Sleeping space matters: LLINs usage in Ghana

ABSTRACT

Long Lasting Insecticidal Net (LLIN) is an effective malaria prevention mechanism. However, ownership of LLIN does not imply its use among households. The availability of enough sleeping space is a natural prerequisite to install and use LLINs. The objective of this study was to explore the effect of sleeping space and other socio-demographic factors of households’ heads on LLINs usage among households. A cross-sectional household-based study was conducted using a quantitative approach. Data was collected exclusively from households that received LLINs at no direct financial cost to them in a mass malaria campaign conducted in the study area using a structured questionnaire. A total of 383 households sampled for the study received 1,181 LLINs with a range of 1 to 15 LLINs per household. Less than 16% of households that received more than 2 LLINs installed all the LLINs they received during the distribution. Among households that received LLINs, 45% of them did not use them at all and 36% of them used them every night including the night before data collection. The number of bedrooms, children and members per household, and the number of occupants per bedroom were also found statistically associated with the use of LLINs among households. The study used a quantitative approach to investigate sleeping space in relation to LLINs usage and malaria control, an area and topic that has not been adequately covered in the literature.

Introduction

Malaria is endemic in most parts of Africa and has caused millions of life loss across age categories including Ghana [1,2]. Even though the World Health Organization (WHO) [3] in its World Malaria Report, 2018 presents a steady decline in malaria mortality rate in Africa over the years, malaria still remains one of the leading causes of mortality in Africa. The Roll Back Malaria Program and Ghana Health Service (GHS) reported 143 deaths attributable to malaria during the first quarter of 2017 in Ghana. This suggests that, approximately, malaria causes two life losses in Ghana daily. This is not different in most malaria-endemic areas. Several preventive and control mechanisms including Long-Lasting Insecticidal Nets (LLINs) have been executed over the years [5]. Currently, a number of tools, technologies and approaches for malaria vector control worldwide have been submitted to the WHO for evaluation. This includes new types of insecticide-treated nets or LLINs, vector traps, spatial mosquito repellants, gene-drive approaches and sugar baits designed to attract and kill Anopheles mosquitoes [6].

Since 2009, the Promoting Malaria Prevention and Treatment (ProMPT) project in Ghana, funded by the United States Agency for International Development (USAID) under the President’s Malaria Initiative (PMI), has worked with the country’s National Malaria Control Program (NMCP), the Ghana Health Service (GHS), and other international donor organizations and programs to strengthen malaria prevention and control, and scale up evidence-based malaria interventions [7].

LLINs are mosquito nets embedded with insecticide. They serve as very effective means for preventing malaria infection and reducing associated morbidity and mortality [6,8]. The adoption of LLINs has played an important role in reducing the malaria burden in Africa to an extent [9]. However, this has not significantly reduced the number of malaria cases in Ghana as expected [10]. Non-usage of LLINs by households who have received LLINs at no financial cost to them during malaria campaigns is one of the reasons that accounts for a lot of malaria cases in Africa [11]. Several studies have identified that the availability of LLINs in households does not guarantee its use [11–13]. A study conducted among pregnant women in suburban coastal Ghana found that LLINs possession was 31.6% with 5.4% utilization [14]. This situation is similar in other malaria-endemic areas in Africa [15,16]. The expected behavior is that once people own LLINs, they should use them [17]. However, that is not the case in a lot of households [18]. This undermines efforts made by governments, local and international bodies to control malaria through LLINs distribution.

Our study focuses on sleeping space, a fundamental requirement for installing and using LLINs. Before one can install and use an LLIN, the person must have enough sleeping space to install it [19]. A lot of bedrooms in many African households are usually smaller than the recommended standard bedroom size by the Statutory Overcrowding Space Standards [20] and are mostly shared with spouses and children. According to the Population and Housing Census [21] conducted in Ghana, national cumulative housing deficit have peaked from over 2.5 million in 2000 to 2.7 million in 2010, when the cumulated deficit is calculated on the basis of 4-persons per household per 2-bedroom unit. Similar trends are observed for the regions and the different city sizes. This makes the bedroom overcrowded and very uncomfortable to use LLINs [22]. Studies conducted in malaria-endemic countries have shown that sleeping space is a major barrier to LLINs usage among households that own them [15,23] but has received relatively less attention in Ghana. Our study, therefore, sought to explore sleeping space and other socio-demographic factors that influence LLINs usage among households that own LLINs in Ghana.

Methods

Study design

A cross-sectional household-based survey was conducted using a quantitative approach. Although households were considered as units of the study, heads of households were interviewed. Data was collected exclusively from households that received LLINs in the mass malaria campaign program conducted in the Bantama sub-metro during the last quarter of 2015 and the first quarter of 2016 using a structured questionnaire. The study determined households that used the LLINs they received and the frequency at which they used them. Chi-squared (X²) test was conducted to find statistical associations between sleeping space factors, other socio-demographic characteristics, and LLIN usage using 95% confidence level. These considered an explanatory variable with a p-value less than 0.05 to be statistically associated with LLINs usage.

Study setting

The study was conducted in the Bantama sub-metro, which is in the Kumasi metropolis in Ashanti region of Ghana. Kumasi metropolitan has 10 sub-metropolitans and the Bantama sub-metro is one of the largest and populated sub-metros in the metropolitan with several large communities such as Suntreso, Kokoso, Adumanu, Abrepo, Bohyen, Bantama, Amanfrom, and Ohwim. Bantama sub-metropolitan is situated in the north-western part of the Kumasi metropolitan. The sub-metropolitan is both a commercial and residential area with a population of 260,474 at risk of malaria [24]. The Bantama community is one of the most important and highly regarded towns in the history of the Ashanti kingdom as it seats one of the powerful chiefs in the Ashanti Kingdom known as ‘BantamaHene’. One of Ghana’s largest teaching and referral hospitals, Komfo Anokye Teaching Hospital (KATH) is also located in the Bantama sub-metro. A lot of houses in the study area are demarcated in single bedrooms which are smaller than the standard bedroom size which is 70 to less than 90 square feet per person [20]. Some of the bedrooms have netted windows and doors. This is to allow ventilation and also prevent mosquitoes and other insects from entering the rooms. The Bantama sub-metro employs LLINs usage and case management (diagnosis and treatment) as the main malaria prevention and treatment interventions. However, results of a malaria incidence study conducted in 2016 using secondary data from the Kumasi Metropolitan Health Directorate reveals that 20,418 patients were diagnosed with malaria in Bantama sub-metro [25]. This excludes unreported malaria incidence in the sub-metro. The same study also indicates that among pregnant women and children under 5 in the Ashanti region of Ghana, Bantama sub-metro recorded the highest laboratory-confirmed severe malaria cases in the region. According to the 2010 population and housing census conducted in Ghana, Bantama sub-metro recorded 1,395 total household deaths [26] and a proportion of these household deaths may be attributable to malaria.

Distribution of LLINs

According to the 2010 census, the Bantama sub-metro has 65,517 households with an average of 3.8 household members [24]. The mass malaria prevention campaign that included free distribution of LLINs conducted in the Bantama sub-metro targeted all households within the sub-metro. The WHO recommended LLINs distribution ratio, 1 LLIN: 1.8 persons at risk of malaria infection [9] was used in distributing LLINs to households in the sub-metro. In other words, the distribution exercise aimed at achieving universal coverage in the sub-metro so they employed this recommendation and shared the LLINs using a ratio of ‘1 LLIN: 1.8 persons’ taking into consideration households with odd number of members. The LLINs distribution was done using volunteers. These volunteers were stationed at vantage points in the sub-metro. They conducted a registration exercise that captured information on the number of households and members within each household in the sub-metro. This exercise served as a guide in the allocation of LLINs to the Bantama sub-metro and the various LLINs collection centers created. The household registration points were converted to LLINs collection points during the distribution exercise. The distribution of the LLINs did not include LLINs hanging up or installation exercise.

Study participants

The inclusion criteria for the study were households that received LLINs in the Bantama sub-metro during the mass malaria campaign. The study used a snowball sampling technique [27]. Data collectors moved from one house to the other based on recommendations of previous households who knew households that received LLINs during the campaign. In an event where a sampled household was unwilling to participate in the study, the next household was considered. Only one household in a house was recruited for the study.

Data collection

A structured questionnaire was designed and used to collect data from households. Data collectors assisted study participants in understanding the questions by interpreting the questions to them in their preferred language. The mass malaria campaign which included free distribution of LLINs was conducted during the last quarter of 2015 and the first quarter of 2016 with an anticipated serviceable life span of 3 years by WHO [28]. Data was collected between May and June 2017 (major raining season in Ghana), approximately a year and half after the LLINs distribution i.e. during half of the anticipated serviceable life span of the nets.

Data analysis

We first analyzed the data to determine the proportion of total LLINs received by households that have been installed. Further analysis was done using cross-tabulation to find out the number of households that received a specified quantity of LLINs and the proportion of the LLINs received per household that has been installed. We also found out the proportion of households that have used the nets as well as the frequency at which they use them. In determining LLINs usage among households, households that had some members not sleeping under the nets were considered cases of non-usage because the objective is for the entire household to use LLINs [29]. Chi-squared test was conducted to find statistical associations between sleeping space factors (number of bedrooms per household, number of children per household, number of household members and number of occupants per bedroom), socio-demographic characteristics of heads of households (marital status, highest educational level, age, and main occupation), and LLINs utilization among households. The results of descriptive analyses were presented as frequencies, percentages and displayed in tables and a graph.

Results

A total of 383 households sampled for the study received 1,181 LLINs with a range of 1 to 15 LLINs per household. Also, 685 (58%) of the LLINs received had not been installed. Households with at least one LLIN for every two people were 244 (63.7%). Of the 383 household heads interviewed, 305 (79.6%) said they know how to install LLINs and can be able to install them on their own.

Table 1 provides detailed information on the proportion of LLINs received that have been installed by households. It also shows the number of households that received a specified quantity of LLINs and the proportion of the nets received that had been installed after about 18 months of LLINs possession. A total of 92 households received 1 LLIN each and 56 of them had installed it. Households that received 2 LLINs each were 93 and 61 of them had installed all the two nets they had received (2/2). Of the 2 LLINs each household received, 11 of them had installed one out of the nets received (1/2) and 21 had not installed any of the LLINs received (0/2). It was also identified that none of the households that received 4 LLINs or 6 LLINs had installed all of them.

Table 1.

Proportion of LLINs installed by households per LLINs received.

Number of LLINs received by households	0	1	2	3	4	5	Number of households that received a specific number of LLINs	Total number of LLINs received by households
1	36	56*	0	0	0	0	92	92
2	21	11	61*	0	0	0	93	186
3	24	14	23	11*	0	0	72	216
4	17	21	14	6	0*	0	58	232
5	0	4	15	8	4	4*	35	175
6	11	0	0	4	0	0	15	90
8	0	0	0	3	0	0	3	24
9	4	0	0	0	0	0	4	36
10	3	0	0	4	0	0	7	70
15	0	0	0	0	0	4	4	60
Total	116 (30.3%)	106 (27.7%)	113 (29.5%)	36 (9.4%)	4 (1.0%)	8 (2.1%)	383 (100%)	1,181

*Installed all LLINs received

We found that out of the 383 households interviewed, 210 (55%) of them used LLINs. Expressing this as a percentage of household heads that can install LLINs (210/305) results in 68.9%. It was also found that, 11 households representing less than 3 percent of total households had a fraction of household members using LLINs. These households were regarded as cases of non-usage of LLINs. The study went further to ascertain the frequency at which households slept under the LLINs. This is displayed in Figure 1.

Figure 1.

Frequency at which households slept under LLINs.

It was revealed that, 35.8% of households slept under the LLINs every night including the previous night data was collected, and 7.6% slept under the LLINs most nights (4–6 nights in a week). A total of 173 households (45.2%) did not use the net at all and this included households that did not install at least one LLIN.

Table 2 displays socio-demographic factors of household heads that were statistically associated with LLINs usage by the entire household. Of the 244 household heads who were married, 153 of those households used LLINs. Out of 100 households with a single household head, there were 54 households that did not use LLINs. Marital status was found statistically associated with LLINs usage by households (X² = 23.98; p < 0.001). Household heads with Junior high school as their highest level of education formed the highest frequency (160, 41.8%). Those with primary school as their highest level of education recorded the lowest (36, 9.4%). Highest educational level of household heads was found to be statistically associated with LLINs use by households (X² = 20.2218; p < 0.001). Age of household heads was grouped in a 5-year interval and was found to be statistically associated with LLINs usage (X² = 59.6539; p < 0.001). The main occupation of respondents was statistically associated with LLINs usage (X² = 32.8578; p < 0.001).

Table 2.

Socio-demographic factors of household heads associated with LLINs usage.

Socio-demographic characteristics	Frequency (%) N = 383	LLINs Usage	LLINs Non-Usage	X² (p-value)
Marital status				23.9800 (< 0.001)
Divorced	18 (4.7)	8	10
Married	244 (63.7)	153	91
Single	100 (26.1)	46	54
Widowed	21 (5.5)	3	18
Highest educational level				20.2218 (< 0.001)
No formal education	81 (21.2)	28	53
Primary school	36 (9.4)	21	15
Junior high school	160 (41.8)	93	28
Senior high school	65 (17.0)	38	27
Tertiary education	41 (10.7)	30	11
Age in groups				59.6539 (< 0.001)
Below 21	15 (3.9)	0	15
21–25	27 (7.1)	19	8
26–30	74 (19.3)	53	21
31–35	43 (11.2)	27	16
36–40	62 (16.2)	44	18
41–45	59 (15.4)	34	25
46–50	30 (17.8)	11	19
51–55	18 (4.7)	4	14
56–60	25 (6.5)	8	17
Above 60	30 (7.8)	10	20
Main Occupation				32.8578 (< 0.001)
Artisan	64 (16.7)	29	35
Businessman/woman	33 (8.6)	27	6
Civil servant	15 (3.9)	15	0
Petty trader	187 (48.8)	106	81
Unemployed	84 (21.9)	33	51

Table 3 shows sleeping space factors (number of bedrooms per household, number of household members, number of children per household, and number of occupants per bedroom) associated with LLINs usage by households. Almost half of the total number of households considered in the study lived in one bedroom (187, 48.8%). It was also recorded that, 110 households with one bedroom used LLINs. The number of bedrooms per household was statistically associated with LLINs usage (X² = 14.2441; p = 0.027). Majority of households had more than 2 household members. The number of household members was found to be statistically associated with LLINs usage (X² = 42.6481; p < 0.001). Similarly, the number of children per household was statistically associated with LLINs usage (X² = 41.9858; p < 0.001). The number of occupants per bedroom was statistically associated with LLINs usage (X² = 38.0106; p < 0.001).

Table 3.

Sleeping space factors associated with LLINs usage.

Sleeping Space Factors	Frequency (%) N = 383	LLINs Usage	LLINs Non-Usage	X² (p-value)
Number of bedrooms per household				14.2441 (0.027)
One	187 (48.8)	110	77
Two	79 (20.6)	41	38
Three	56 (14.6)	25	31
Four	38 (9.9)	18	20
Five	16 (4.2)	12	4
Seven	4 (1.0)	4	0
Nine	3 (0.8)	0	3
Number of household members				42.6481 (< 0.001)
One	17 (4.4)	3	14
Two	23 (6.0)	13	10
Three	62 (16.2)	37	25
Four	68 (17.8)	41	27
Five	77 (20.1)	45	32
Six	73 (19.1)	34	39
Above six	63 (16.4)	37	26
Number of children per household				41.9858 (< 0.001)
Zero	47 (12.3)	20	27
One	52 (13.6)	33	19
Two	57 (14.9)	15	42
Three	54 (14.1)	33	21
Four	82 (21.4)	37	45
Five	50 (13.1)	18	32
Six	20 (5.2)	16	4
Above six	21 (5.5)	11	10
Number of occupants per bedroom				38.0106 (< 0.001)
One	71 (18.5)	29	42
Two	91 (23.8)	50	41
Three	106 (27.7)	54	52
Four	42 (11.0)	38	4
Five	35 (9.1)	23	12
Six	34 (8.9)	12	22
Eight	4 (1.0)	4	0

Discussion

Non-usage of LLINs by households that possess LLINs is a major challenge in the fight against malaria in Africa, Central India and other malaria-endemic areas in the world [30]. Our study considered 383 households who had received a total of 1,181 LLINs at no direct financial cost to them during a malaria campaign in the study area. Findings from our study show that 685 (58%) of the LLINs received have not been installed and ready for use after about 18 months of LLINs possession. Meanwhile, majority of household heads indicated they had knowledge on how to install LLINs and could install them on their own. This suggests that, ability to install LLINs is mainly not the reason for non-usage of LLINs. These uninstalled LLINs do not complement efforts made to combat malaria using LLINs as a primary preventive mechanism. Findings from several studies conducted in Africa and other malaria-endemic areas have shown that a significant percentage of LLINs distributed to households for free are not installed [13,14]. For instance, a report by the National Malaria Control Program (NMCP) of the Ghana Health Service in 2013 upon adopting the distribution of LLINs as a major malaria preventive intervention since 1998 reported that, almost 45% of LLINs owned were not installed and ready for use [31]. Non-installation of LLINs does not only has a negative effect on the health of people at risk of malaria infection but also has a financial cost element that is also very crucial. A study conducted in Ghana on the cost of LLINs distribution recorded that the average annual economic cost of mass malaria campaign was 2.90 USD per LLIN delivered [13]. Multiplying this by the number of non-installed LLINs in Ghana alone may amount to several millions of dollars spent on LLINs distribution that did not yield the desired results.

It is recommended that populations at risk of malaria infection sleep under LLINs each time they go to bed in order to be protected from mosquito bites, hence malaria infection. However, it was ascertained in our study that 35.8% of households adhere to this recommendation. This undermines the purpose for which the LLINs were freely distributed and may account for malaria infection among households that do not use LLINs every night. It was also found that, 11 households (less than 3%) had a fraction of members using LLINs. This suggests that, LLINs usage is an ‘almost all or none’ situation. It therefore suggests that when health education on the importance of using LLINs is intensified, chances are that almost all members within a household would use LLINs. We further analyzed the proportion of LLINs that have been installed out of the specific number of LLINs received by individual households. An issue of concern identified was that, less than 16% of households that received more than two LLINs installed all the LLINs they received. This may suggest that a significant proportion of LLINs received that were not installed was as a result of giving more LLINs to a household considering the WHO recommend LLINs distribution ratio, 1 LLIN: 1.8 persons at risk of malaria infection [9]. Even though sleeping space of the people at risk is a natural pre-requisite for installing and using LLINs, the distribution ratio or criteria do not consider it. A relationship can be drawn between non-installation of LLINs, number of bedrooms per household and number of people per household. Our study found that 48.8% of the total households have one bedroom, and about 90% of households have at least 3 household members. This suggests that, a lot of the households with one bedroom have three or more household members and this makes it highly impossible to use LLINs in such households. It therefore suggests that inadequate bedroom or sleeping space for household members may account for the low proportion of LLINs installed and used. An evaluation study conducted in Mali on LLINs usage drew a positive relationship between sleeping space and LLINs installation [32] and this is consistent with the findings of this study. Also, non-installation of LLINs has direct consequences on LLINs usage as one needs to fix the net before it can be used. It is therefore not surprising that about 45% of households that received the LLINs did not use them at all.

Socio-demographic factors of household heads such as age, marital status, highest educational level, and occupation were found to have significant relationship with LLINs usage among households. This is consistent with findings from previous studies in other malaria-endemic areas in Africa [11, 33].

Although, these socio-demographic characteristics of household heads are significant to LLINs use, using sleeping space alone results in a stronger prediction of LLINs usage [19]. As highlighted by these studies, factors that suggest non-availability of enough sleeping space have been established to be demotivating factors in the installation and usage of LLINs among households. This is even evident in studies that recorded high levels of LLINs usage among households. A study conducted in Uganda in 2016 recorded 80% of the entire population and 83 % of children under five years of age sleeping under an LLIN every night including the night before data collection [35]. This is a great milestone considering the WHO operational definition for success in LLINs usage [29]. However, it was also found in this study conducted in Uganda that households with more than four members were less likely to use LLIN. This is in line with the findings of our study as the number of household members was found to have significant association with LLINs usage. In cases where bedrooms are shared with other people, it is relatively difficult to use LLINs because one may not get enough sleeping space to even install and comfortably use it. The findings of another study conducted in malaria-endemic areas in Central India is consistent with the results of this study. It also reports inadequate space to install LLINs as a major reason why households in possession of LLINs did not use them [30].

Number of bedrooms per household, number of children per household, number of household members and number of occupants per bedroom were found to be statistically associated with LLINs usage among households. All these determine the availability of bedroom space or sleeping space available for household members. According to statutory overcrowding space standards, a bedroom size of 70 to less than 90 square feet should be used by only one person [20]. However, in Ghana and many African countries, a lot of bedrooms are smaller than 70 square feet and are being used by multiple people [19]. When there is limited sleeping space for room occupants, LLINs installation and usage is almost not possible [32,36]. Studies have shown that dwelling construction, family size and sleeping arrangements are associated with the use of LLINs among households [37]. The availability of enough sleeping space is critical in LLINs installation and it is one of the criteria for making decisions on the intra-household allocation of LLINs in Uganda [38].

Limitations of the study

The study duly acknowledges that there are other sources of acquiring LLINs aside mass LLINs distribution exercises, which is the major medium through which a lot of households acquire LLINs in Ghana. However, it sought to target the main LLINs distribution channel which was implemented at a specific period. This was necessary in order to have a common basis to compare the amount of time that households have had possession of LLINs and whether the LLINs have been used or not. The study considered households where a fraction of household members used LLINs as cases of non-usage of LLINs. Our findings do not further summarize the direction of the association between sleeping space and LLINs usage. There is strong evidence that house structures also play significant role in LLINs usage. People with well-roofed houses, netted doors and windows tend not to sleep under LLINs, even when they have one. This was not considered in the study.

Conclusions

LLINs usage has been proven to be an effective malaria prevention mechanism. However, households owning LLINs do not automatically translate into usage due to several factors including inadequate sleeping space and what could be described as undesirability of LLINs usage. This phenomenon could be attributed to low public health education on the benefits of LLINs usage during LLINs distribution in malaria-endemic areas. The wide gap between LLINs ownership and usage could potentially stall malaria prevention efforts and interventions. Sleeping space is a natural prerequisite to using LLINs and its inadequacy in households poses a threat to LLINs usage. However, a more pragmatic approach to bridge this gap should be devised and integrated into LLINs distribution criteria. Also, further studies are imperative to explore innovative ways for LLINs installation and usage in households with sleeping space constraints. It is important for the sub-metropolitan health directorate, national malaria control program, and other non-governmental agencies committed to malaria prevention in Ghana and other malaria-endemic areas to explore appropriate malaria prevention mechanisms that do not require sleeping space in their implementation. Additionally, LLINs usage campaigns and outreach programs should be designed such that, socio-demographics of households and sleeping space factors are considered as they may largely differ among households or communities. Even though the study was conducted in the Bantama Sub-Metro, findings may be applicable to areas in Ghana and other malaria-endemic areas in Africa that uses free distribution of LLINs as a mechanism to reducing malaria incidence [39]***.

Disclosure statement

No potential conflict of interest was reported by the authors.