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  • Open Access

Education attainment of head of households associated with insecticide-treated net utilization among five to nineteen-year old individuals: evidence from the malaria indicator survey 2010 in Zambia

  • 1, 2Email author,
  • 1,
  • 1 and
  • 3
Malaria Journal201413:378

https://doi.org/10.1186/1475-2875-13-378

  • Received: 24 July 2014
  • Accepted: 18 September 2014
  • Published:

Abstract

Background

Education attainment may be a factor potentially influencing health-seeking behaviour of individuals. The effect of the level of education attainment of head of households of five to nineteen year old individuals in Zambia on ITN utilization was investigated.

Methods

Data stem from the 2010 Malaria Indicator Survey, which covered the entire Zambia, was used in this study. Of the total number of five to 19-year olds (n = 7,429), only 65% (4, 810) met the inclusion criteria for this study. The education level of the head of households was taken as a household variable and was categorized as "never been to school" for those who had never enrolled in school, Primary for Grades 1 to 7, Secondary for Grades 8 to 12 and Tertiary for beyond Grade 12. Multivariate Logistic regression was used to determine adjusted odds ratios that estimated the effect of education on ITN utilization after controlling for residence, sex, age group and other background factors.

Results

Overall (n = 4,810), 48.5% were males and 51.5% were females with the median age of 10 years and 11 years respectively. The ITN utilization among the five to 19 year old individuals from households with the head having Primary and Secondary education were not statistically significant from those who came from households where the head had never been to school. However, those who came from households with the head having tertiary education attainment were 1.7 times more likely to have slept under an ITN a night before the survey than those from households headed by individuals who never attended school or had primary education. (AOR, 1.69; 95% CI, 1.19-2.41). Of the eligible population, 35% were excluded from the study due to incomplete records.

Conclusion

The findings suggest that tertiary education of the head of head of the household might be important in influencing health behaviour of the members of households. Therefore, health education messages focussing on strategies that aim to increase ITN utilization need to account for these differential variations associated with education attainment in communities.

Keywords

  • Malaria
  • Insecticide-Treated Nets (ITNs)
  • Malaria Indicator Survey (MIS)

Background

Insecticide-treated nets (ITNs) have been found to reduce all forms of child mortality by 16% in most African settings making it an effective intervention for the control of malaria transmission by Anopheles mosquitoes[1]. However, high coverage and utilization rates are required for ITNs to make a substantial impact on the prevention of malaria transmission. In order to achieve this, the Government of the Republic of Zambia, in collaboration with cooperating partners embarked on distribution of free ITNs throughout the country. This led to an increase in the number of households owning at least one ITN from 13.6% in 2001 to 35% in 2005 and 64% in 2010[2]. The current national policy on ITNs is to have all sleeping spaces available in the households covered by ITNs in order to increase the levels of utilization. This is a shift from making ITNs only available to pregnant women and under-five children to all at risk of malaria.

The Ministry of Health had, therefore, set a target to have 80% of the households owning at least one ITN and to increase the level of utilization to 75% by 2012[3]. Although there has been an increase in the ITN coverage rates over the years, the ITN utilization trend by age group shows that five to 19-year old individuals are least likely to sleep under an ITN[4, 5] despite making up about 40% of the Zambian population[6]. This implies that the larger number of people at risk of malaria still remain unprotected by ITNs. Articles that have been published on the determinants of ITN utilization have focused more on pregnant women and under-five children[7, 8].

This study was aimed to identify if education attainment among household heads is associated with ITN utilization among five to 19-year olds in Zambia. The higher goal was to inform programming and associated intervention strategies.

Methods

Design

Data stem from the 2010 Malaria Indicator Survey (MIS) conducted in Zambia as part of national malaria surveillance programme. The MIS was a nationally representative cross-sectional survey that was conducted in April and May of 2010 in Zambia using a two cluster sampling approach. The objective of the survey was to monitor and evaluate the coverage and use of malaria intervention programmes that were being implemented such as ITNs, Indoor Residue Spraying (IRS), anti-malarial drugs and estimation of the prevalence of fever, malaria parasitaemia and anaemia.

The country was stratified into rural, urban and new IRS strata. The first stage involved selection of clusters using probability proportional to size and the second stage involved selection of households within selected clusters using systematic sampling method. A representative sample of 4,500 households was selected for the whole country. The full details of the survey have been described elsewhere[5].

Data collection

Household and women questionnaires were used to collect socio-demographic as well as utilization data. The household questionnaire was administered to the head of each of the selected households and it was used to list all the members of the household and valuable goods in the household. This helped in identifying women aged 15 to 49 years who answered the women questionnaire. The head of the household answered questions on behalf of all household members including those relating to ITN ownership and usage among all household members. The women questionnaire was used to collect information from women aged 15 to 49 years about general malaria knowledge and also information related to access to information about malaria.

Data analysis

Data was analysed using Stata® Version 11 (Stata Corporation, College Station, Texas). The analysis was restricted to five to nineteen year old individuals who came from households that had at least one ITN and a woman who was interviewed. The goal was to find out the proportion of individuals aged five to nineteen years who slept under an ITN a night before the survey. This information was given by the head of the household and was available for all the household members. The outcome factor was examined against its association with various personal and household factors. Personal factors examined were sex, residence and region while household factors included education level of the head of household, wealth index, and number of ITNs, age of the head of the household, presence of under-five children and presence of under five children who slept under an ITN the night before the survey. Education attainment of the head of the household was measured using the number of formal school years the respondent spent in school. This was categorized into four as follows; Never been to school for those who had no formal education, Primary level from Grades one to seven, Secondary level from Grades eight to twelve and Tertiary level for above Grade Twelve.

The first step involved using bivariate cross tabulation analysis where each of the individual and or household characteristics were tested to what extent they were associated with ITN utilization and the mantel-Haenszel (chi-square) test for overall degree of association was used for this measure.

Multiple Logistic regression analyses were used to assess and estimate the specific changes in odds among all the included individual and household factors on ITN utilization. The distribution of age as a continuous variable conformed to normality as assessed by probability plots. Interactions were looked for using the likelihood ratio test. Model diagnostics were done using the Maximum Likelihood Estimation (MLE) and the Hosmer-Lemeshow goodness-of-fit. The variables in the model were age, sex, residence and region while household variables included education level of the head of household, wealth index, number of ITNs, age of the head of household, presence of under-five children and presence of under-five children who slept under an ITN the night before the survey.

Ethics

Prior to the survey, the Research Ethics Committee of the University of Zambia reviewed and approved the protocol. Permission was sought from the Ministry of Health to use the MIS 2010 dataset for this study and ethical clearance was obtained from the Research Ethics Committee of the University of Zambia for the protocol to conduct secondary data analysis for MIS 2010. Written informed consent was obtained from parents or guardians for the publication of this report and any accompanying images.

Results

Participation and distribution

Overall (n = 4, 810), 48.5% were males. The majority (68.2%) of the participants came from rural areas while 31.8% came from urban areas (Table 1). Copperbelt province contributed the highest number of participants (18.8%) while North Western had the least (5.5%). The mean age was 10.9 years and standard deviation was 4.2 years. Non-participation (35%) was largely due to incomplete records.
Table 1

Distribution of socio demographic characteristics in 2010 malaria indicator survey in Zambia

Characteristic

Category

Proportion (percent) n = 4810

Sex

Male

48.5%

 

Female

51.5%

Residence

Rural

31.8%

 

Urban

68.2%

Region

Luapula

6.8%

 

Central

10.9%

 

Copperbelt

18.8%

 

Eastern

16.5%

 

Lusaka

10.2%

 

North Western

5.5%

 

Northern

10.8%

 

Southern

12.5%

 

Western

8.1%

Age group (yrs)

5-9

41.8%

 

10-14

34.7%

 

15-19

23.5%

Gender of head of household

Male

79.6%

 

Female

20.4%

Wealth quintile

Lowest

20.1%

 

Second

12.5%

 

Middle

19.5%

 

Fourth

23.1%

 

Highest

24.8%

Ratio of nets to sleeping spaces

Not all spaces covered

54.5%

 

All spaces covered

45.5%

Education level of head of household

Never attended school

7.5%

 

Primary

41.3%

 

Secondary

39.4%

 

Tertiary

11.8%

Age of head household (yrs)

<25

3.4%

 

25-34

22.0%

 

35-44

36.5%

 

45-59

29.9%

 

60+

8.2%

Number of ITNs

1

34.0%

 

2

32.2%

 

3 or more

33.8%

Women knowledge on malaria

The majority (69.9%) came from households where the women knew that sleeping under an ITN protects against malaria. Of the study participants, 80.5% came from households where women knew that malaria parasite is transmitted by mosquitoes. The higher number of the participants (95.6%) had reported not having received health education about malaria at home.

The bivariate analysis showed that education level of the head of the household was associated with ITN utilization among five to19-year olds (p = 0.013) as shown in Table 2.
Table 2

Distribution of number of 5–19 year olds who slept under ITN in households with at least one ITN

Characteristic

Slept under ITN last night

Significance (p-value) using chi square test

  

Yes n(%)

No n(%)

 

Sex

Male

928(39.8)

1 404(60.2)

0.001

 

Female

1 095(44.2)

1 383(55.8)

 

Residence

Rural

552(36.1)

978(63.9)

0.005

 

Urban

1 471(44.8)

1 809(55.2)

 

Region

Luapula

91(28.0)

234(72.0)

0.000

 

Central

236(44.9)

289(55.1)

 
 

Copperbelt

336(37.1)

570(62.9)

 
 

Eastern

429(54.1)

364(45.9)

 
 

Lusaka

151(30.9)

338(69.1)

 
 

North Western

136(51.7)

127(48.3)

 
 

Northern

252(48.3)

270(51.7)

 
 

Southern

207(34.7)

390(65.3)

 
 

Western

185(47.4)

205(52.6)

 

Age group (yrs)

5-9

932(46.3)

1 080(53.7)

0.000

 

10-14

647(38.8)

1 022(61.2)

 
 

15-19

444(39.3)

685(60.7)

 

Number of 5–19 headed by Male or Female

Male

1 618(42.2)

2 213(57.8)

0.934

 

Female

405(41.4)

574(58.6)

 

Wealth quintile

Lowest

391(40.4)

576(59.6)

0.465

 

Second

293(48.8)

307(51.2)

 
 

Middle

407(43.4)

531(56.6)

 
 

Fourth

450(40.4)

663(59.6)

 
 

Highest

482(40.4)

710(59.6)

 

Ratio of nets to sleeping spaces

Inadequate nets

653(24.9)

1 969(75.1)

0.000

 

Adequate nets

1 370(62.6)

818(37.4)

 

Education level of head of household

Never attended school

150(41.8)

209(58.2)

0.013

 

Primary

819(41.2)

1 168(58.8)

 
 

Secondary

764(40.3)

1 130(59.7)

 
 

Tertiary

290(50.9)

280(49.1)

 

Age group household head (years)

<25

95(57.6)

70(42.4)

0.001

 

25-34

508(48.0)

551(52.0)

 
 

35-44

734(41.8)

1 020(58.2)

 
 

45-59

514(35.8)

922(64.2)

 
 

60+

172(43.4)

224(56.6)

 

Number of ITNs

1

268(16.4)

1 366(83.6)

0.000

 

2

773(50.0)

774(50.0)

 
 

3 or more

982(60.3)

647(39.7)

 
Multivariate logistic regression analysis was used to determine the effect of level of education of the head of the household on ITN utilization among five to 19-year olds from households with at least one ITN putting into account effect of survey settings (Table 3). The model was controlled for covariates that were significant at (p < 0.05) in the bivariate analysis. These covariates were sex, residence, region, age group of individuals, age group of the head of household, number of households with under-fives who slept under ITNs, number of ITNs and ratio of ITNs to sleeping spaces in households. There was no significant difference in ITN utilization between individuals who came from the household where the head of the households had secondary education (AOR = 1.15; 95% CI 0.89-1.49) and those from households where the head of households had primary level or had never been to school. However, individuals from households with tertiary education attainment for the head of the household were 1.7 times more likely to have slept under an ITN than those from households were the head had primary or never been to school (OR = 1.69; 95% CI 1.19-2.41).
Table 3

Logistic regression of predictors of 5–19 year old sleeping under an ITN a night before the survey in households with at least one ITN

Characteristic

AOR (95% CI)

Sex

Male

1.00

 

Female

1.36(1.17-1.58)

Number of ITNs

1

1.00

 

2

3.94(3.02-5.13)

 

3 or more

5.11(3.63-7.20)

Region

Luapula

1.00

 

Central

1.54(1.01-2.33)

 

Copperbelt

1.22(0.77-1.93)

 

Eastern

2.59(1.68-3.99)

 

Lusaka

1.19(0.68-2.07)

 

North Western

1.86(1.19-2.92)

 

Northern

1.48(0.91-2.40)

 

Southern

0.82(0.48-1.38)

 

Western

1.69(1.09-2.61)

Residence

Rural

1.00

 

Urban

1.20(0.85-1.68)

Education level of head of household

Primary and Never

1.00

 

Secondary

1.15(0.89-1.49)

 

Tertiary

1.69(1.19-2.41)

Number of bed spaces covered

Not all

1.00

 

All

2.78(2.17-3.57)

Household with under five who slept under ITNs

No

1.00

 

Yes

2.61(2.00-3.41)

Age group of head of households (years)

<25

3.18(1.77-5.69)

 

25-34

1.37(1.03-1.82)

 

35-44

1.00

 

45-59

1.04(0.77-1.40)

 

60 and above

1.34(0.82-2.18)

Age group of 5–19 year olds

5-9

1.29(1.03-1.60)

 

10-14

0.92(0.76-1.13)

 

15-19

1.00

Notes: 1. AOR denotes adjusted Odds Ratio 2. CI denotes confidence Interval.

Discussion

This study finds evidence suggesting that education attainment is probably one of the important factors that could influence ITN utilization. The finding that tertiary level of education of the head of household is associated with high ITN utilization among five to 19 year olds suggests priority when planning health outreach programmes aimed at sensitizing people on ITN use should be focussed more on those with lower education. This trend may be due to the fact that the five to 19-year old individuals mostly depend on their parents or guardians to make decisions on their behalf and hence parents become important in determining whether their household members utilize ITNs or not. The parents’ knowledge about the danger of malaria to their children determines whether they take action or not to compel their children to use preventive measures such as sleeping under an ITN. This theory is based on health belief model[9] in health promotion. This was also demonstrated in a study which was done in Ethiopia, where skill based training of heads of households on ITN utilization increased ITN utilization in under five children by 31.6 per cent and 38.4 per cent after six and twelve months respectively[10].

Although receiving malaria education was significantly found to be associated with ITN utilization in women in Ethiopia[11], receiving malaria education at home did not result in increased ITN use by the five to 19-year olds in 2010 in Zambia. This may have been due to low coverage of health education at homes in 2010 since only 4.4 per cent of the 4, 810 participants had received health education on malaria at home. An increase in the coverage of health education at homes could have probably resulted in an increased ITN utilization by the 5 to 19 year olds as it would have bridged the gap that existed between heads of households with low and high levels of education. The number of ITNs owned by the household was also an important determinant of ITN utilization by the five to 19-year olds. Individuals who came from households with two ITNs were four times more likely to have slept under an ITN than those from households with one ITN. Similarly, individuals aged five to 19 years who came from households which had three or more ITNs were five times more likely to have slept under an ITN than those from the household which had only one ITN. This suggests that an increase in the number of households with at least three ITNs could lead to an increased ITN utilization among the five to 19-year olds.

This study has highlighted the importance of head of household education level in determining ITN utilization by household members and this can be useful in designing outreach programmes and targeting heads of households with low education levels could lead to increased ITN utilisation in five to 19-year olds.

There are some limitations to this study, the questionnaire was not specifically designed for this study and therefore, some important questions that could have helped in identifying other determinants were left out. There was no question on the number of five to 19-year olds who were sleeping on the floor although this has been found to be associated with low ITN utilization[12]. This would have been captured if mixed methods were used. The fact that this was a household based survey means that those individuals who were in boarding schools and colleges could not have been captured.

Conclusion

The findings that tertiary education level of the head of households influenced the ITN utilization of the five to 19-year old individuals in the 2010 Malaria Indicator survey suggests that health education aimed at sensitizing the public on the importance of sleeping under an ITN as a preventive tool against malaria should focus more on targeting those with lower levels of education. This will help bridge the gap that exist in knowledge levels between those with higher and lower education attainment and might lead to an increase in ITN utilization in the five to19-year old age group.

Future research should focus on school-based surveys to target children using mixed methods and also to educate children on the importance of using ITNs as a preventative method against malaria. The authorities should also consider distributing ITNs in schools to enable more children access ITNs.

Abbreviations

AOR: 

Adjusted odds ratio

OR: 

Odds ratio

ITN: 

Insecticide-treated net

IRS: 

Indoor residue spraying

CI: 

Confidence interval

MIS: 

Malaria indicator survey

WHO: 

World health organization.

Declarations

Acknowledgements

We acknowledge the support provided by the Research Support Centre at the University of Zambia, School of Medicine (UNZA-SoM) through the Southern African Consortium for Research Excellence (SACORE), which is part of the African Institutions Initiative Grant of the Wellcome Trust (company no. 2711000), a charity (no. 210183) registered in England; The National Institutes of Health (NIH) through the Medical Education Partnership Initiative (MEPI) programmatic award No.1R24TW008873 entitled "Expanding Innovative Multidisciplinary Medical Education in Zambia" at UNZA-SoM; We also acknowledge the various contributions made by the following people for this work: The members of the UNZA-SoM SACORE Steering Committee (Dr. Margret Maimbolwa, Dr. Paul Kelly, Dr. Hellen Ayles, & Dr. Charles Michelo) as well as Mr Maxward Katubulushi, Ms. Choolwe Nkwemu Jacobs, Ms. Mutanti Simonda and Ms. Mulemwa Mwangala arranging analytical support. We also acknowledge the valuable contribution by Megan Littrell in data analysis and interpretation of data.

Authors’ Affiliations

(1)
Department of Public Health, School of Medicine, University of Zambia, P.O Box 50110, Lusaka, Zambia
(2)
South Luangwa conservation Society, P.O Box 3, Mfuwe, Zambia
(3)
PATH Malaria Control and Evaluation Partnership in Africa, Postnet P.O Box 370, P/Bag E-10 Lusaka, Zambia

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