Background

Malaria is endemic in Liberia, representing a major cause of morbidity and mortality, and a leading cause of outpatient attendance and in-patient deaths in 2014 [1]. Children and pregnant women are the most affected by the disease. Rapid diagnostic testing conducted as part of the 2011 Malaria Indicator Survey revealed that 45% of children aged 6–59 months had malaria; microscopy revealed a lower prevalence (28%) [2]. The microscopy test results indicated that malaria prevalence increased monotonically with age from 9.6% among children aged 6–8 months to 35.4% among those aged 48–59 months. Other factors associated with variations in malaria prevalence among children included rural residence, county of residence, mother’s education, and household wealth quintile.

Insecticide-treated nets (ITNs) provide a physical barrier between humans and mosquitoes; the insecticide used on the nets also repels and kills mosquitoes. ITNs have been shown to lead to significant reductions in parasite rates in children under five years old and all-cause child mortality [3–5]. Additionally, there is evidence that ITN use by a majority of the community provides some level of protection even to those who are not using them, as it helps to reduce overall malaria transmission [6].

The government of Liberia is committed to reducing the burden of malaria in the country as evidenced in the 2010–2015 National Malaria Strategic Plan, which is the most recent national guidance available for Liberia [1]. The strategic plan builds on the two previous national malaria strategic plans and articulates strategies designed to reduce malaria morbidity and mortality, and reduce the incidence of malaria by 2015. The strategic plan has specific targets and strategies focused on each of the following four strategic areas: malaria case management, intermittent preventive treatment in pregnancy (IPTp), integrated vector control (including use of ITNs and indoor residual spraying (IRS)), and behavior change. Additionally, the plan recognizes the need to strengthen the capacity of the National Malaria Control Program in the development, management, and evaluation of malaria programs. The strategies articulated in the strategic plan are geared towards increasing prompt and effective treatment of malaria in children under five years old, increasing the uptake of IPTp for pregnant women, increasing access to IRS and ITNs in households, and increasing ITN use by children and pregnant women. Regarding ITN use, one of the key objectives of the National Malaria Strategic Plan seeks to increase the use of long-lasting insecticide-treated nets (LLINs) to 80% among children and pregnant women by 2010 and sustain this level of use through 2015.

Results of the 2013 Demographic and Health Survey showed that 55% of households in Liberia had at least one ITN while only 22% of households had universal coverage [7]. Only 38% of children under five and 37% of pregnant women slept under an ITN on the night preceding the survey. In households owning at least one ITN, 63% of both groups slept under an ITN the previous night.

In order to provide optimum protection, ITNs must be used regularly by all members of a population. Reasons for ITN use differ, but include the protection they offer from nuisance mosquitoes, perceived density of mosquitoes in one’s surroundings [8–11], and quality of the ITN [12]. The reasons often provided for non-use of ITNs include perceived heat, perceived discomfort of sleeping under an ITN, perceived low mosquito density, torn or worn ITNs, perception that the ITN was not needed, and unavailability of ITNs (lack of access) [10, 13–15].

Access is a key determinant of ITN use but not the only one. Studies that have focused on the factors associated with ITN use have highlighted the roles of age [16–21], sex [16, 19, 21–22], and pregnancy status [17]. Other factors found to be associated with variations in ITN use include household size [21, 23], and socio-economic status [18, 24]. Studies have also found a positive relationship between exposure to social and behavior change communication (SBCC) messages and ITN use in various settings [15, 23, 25–28]. In addition to these socio-demographic and program exposure variables, it is important to understand the cognitive, emotional, and social interaction factors that influence health behaviors. In the case of ITNs, these factors include knowledge, personal beliefs in one’s ability to obtain and use ITNs properly, perceived threat, perceived ITN efficacy, interpersonal communication, perceived social support, and social norms. For example, possessing accurate malaria knowledge has been found to be a strong predictor of ITN use in some settings [23, 29–32]. Similarly, beliefs that malaria is not a serious problem (low threat) and that the ITN is not effective in preventing malaria (low response efficacy) can contribute to low ITN use [10, 33–34].

The combination of these cognitive, emotional, and social interaction concepts is called “ideation.” Ideation is a concept frequently used in the family planning and HIV community as a way to understand people’s readiness to adopt health protective behaviors [35–37]. Ideation has only recently been explored in the malaria literature as a way to understand how mass media campaigns and community mobilizers influence the number of ITNs per person in a household [26].

Objectives

Using household survey data collected between March and April 2014, this study evaluates the role of socio-demographic characteristics, caregiver ITN ideation, household characteristics, and community factors in ITN use among household members. The tested hypothesis is that the factors affecting ITN use operate at individual, household, and community levels. What differentiates this study from most previous studies is its focus on the role of ideational characteristics and unmeasured factors operating at the household and community levels in intra-household ITN allocation.

Study Setting

The study took place in four counties of Liberia in 2014, just prior to rainy season: Bong, Cape Mount, Grand Kru and Rivercess. Malaria prevalence among children under five years old (measured by rapid diagnostic test) was generally high in these counties and varied from 41.6% (95% CI: 33.9–48.7) in Bong to 69.5% (CI: 50.9–83.3) in Grand Kru (secondary analysis of MIS 2011 data performed by lead author). The four counties represented two endemicity strata in Liberia: Bong and Rivercess which have a malaria prevalence below the national average, and Grand Kru and Cape Mount which have a malaria prevalence above the national average.

Study Design and Procedures

The data presented were derived from a cross-sectional household survey conducted in Liberia in 2014 by the Johns Hopkins Center for Communication Programs. A total of 1200 households were randomly selected from the four counties. The sample size was adequate to detect a 10-percentage point difference in ITN use between the two malaria endemicity strata. Households were selected through a multistage process that involved randomly selecting enumeration areas (clusters) with a probability proportional to size and then households from each study county. Only households with at least one child under the age of five years were eligible for participation in the survey. In selected households, a woman with a child aged less than five years old was randomly selected for interview. Through the household questionnaire, ITN use information was collected for 6,463 household members. The data analyzed in this manuscript combined ITN use information for individual household members derived from the household questionnaire with female caregivers’ socio-demographic and ideational characteristics derived from the individual questionnaire.

Data Analysis

The dependent variable evaluated in this study is defined as sleeping under an ITN on the night before the survey. We limit the analysis to individuals from households with at least one ITN, representing only a little over one third of the households.

We assessed the predictive value of fifteen independent variables measured at the individual, household, and community levels and defined as follows:

1. Age: Household members were divided into three age groups: 0–4 years, 5–17 years, and adults aged 18 years and above;
2. Sex of household member: Male or female;
3. Education level of the female caregiver interviewed in the household, assessed as none, primary, or post-primary;
4. Female caregiver’s perception about ITN use being the norm in their community: An ideational variable assessed through a question that asks respondents in how many households in their community do people sleep under an ITN. The response options were: All households, most households, at least half of the households, fewer than half households, or hardly any households. We distinguished between the women that responded “all” or “most” households and those that gave other responses;
5. Female caregiver’s perceived susceptibility to malaria: Another ideational variable assessed through seven Likert-scale attitudinal statements related to the likelihood of getting malaria. For example, “During the rainy season, I worry almost every night that someone in my family will get malaria”; and “Nearly every year, someone in this community gets a serious case of malaria”. We scored each of the seven items between -2 and +2, computed a total score which we then split it at zero to denote low versus high perceived susceptibility;
6. Female caregiver’s perceived severity of malaria: Measured through five Likert-scale attitudinal items. For example: “When someone I know gets malaria, I usually expect them to completely recover in a few days” (reverse-coded); and “Every case of malaria can potentially lead to death”. We scored each of the five items between -2 and +2, computed a total score which we then split it at zero to denote low versus high perceived severity of malaria;
7. Female caregiver’s perceived self-efficacy to recognize a complicated case of malaria;
8. Female caregiver’s knowledge about malaria prevention: Measured as mentioning at least one correct malaria prevention method while not mentioning any incorrect prevention methods;
9. Female caregiver’s perceived self-efficacy to prevent malaria in self and children.
10. Female caregiver’s exposure to the “Take Cover” malaria communication campaign. The “Take Cover” campaign used radio spots, print materials and community mobilization to promote ITN use. It was first launched in 2009; the radio materials were periodically rebroadcast until the time of the survey in 2014. We defined high level of exposure to the campaign as having heard of the program from two or more media or community sources;
11. Number of ITNs in household: Classified as one, two or more than two;
12. Household size: The number of usual residents of the household;
13. Household socio-economic status: Derived from household assets through principal components analysis and divided into quintiles;
14. Number of under-five children within the household: We divided the number into one, two, or three or more; and,
15. County of residence: That is, Bong, Cape Mount, Grand Kru or Rivercess.

Multilevel modeling is the main analytic method used in this manuscript. The survey data analyzed in this manuscript reflect a hierarchical nature with individuals nested within their household, which are, in turn, nested within their clusters or neighborhood. In nested data, individuals within the same units tend to be more similar than those from other units. Ordinary regression methods do not account for this clustering and tend to underestimate the standard errors of regression coefficients [38]. When survey data are nested, multilevel modeling is the indicated analytic approach as it helps to adjust for clustering. To further justify the use of multilevel modeling, we computed the design effect. A design effect greater than 2.0 indicates violations of the independence assumption [39]. The design effect in our data was 11.4. In other words, clustering in the data results in over eleven-fold reduction in effective sample size compared to what would have occurred with simple random sampling.

We estimated three-level mixed effects models with fixed effects at the individual, household, and county levels, and random effects at the household and cluster levels. We estimated two models: an empty model without covariates to assess if there was significant group-level variation in ITN use, and the full model that included variables measured at the individual, household, and county levels. In multilevel models, a small number of groups and small group sizes have been documented to bias the efficiency of multilevel random parameter estimates downwards [39–41]. Some studies have also found that having a large number of groups compensates for the negative effects of small group sizes [39, 41]. For example, Clarke and Wheaton [41] found in their simulation study that when number of groups is greater than 150 the bias resulting from even extremely small group sizes is considerably reduced. In our data, we have a total of 60 clusters with size varying from 3 and 80 individuals, with a mean of 38. To minimize bias in the random components of the estimates, we follow Clarke & Wheaton [41] and limit the analyses in this manuscript to respondents residing in clusters with at least ten individuals. This approach resulted in a loss of five groups and 29 individuals. The final sample used for the analysis comprised 2,269 individuals. We estimated the models using the gllamm command in Stata 13 (College Station, Texas, USA).

Ethical approval and informed consent

The Johns Hopkins Bloomberg School of Public Health Institutional Review Board (IRB) and the University of Liberia, Pacific Institute for Research and Evaluation IRB approved this survey. Only adults were enrolled into the study. Interviewers obtained verbal informed consent from all participants prior to the interviews. The researchers opted for verbal consent due to the low literacy level of a significant proportion of the study participants. The person obtaining the consent signed the consent document to attest that consent had been obtained. The two ethics committees approved this procedure.

Socio-demographic characteristics of households and members

Table 1 provides information on the socio-demographic and ideational characteristics of the population in households with at least one ITN. Almost half (47.3%) of the population were adults, and household members were equally divided between males and females. In terms of female caregiver’s characteristics, most of the study population came from households where the female caregiver had little or no education. The ideational characteristics of the female caregivers revealed that fewer than one third (29.8%) of these women believed ITN use to be the norm among other households in their community. Nonetheless, the majority of the women believed in their susceptibility to malaria and perceived malaria to be a serious disease. Furthermore, most of the caregivers had a high level of perceived self-efficacy to prevent malaria and to detect a serious case of malaria, although the prevalence of comprehensive knowledge about malaria was low. More than half of the female caregivers (57.5%) had a high level of exposure to the “Take Cover” communication campaign.

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Table 1. Background characteristics of people in households with at least one ITN, Liberia 2014.

https://doi.org/10.1371/journal.pone.0158331.t001

More than half (54.7%) of the members were from households with only one under-five child (55.1%), and most were from households with only one (53.3%) or two (30.0%) ITNs. Proportionally fewer of the members were from the lowest or second wealth quintiles than from any of the three upper quintiles. Similarly, proportionally fewer of the household members were from Rivercess County compared to any of the other three counties.

Patterns of ITN ownership, conditions, and use

A little over one third (36%) of surveyed households had at least one net. Almost all (99.1%) of these nets were ITNs; the rest were untreated nets. Overall, only 4% of the study households had enough ITNs for all household members as defined by the WHO as one ITN per two household members. Upon inspection, about three-fifths (58.3%) of the ITNs in use in the surveyed households were found to have no holes while 16.7% had very small holes (smaller than a flashlight battery); the rest (25%) had at least one hole larger than a flashlight battery. Most of the ITNs (78.7%) had been in the household for more than six months. In households with at least one ITN, two thirds (66.6%) of the members slept under an ITN on the night before the survey. This indicator varied widely by country: 85.6% in Bong, 76.3% in Cape Mount, 62.0% in Rivercess, and 36.3% in Grand Kru. A little over one tenth (12%) of the ITNs within the households were not used on the night prior to the survey. Nonetheless, in many households with ITNs, up to four persons slept under the same ITN; the median number of users per ITN was three household members.

Correlates of intra-household ITN use

We used multilevel modeling to assess the correlates of intra-household ITN use. The results of the three-level models are presented on Table 2. The empty model revealed significant clustering of ITN use at both the household and cluster levels. The intra-class correlation (ICC) indicates that about 24% of the variance in intra-household ITN use is attributable to factors operating at the cluster level while about 60% of the variance is due to factors operating at the household level. This result justifies the use of multi-level modeling.

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Table 2. Results (odds ratio) of the multilevel modeling of the relationship between ITN use and selected individual, household, and community variables, Liberia 2014.

https://doi.org/10.1371/journal.pone.0158331.t002

When the covariates are introduced (Full Model), the residual ICC was substantially diminished at the cluster level, indicating that much of the cluster-level variance was due to differences across communities in the covariates included in the estimated model. In contrast, there remains a significant level of clustering at the household level, indicating that irrespective of socio-demographic characteristics, there are inter-household differences in ITN use among households within the same cluster. The results of this model further reveal that the strongest correlates of intra-household ITN use are number of ITNs in the household, age, household size, and county of residence. Other significant correlates of ITN use include caregiver’s exposure to malaria prevention messages, her perceived self-efficacy to detect complicated malaria, her perceived severity of malaria, and household wealth.

There is a significant interaction between sex and age group, indicating that the relationship of sex with ITN use varies by age. The findings indicate that sex does not make a difference for ITN use among children under five. Sex does not significantly moderate the association of being an older child or teenager with ITN use. In contrast, among adults, being female significantly alleviates the negative effects of age on ITN use. Among male members, older children and teenagers were 91% less likely and adults were 53% less likely than under-five children to use an ITN. Furthermore, the predicted marginal probability from the estimated full model reveal that adult women (75.8%) were significantly more likely than adult men (65.7%) to sleep under an ITN: (p<0.001). For under-five children, the predicted marginal probability was 76.2% for boys and 76.3% for girls.

The number of ITNs in a household was one of the strongest predictors of ITN use; having three or more ITNs in a household is associated with a 13-fold increase in the odds of sleeping under an ITN. Individuals residing in households with a female caregiver who reported a high level of perceived severity of malaria were 62% more likely than their peers from other households to sleep under an ITN. Similarly, a female caregiver’s high level of perceived self-efficacy to detect complicated malaria was associated with a two-fold increase of household members’ use of ITNs. The relationship with exposure to the “Take Cover” campaign was such that individuals from households in which the female caregiver had a high level of exposure were 90% more likely to sleep under an ITN compared to individuals from households in which the female caregiver had a low level of exposure.

The relationship with household size is negative, such that a unit increase in household size is associated with a 32% reduction in the odds of using an ITN. As for household wealth, the only significant difference is between the lowest and highest quintiles, with individuals from the highest quintile being more than twice as likely to sleep under an ITN as their peers from the lowest quintile. Individuals from Grand Kru and Rivercess were significantly less likely to sleep under an ITN than their counterparts from Bong. Finally, the number of under-five children in the household was not significantly associated with intra-household ITN use.