0.156)

Notes: Standard deviation in parenthesis. * = significant at p < 0.1; *** = significant at p < 0.00.

Table 3. Double robust DiD estimates of the effect of health education training on the intensity of knowledge and management of ADs in Kenya.

Variables	RVF				Chikungunya fever				Dengue fever
	Knowledge		Management		Knowledge		Management		Knowledge		Management
Post*Treat	0.077**	0.094***	0.039	0.043	0.061**	0.097**	0.008	0.038	0.131***	0.148***	−0.032	0.002
	(0.024)	(0.026)	(0.024)	(0.028)	(0.026)	(0.036)	0.028	(0.038)	(0.037)	(0.037)	(0.037)	(0.043)
Baseline controls	No	Yes	No	Yes	No	Yes	No	Yes	No	Yes	No	Yes
Location-fixed effects	No	Yes	No	Yes	No	Yes	No	Yes	No	Yes	No	Yes
Observations	688		682		682		682		371		371

Notes: Coefficient estimates are shown with robust standard errors clustered at the household level in parentheses. Inverse probability weighting was used to control for attrition. Post*Treat is an interaction term, a dummy variable that takes a value of 1 for follow-up round observations (after treatment) and zero for baseline observations. Baseline controls include household demographic characteristics (education, gender, and religion), access to health information (experience and distance to health facility), social capital (group membership), and asset endowment (livestock units and income). Location-fixed effects (county) were also included in the model. ** = significant at p < 0.05; *** = significant at p < 0.00.

Table A1. Attrition rates across treatment and control groups.

	Baseline number (%)	Follow-up number (%)	Attriting number (%)
Control	256 (40.70)	228 (39.72)	28 (10.94)
Treatment	373 (59.30)	346 (60.26)	27 (7.24)
Observations	629 (100)	574 (100)	55 (8.74)

Table A2. Attrition probit regressions.

Variables	Treatment	Control	Full sample
	Attrition	Attrition	Attrition
Treatment			−0.376**
			(0.149)
Education	0.010	−0.004	−0.000
	(0.024)	(0.031)	(0.018)
Gender	0.106	0.084	0.020
	(0.269)	(0.306)	(0.198)
Christianity^a	−1.250*	0.029	−0.288
	(0.738)	(0.647)	(0.470)
Islam^a	−1.526*	−0.066	−0.476
	(0.808)	(0.733)	(0.636)
Experienced RVF	0.014	−0.010	0.075
	(0.285)	(0.417)	(0.239)
Experienced chikungunya fever	1.027**	0.051	0.263
	(0.327)	(0.296)	(0.183)
Experienced dengue fever	0.075*	−0.306	0.282
	(0.394)	(0.594)	(0.320)
Distance	0.030	−0.076	−0.026
	(0.134)	(0.126)	(0.087)
Group membership	−0.158	–	−0.625
	(0.488)		(0.434)
Livestock units	−0.007	−0.063	−0.007
	(0.008)	(0.042)	(0.008)
Income	−0.040	−0.004	−0.014
	(0.067)	(0.065)	(0.046)
Kwale^b	−1.151**	0.373	−0.060
	(0.495)	(0.584)	(0.544)
Kilifi^b	−1.089***	0.340	−0.026
	(0.303)	(0.337)	(0.211)
Constant	0.232	−1.024	−0.620
	(1.225)	(1.089)	(0.790)
Pseudo R-squared	0.112	0.039	0.039
Observations	373	239	629

Notes: Coefficient estimates are shown with robust standard errors clustered at farmer group level in parentheses. ^aOther religions and ^bBaringo County are the reference. *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.