Skip to main content

Mixed effect analysis of factors influencing the use of insecticides treated bed nets among pregnant women in Ghana: evidence from the 2019 Malaria Indicator Survey

Abstract

Background

Malaria during pregnancy is a major cause of maternal morbidity globally and leads to poor birth outcomes. The World Health Organization has recommended the use of insecticide treated bed nets (ITN) as one of the effective malaria preventive strategies among pregnant women in malaria endemic areas. This study, therefore, seeks to examine the individual and household factors associated with the use of ITNs among pregnant women in Ghana.

Methods

Data for this study was obtained from the 2019 Ghana Malaria Indicator Survey (GMIS) conducted between September 25 and November 24, 2019. The weighted sample comprised 353 pregnant women aged 15–49 years. Data was analyzed with SPSS version 22 using both descriptive and multilevel logistics regression modelling. Statistically significant level was set at p < 0.05.

Results

The study found that 49.2% of pregnant women in Ghana use ITN to prevent malaria. Pregnant women aged 35–49 years (AOR = 3.403, CI: 1.191–9.725), those with no formal education (AOR = 5.585, CI = 1.315–23.716), and those who had secondary education (AOR = 3.509, CI = 1.076–11.440) had higher odds of using ITN. Similarly, higher odds of ITN usage was found among who belonged to the Akan ethnic group (AOR = 7.234, CI = 1.497–34.955), dwell in male-headed households (AOR = 2.232, CI = 1.105–4.508) and those whose household heads are aged 60–69 years (AOR = 4.303, CI = 1.160–15.966). However, pregnant women who resided in urban areas (AOR = 0.355, CI = 0.216–0.582), those whose household heads aged 40–49 years (AOR = 0.175, CI = 0.066–0.467) and those who belonged to richer (AOR =0.184, CI = 0.050–0.679) and richest (AOR = 0.107, CI = 0.021–0.552) households had lower odds of using ITN for malaria prevention.

Conclusions

Individual socio-demographic and household factors such as pregnant women’s age, educational level, place of residence, ethnicity, sex and age of household head, and household wealth quintile are associated with the use of ITN for malaria prevention among pregnant women. These factors ought to be considered in strengthening malaria prevention campaigns and develop new interventions to help increase ITN utilization among vulnerable population living in malaria- endemic areas.

Peer Review reports

Background

Malaria as a vector borne disease is still a global health problem especially in sub-Saharan Africa and the most adversely affected are pregnant women and children under five [1, 2]. According to the World Health Organisation (WHO), in 2019, an estimated 11 million pregnant women were exposed to malaria infections. These pregnant women delivered 872,000 children with low birth weight, with West Africa having the highest prevalence of low birth weight children due to malaria in pregnancy [1]. Further, an estimated 25 million pregnant women are currently at risk of malaria infection. Meanwhile, malaria infection among pregnant women account for over 10,000 maternal and 200,000 neonatal deaths per annum [3, 4]. Malaria in pregnancy is associated with risk of miscarriages, stillbirths and, intrauterine demise [5,6,7].

In Ghana, malaria cases recorded at Out-patient Departments (OPD) in 2017 was 399,736 compared to 383,034 in 2016 [8] among pregnant women. This figure represents an increase of 4.2% over the 2016-recorded number of cases among pregnant women. To help reduce Malaria in Pregnancy (MIP), the National Malaria Control Programme (NMCP) has introduced a number of preventive interventions such as Intermittent Preventive Treatment of malaria in Pregnancy (IPTp), distribution and use of Insecticide Treated Nets (ITNs) and Indoor Residual Spraying (IRS) [9,10,11]. Other malaria prevention strategies for vulnerable population are Seasonal Malaria Chemoprevention (SMC), and Integrated Community Case Management (iCCM) [11].

Among these interventions, available empirical evidence suggests that the use of ITN is a cost-effective vector control measure for the prevention of malaria transmission especially in highly endemic areas [12,13,14,15,16,17]. The appropriate and effective use of ITNs has been shown to decrease the transmission of malaria by 90% [18] and negative pregnancy outcomes by 33% [18, 19]. It is therefore not farfetched that WHO recommends the use of ITN as an effective measure for the prevention of malaria in pregnancy [1, 2].

However, the effective and continuous use of ITN by pregnant women in the African sub-region including Ghana has been relatively low [20,21,22,23,24]. A number of reasons and factors have been associated with the low utilization of ITN. Some of these reasons and factors include discomfort with sleeping under ITNs [20, 25,26,27], poor knowledge and perception of ITNs [28, 29], high cost of ITNs [30], distance to the nearest health facility [31, 32], age of pregnant women, area of residence, educational level, marital status, and wealth index [33,34,35,36,37,38,39,40].

In Ghana, ITN utilization among pregnant women decreased from 59% in 2016 to 49% in 2019 [11], implying that Ghana still has a long way to go in its efforts to achieve universal coverage of ITNs. The universal coverage of ITNs has been defined as ITN use by over 80% of vulnerable populations in malaria endemic areas to achieve optimum protection [41]. Although previous studies have examined factors affecting ITN utilization among vulnerable sub-populations such as pregnant women across different geographical locations including Ghana [26, 30, 34, 36, 39], to the best of our knowledge none of the studies have focused on how individual and household factors interact to influence the use of ITNs among pregnant women. This paper, therefore, seeks to examine the mixed effects of individual and household factors on the use of ITNs among pregnant women in Ghana using the 2019 Ghana Malaria Indicator Survey (GMIS).

Materials and methods

Data source

The data for this study was (secondary data) extracted from the 2019 Ghana Malaria Indicator Surveys (GMIS) which was conducted from September 25 to November 24, 2019. We used data from the women’s file (15–49 years). The GMIS collects information on malaria prevention (ownership and use of treated mosquito bed nets and assess coverage of intermittent preventive treatment to protect pregnant women against malaria), treatment, and prevalence in Ghana. In this study, data on a weighted sub-sample of women who reported they were pregnant during the surveys was extracted and analyzed.

Survey and participants

Details concerning the scope and methodology of the GMIS have already been published [11]. Briefly, the nationally representative survey was implemented by the Ghana Statistical Service (GSS), Ministry of Health (MOH) and National Malaria Control Programme of the Ghana Health Service with technical support from Inner City Fund (ICF) through the Demographic and Health Surveys (DHS) Program.

Sampling and sample size

The total number of women within the reproductive ages 15–49 years in the 2019 GMIS was 5181. However, in this study we limited the analysis to women who reported being pregnant during the survey. We weighted the entire data before sampling out pregnant women in all the 16 regions of Ghana. Therefore, the weighted sample of respondents (currently pregnant women) in the 2019 GMIS was 353.

Study variables

Dependent variable

The dependent variable for this study was the use of ITN. An ITN was defined in this study as a bed net that has been treated with insecticide to protect against mosquito bites and malaria. Eligible women were asked whether they slept under a treated mosquito net the night prior to the survey or otherwise. We coded ‘1’ for pregnant women who indicated they slept under ITN and coded ‘0’ for those who did not.

Predictor variables

We considered both individual and household level factors in this study. The rationale for the choice of these factors was based on their statistically significant association with ITN utilization in earlier studies [26, 29, 32, 35].

Individual socio-demographic factors

The individual-level socio-demographic factors included age of pregnant women (15–24, 25–34, 35–49) educational level (no education, primary, secondary, higher) religion (catholic, protestant, Muslim, pentecostal/charismatic, no religion) literacy level (illiterate, literate), ecological zones of residence (coastal zone, middle belt, northern zone) place of residence (urban, rural) ethnicity (Akan, Ga/Dangme, Ewe, Mole-Dagbani, Others) and parity (1–3, 4–6, 7 or more).

Household level factors

We considered the following household-level factors in the study: sex of household head (male and female), age of household head (20–29,30–39, 40–49, 50–59,60–69, 70+) and household wealth quintile (poorest, poorer, middle, richer, richest). The other variables included household source of drinking water, type of toilet facility and type of cooking fuel used by the household. The measurement and classification of the variable ‘household source of drinking water’ was guided by the WHO/United Nations International Children’s Emergency Fund Joint Monitoring Programme for Water Supply, Sanitation and Hygiene (WHO/UNICEF-JMP) classification of source of drinking water. For this study, the variable had been classified into two: improved and unimproved source of drinking water. In this study, improved source of drinking water comprised pipe-borne water inside dwelling, piped into dwelling, pipe to yard/plot, piped to neighbour’s house/compound, tube well water, borehole, protected dug well, protected well, protected spring and rainwater collection, bottled water and sachet water. Unimproved source of drinking water in this study included unprotected well, surface from spring, unprotected spring, river/dam, tanker truck and cart with a small tank. Type of toilet facility was also categorized into two improved and unimproved. The classification of improved toilet facility was also guided by the WHO/UNICEF-JMP classification of sanitation technologies. Improved toilet facilities in this study comprised flushed to pipe sewer, flushed to septic tank, flushed to pit latrine, flushed to unknown place, flushed to bio-digester, ventilated improved pit latrine (VIP), pit latrine with slab, pit toilet latrine and composting toilets. The unimproved toilet facility included flush to somewhere else, pit without slab/open pit, no facility, bush/field and hanging toilet/latrine. Type of household cooking fuel was categorized into the following: Liquified Petroleum Gas (LPG), Charcoal, Fuel wood and other cooking fuel (straw/shrub/grass, agricultural crops, and animal dung).

Statistical analysis

We analyzed the data with SPSS version 22. In analyzing the data, we followed three stages. The first stage was the use of simple descriptive statistics to describe the outcome and predictor variables. The second stage involved a cross-tabulation of all the individual and household level factors against the use of ITN among pregnant women. In the third stage, we developed three different models that involved multilevel binary logistic regression analyses to assess the effect of individual and household level factors on pregnant women’s use of insecticides treated bed nets. Model I analyzed the effect of only individual-level factors, model II analyzed the effect of only household-level factors, while model III analyzed both individual and household level factors on the use of ITN among pregnant women. For all three models, we presented the adjusted odds ratios (AOR) and their associated 95% confidence intervals (CIs). We also applied sample weight (v005/1,000,000) in weighting the entire data to correct possible over and under sampling issues.

Results

Socio-demographic and insecticide-treated bed net utilization among pregnant women in Ghana

Table 1 shows the individual socio-demographic characteristics of ownership and use of ITN among pregnant women in Ghana. About 85% of pregnant women owned at least one treated bed net in Ghana. A higher proportion (50.8%) of pregnant women reported not using treated bed nets compared to 49.2% who used ITNs. About 46% of the respondents were aged 25–34 years constituting the highest proportion of pregnant women in any of the age categories. More than half (51.6%) had attained secondary level of education and an almost equal proportion were literate. With regards to residence, a higher proportion (40.8%) of pregnant women resided in the middle belt compared to other ecological zones of the country. More than half (58.5%) of pregnant women resided in rural areas with a higher proportion (38.9%) belonging to the Akan ethnic group. About 7 out of 10 pregnant women in Ghana had between 1 and 3 children while 5% had 7 or more children.

Table 1 Individual socio-demographic characteristics and use of ITN net among pregnant women in Ghana

Household factors and use of insecticide treated bet net among pregnant women in Ghana

Table 2 shows the household characteristics of pregnant women and their utilization of ITN. The results showed that 77.1% of pregnant women belonged to male-headed households. The highest proportion (35.4%) of the heads of households were between ages 30–39 years. Highest proportion of (22.0%) pregnant women belonged to the poorest household wealth quintile category with the lowest proportion (18.9%) belonging to the richer wealth quintile. About 6 out of 10 pregnant women belong to households that access improved source of drinking water as well as improved toilet facility. Additionally, 44.4% of pregnant women in 2019 belonged to households that used fuel wood as the main type of cooking fuel. This proportion constituted the highest compared to other types of household cooking fuel.

Table 2 Household characteristics and use of ITN among pregnant women in Ghana

Association between individual and household level factors and use of ITN among pregnant women in Ghana

Table 3 shows a chi-square analysis between individual-level and household level factors and use of ITN among pregnant women in Ghana. Individual socio-demographic factors of pregnant women such as educational level, literacy level, ecological zone of residence, place of residence, ethnicity and parity were found to be significantly associated with the use of ITN at p < 0.05. With regards to household level factors, sex of household head, age of household head, wealth quintile, household source of drinking water, type of toilet facility and type of cooking fuel had a significant association with use of ITN among pregnant women in Ghana at p < 0.05.

Table 3 Association between individual, household level factors and use of ITN among pregnant women in Ghana

There was a significant difference [p = 0.002] in ITN use among pregnant women by their educational level with higher ITN use being recorded among women with no education (63.4%) relative to the other categories. Similarly, higher use of ITN was found among illiterate pregnant women (56.6%) compared to literate pregnant women (42.2%) at p = 0.007. The study also found that, a higher proportion (64.4%) of pregnant women who reside in the Northern ecological zone used ITNs more as compared to those who reside in the Middle belt (49.3%) and Coastal zone (40.9%) [p = 0.005]. There was also a significant difference in ITN use among pregnant women who are urban residents (32.7%) and those who resided in rural areas (60.9%) [p < 0.001]. Pregnant women who belong to the Mole-Dagbani ethnic background recorded higher use (59.5%) of ITN relative to other ethnic groups (p = 0.012). Higher use of ITN was recorded among pregnant women with 7 or more children (61.1%) followed by those with 4–6 children and 1–3 children represented by 58.4 and 44.3% respectively (p = 0.034).

Regarding household factors, a statistically significant [p = 0.024] difference was established between the use of ITN among pregnant women who dwell in male-headed (52.6%) households and those who dwell in female-headed households (38.3%). Pregnant women who resided in households headed by persons aged 60–69 years (84.0%) recorded higher ITN utilisation compared to other age categories [p = 0.002]. ITN use by pregnant women was higher among pregnant women from the poorest household wealth quintiles (70.5%) as compared to those from the richest household quintiles (19.4%) [p < 0.001]. A statistically significant association [p = 0.005] was found between household source of drinking water and ITN utilisation, with higher ITN use recorded among pregnant women who belong to household that have access to improved sources of drinking water (55.2%) compared to those using unimproved drinking water sources (39.9%). A higher proportion of pregnant women belonging to households with unimproved toilet facilities (67.5%) used ITN relative to their counterparts who had access to improved toilet facilities (39.9%). ITN use was higher among pregnant women who belonged to the household that used fuel wood (69.9%) as their main source of cooking fuel than among those from households that used other types of household cooking fuels [p = 0.000].

Individual and household factors influencing the use of ITN among pregnant women in Ghana

Table 4 presents results on the individual and household factors that influence the use of ITN among pregnant women in Ghana. In the Model 1 (only individual-level variables), educational level and place of residence significantly predicted the use of ITN among pregnant women in Ghana. In terms of educational level, the results showed that pregnant women with no formal education (AOR = 5.585, CI: 1.32–23.72) and secondary education (AOR = 3.509, CI: 1.08–11.44) had higher odds of ITN utilisation compared to those with tertiary/higher education. Regarding place of residence, compared to those who resided in rural areas, pregnant women who resided in urban areas (AOR = 0.355, CI: 0.22–0.58) had lower odds of ITN utilisation. In the second model (only household-level variables), sex and age of household heads were significant predictors of ITN use among pregnant women in Ghana. Pregnant women who belonged to male-headed households (AOR = 1.870, CI: 1.00–3.49) had higher likelihood of ITN utilisation relative to those who belong to female headed households. Pregnant women whose household heads were aged between 40 and 49 years were less likely (AOR = 0.437, CI: 0.19–0.99) to use ITN as compared to those whose household heads were aged 20–29 years. Additionally, pregnant women who belonged to households with heads of households aged between 60 and 69 years were more likely to use ITNs as compared to pregnant women whose household heads were aged between 20 and 29 years (AOR = 4.303, CI: 1.16–15.97). The third model, which combined individual and household level factors, showed that age of pregnant women, their ethnic background, sex and age of household heads and household wealth quintile were significant in predicting ITN utilisation among pregnant women in Ghana. Pregnant women aged 35–49 years (AOR = 3.403, CI: 1.19–9.73) had a higher likelihood of using ITN compared to those aged 15–24 years. Pregnant women from Akan ethnic background, were more likely (AOR = 7.234, CI:1.50–34.96) to use ITN as compared to those who belonged to other ethnic groups. Additionally, pregnant women who belonged to households with household heads aged between 40 and 49 years and 50–59 years (AOR = 0.239, CI:0.08–0.72) were less likely to use ITN (AOR = 0.175, CI:0.07–0.47) relative to those whose household heads were aged between 20 and 29 years. Pregnant women from households belonging to the richer wealth quintile (AOR = 0.184, CI: 0.05–0.68) and richest wealth quintiles (AOR = 0.107, CI: 0.02–0.55) were less likely to use ITNs as, compared to those from households belonging to the poorest household wealth index.

Table 4 Multilevel logistic regression of individual and household level factors influencing use of ITN among pregnant women in Ghana

Discussion

Summary of main findings

The study aimed to examine the individual socio-demographic and household factors associated with the use of insecticide treated net by pregnant women in Ghana. The results indicate that the use of ITN among pregnant women in Ghana is low, with only 4 out of 10 pregnant women reporting the use of an ITN the previous night before the survey to prevent malaria. The individual socio-demographic factors (model I) associated with pregnant women’s use of ITN are their educational level and place of residence. The household factors (model II) influencing pregnant women’s use of ITNs for malaria prevention are the sex and age of household heads. A combination of individual socio-demographic and household factors in model III revealed age, and ethnic background of pregnant women, and household level factors such as sex and age of household heads and household wealth quintile were significant in predicting ITN use among pregnant women in Ghana.

Synthesis with earlier studies

The prevalence of ITN use by pregnant women in this study is similar to prevalence reported in other sub-Saharan African countries such as Ethiopia (47.6%) [34], Kenya (52%) [39], Malawi (45.9) [32], Nigeria (19.2%) [40] and Uganda (35%) [42]. Reasons associated with the relatively low utilisation of ITN by pregnant women in these studies were high room temperature resulting in discomfort [20, 33, 37, 38], belief that malaria is no longer a major health problem [29, 43], poor quality of ITNs [44], reliance on other alternative malaria preventive measures [45]. The predominant reason for not using ITN by pregnant women is the discomfort experienced when sleeping under these treated bednets due to the high room temperature. Studies within the Africa and Asia regions suggest that treated bednet reduces the flow of air [46], and this explains the heat and warmness under a bednet [47,48,49]. There have been attempts by studies on a pilot basis to include small fans to increase the flow of air with the aim of ensuring comfort under treated bednets, thereby increasing the proportion of pregnant women sleeping under treated bed net [50]. This is important as several building in Ghana are poorly ventilated in additional to poor layout plans. Consequently, affecting room temperature and use of ITN.

The study showed that pregnant women aged 35–49 years had higher odds of using ITN to prevent malaria, compared to those aged 15–24 years after controlling for household factors. The finding of this study supports results of earlier studies in Cameroon [37], Kenya [39] and Senegal [51], which found increasing ITN use associated with relatively older pregnant women. However, a number of studies have found contrary evidence where higher ITN use was found among relatively younger pregnant women (20 years and below) relative to older women (30 years and above) [33, 34, 36, 52]. Other studies found no significant association between age of pregnant women and ITN utilisation [32, 35, 38, 43].

This study also found that pregnant women with no formal education and those who attained secondary education had higher odds of using ITN to prevent malaria, compared to those who had attained tertiary education without controlling for the effect of household factors. This finding is contrary to earlier studies carried out in sub-Saharan Africa, which found higher ITN use among highly educated pregnant women compared to uneducated pregnant women [20, 34, 37, 38]. The probable dominant reason given is that people with higher education are expected to have deeper knowledge and understanding about the usefulness and essence of using ITN for malaria prevention. This study reveals how the households’ pregnant women belong to influence their individual factors in ITN utilization in malaria prevention. For instance, ITN use is generally lower among uneducated pregnant women in the literature, however, the result of this study shows higher use of ITN among uneducated pregnant women relative to the educated ones after controlling for the effects of their household characteristics.

The study also showed that pregnant women residing in urban areas had lower odds of using ITN for malaria prevention relative to women in the rural areas. This study finding seems contrary to the findings of previous studies in the African sub-region that found higher use of ITN among pregnant women residing in urban areas [22, 32, 38, 53, 54]. The predominant reasons attributed to this phenomenon is the possibility of pregnant women having access to malaria prevention resources including ITN, pregnant women in urban centres having more knowledge about the essence of malaria prevention especially during pregnancy [32] and pregnant women in the urban centre having more extensive media exposure than their rural counterparts [53]. The findings of this study however suggest that the rural-urban disparity in ITN use among pregnant women in malaria prevention needs to be relooked at. It is argued in the literature that there is high use of ITN in rural areas because of the existence of various malaria control efforts and free distribution of ITNs [35]. Also, rural residents are less able to afford malaria treatment and therefore take preventive measures more seriously than those residing in the urban areas [37].

Another important finding in this study is that pregnant women who belong to households headed by males were more likely to use ITN compared to female households. This is in line with other studies in Nigeria [54], Sierra Leone [17] and Liberia [55]. The basic explanation could be that male headed household are often characterised by display of strict rules, discipline, and authority in making household decision. This may influence the adherence and regular use of ITN by pregnant women in such households [17].

Age of household head was also significant in predicting ITN use among pregnant women for malaria prevention. The odds of pregnant women using ITN is lower in households with relatively older (30–59) heads compared to heads of household aged 20–29 years. This study findings corroborates with an earlier study in Kenya [39]. This implies that as the age of household head gets increases, the odds of using an ITN decreases. It was also found that pregnant women who belong to the Akan ethnic group had higher odds of using ITN for malaria prevention, compared to pregnant women in other ethnic groups. Other related studies in Ghana did not find any significant relationship between ethnicity and ITN use among pregnant women [56].

Strengths and limitations of the study

The main strength of this study is the use of malaria-related nationally representative data to examine individual and household factors associated with the use of ITN among pregnant women in Ghana. The findings can, therefore, be generalised to all pregnant women in Ghana. Regardless of these outlined strengths, this was a cross sectional study, and it will be difficult to deduce any causal interpretation. Also, the use of ITN may be influenced by seasonality of mosquito abundance and the data did not take into consideration this phenomenon. However, this we believe did not to a large extent affect the accuracy of result obtained. Finally, because the study used secondary data, it could not account for other factors at the community and national level that might have influenced pregnant women’s use of ITNs.

Conclusion

The study found that 49.2% of pregnant women use ITN for malaria prevention in Ghana. Both individual and household factors were related to use of ITN among pregnant women. Particularly, age, educational level, place of residence, ethnicity, sex and age of household head and household wealth index were related to ITN utilisation among pregnant women. These factors ought to be reconsidered to improve and strengthen various malaria prevention strategies among vulnerable populations and in malaria endemic areas by the National Malaria Control Programme in achieving universal coverage of ITN among pregnant women.

Availability of data and materials

The datasets used for this study is openly available and can be accessed via https://dhsprogram.com/.

Abbreviations

AOR:

Adjusted Odds Ratio

CI:

Confidence Interval

DHS:

Demographic and Health Surveys

GPS:

Global Positioning System

GMIS:

Ghana Malaria Indicator Survey

GSS:

Ghana Statistical Service

iCCM:

Integrated Community Case Management

ICF:

Inner City Fund

IPTp:

Intermittent Preventive Treatment in Pregnancy

IRB:

Institutional Review Board

IRS:

Indoor Residual Spraying

ITN:

Insecticides Treated Bed net

JMP:

Joint Monitoring Programme

LPG:

Liquified Petroleum Gas

LLIN:

Long Lasting Insecticide Net

MIP:

Malaria In Pregnancy

MOH:

Ministry of Health

NMCP:

National Malaria Control Programme

SMC:

Seasonal Malaria Chemoprevention

UNICEF:

United Nation International Children Emergency Fund

VIP:

Ventilated Improved Pit

WHO:

World Health Organisation

References

  1. World Health Organization. World malaria report 2020: 20 years of global progress and challenges. In World malaria report 2020: 20 years of global progress and challenges; 2020.

  2. World Health Organization, Center for Disease Control. Basic malaria microscopy: tutor's guide. Geneva: World Health Organization; 2010.

  3. World Health Organization. Global technical strategy for malaria 2016-2030. Geneva: World Health Organization; 2015. p. 1–35.

  4. Schantz-Dunn J, Nour NM. Malaria and pregnancy: a global health perspective. Rev Obstet Gynecol. 2009;2(3):186.

    PubMed  PubMed Central  Google Scholar 

  5. Moore KA, Fowkes FJ, Wiladphaingern J, San Wai N, Paw MK, Pimanpanarak M, et al. Mediation of the effect of malaria in pregnancy on stillbirth and neonatal death in an area of low transmission: observational data analysis. BMC Med. 2017;15(1):1–1.

    Article  Google Scholar 

  6. Roman E, Wallon M, Brieger W, Dickerson A, Rawlins B, Agarwal K. Moving malaria in pregnancy programs from neglect to priority: experience from Malawi, Senegal, and Zambia. Glob Health Sci Pract. 2014;2(1):55–71.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Lawn JE, Blencowe H, Waiswa P, Amouzou A, Mathers C, Hogan D, et al. Stillbirths: rates, risk factors, and acceleration towards 2030. Lancet. 2016;387(10018):587–603.

    Article  PubMed  Google Scholar 

  8. Awine T, Malm K, Bart-Plange C, Silal SP. Towards malaria control and elimination in Ghana: challenges and decision making tools to guide planning. Glob Health Action. 2017;10(1):1381471.

    Article  PubMed  PubMed Central  Google Scholar 

  9. National Malaria Control Programme, Ghana. 2017 Annual report. Ghana: National Malaria Control Programme of Ghana; 2018. p. 1–151.

  10. Ghana Health Service. Ghana Health Service 2018. Annu Rep. 2019:1–129.

  11. GSS, GHS. Ghana statistical service (GSS), Ghana health service (GHS), and ICF. Ghana malaria Indicator survey 2019. Accra, and Rockville: GSS, GHS, and ICF; 2020.

    Google Scholar 

  12. Lengeler C. Insecticide-treated bednets and curtains for preventing malaria. Cochrane Database Syst Rev. 2000;(2):CD000363.

  13. Mueller DH, Wiseman V, Bakusa D, Morgah K, Daré A, Tchamdja P. Cost-effectiveness analysis of insecticide-treated net distribution as part of the Togo integrated child health campaign. Malar J. 2008;7(1):1–7.

    Article  Google Scholar 

  14. Taremwa IM, Ashaba S, Ayebazibwe C, Kemeza I, Adrama HO, Omoding D, et al. Mind the gap: scaling up the utilization of insecticide treated mosquito nets using a knowledge translation model in Isingiro district, rural south western Uganda. Health Psychol Behav Med. 2020;8(1):383–97.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kleinschmidt I, Schwabe C, Shiva M, Segura JL, Sima V, Mabunda SJ, et al. Combining indoor residual spraying and insecticide-treated net interventions. Am J Trop Med Hyg. 2009;81(3):519–24.

    Article  PubMed  Google Scholar 

  16. Loha E, Lindtjørn B. Model variations in predicting incidence of Plasmodium falciparum malaria using 1998-2007 morbidity and meteorological data from south Ethiopia. Malaria J. 2010;9(1):1–8.

  17. Bennett A, Smith SJ, Yambasu S, Jambai A, Alemu W, Kabano A, et al. Household possession and use of insecticide-treated mosquito nets in Sierra Leone 6 months after a national mass-distribution campaign. Plos One. 2012;7(5):e37927.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Omer SA, Idress HE, Adam I, Abdelrahim M, Noureldein AN, Abdelrazig AM, et al. Placental malaria and its effect on pregnancy outcomes in Sudanese women from Blue Nile state. Malar J. 2017;16(1):1–8.

    Article  Google Scholar 

  19. Dombrowski JG, Souza RM, Silva NR, Barateiro A, Epiphanio S, Gonçalves LA, et al. Malaria during pregnancy and newborn outcome in an unstable transmission area in Brazil: a population-based record linkage study. Plos One. 2018;13(6):e0199415.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Manu G, Boamah-Kaali EA, Febir LG, Ayipah E, Owusu-Agyei S, Asante KP. Low Utilization of Insecticide-Treated Bed Net among Pregnant Women in the Middle Belt of Ghana. Malaria Res Treat. 2017;2017(1-8):7481210.

  21. Singh M, Brown G, Rogerson SJ. Ownership and use of insecticide-treated nets during pregnancy in sub-Saharan Africa: a review. Malar J. 2013;12(1):1–0.

    Article  Google Scholar 

  22. Ankomah A, Adebayo SB, Arogundade ED, Anyanti J, Nwokolo E, Ladipo O, et al. Determinants of insecticide-treated net ownership and utilization among pregnant women in Nigeria. BMC Public Health. 2012;12(1):1–0.

    Article  Google Scholar 

  23. Diema Konlan K, Japiong M, Dodam Konlan K, Afaya A, Salia SM, Kombat JM. Utilization of insecticide treated bed nets (ITNs) among caregivers of children under five years in the ho municipality. Interdiscip Perspect Infect Dis. 2019;1:2019.

    Google Scholar 

  24. Ahmed SM, Zerihun A. Possession and usage of insecticidal bed nets among the people of Uganda: is BRAC Uganda health Programme pursuing a pro-poor path? Plos One. 2010;5(9):e12660.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Pulford J, Hetzel MW, Bryant M, Siba PM, Mueller I. Reported reasons for not using a mosquito net when one is available: a review of the published literature. Malar J. 2011;10(1):1–0.

    Article  Google Scholar 

  26. Njumkeng C, Apinjoh TO, Anchang-Kimbi JK, Amin ET, Tanue EA, Njua-Yafi C, et al. Coverage and usage of insecticide treated nets (ITNs) within households: associated factors and effect on the prevalance of malaria parasitemia in the Mount Cameroon area. BMC Public Health. 2019;19(1):1–1.

    Article  Google Scholar 

  27. Ahorlu CS, Adongo P, Koenker H, Zigirumugabe S, Sika-Bright S, Koka E, et al. Understanding the gap between access and use: a qualitative study on barriers and facilitators to insecticide-treated net use in Ghana. Malar J. 2019;18(1):1–3.

    Article  Google Scholar 

  28. Hill J, Hoyt J, van Eijk AM, D'Mello-Guyett L, Ter Kuile FO, Steketee R, et al. Factors affecting the delivery, access, and use of interventions to prevent malaria in pregnancy in sub-Saharan Africa: a systematic review and meta-analysis. Plos Med. 2013;10(7):e1001488.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Nyavor KD, Kweku M, Agbemafle I, Takramah W, Norman I, Tarkang E, Binka F. Assessing the ownership, usage and knowledge of Insecticide Treated Nets (ITNs) in Malaria Prevention in the Hohoe Municipality, Ghana. Pan Afr Med J. 2017;28:67.

  30. Scates SS, Finn TP, Wisniewski J, Dadi D, Mandike R, Khamis M, et al. Costs of insecticide-treated bed net distribution systems in sub-Saharan Africa. Malar J. 2020;19(1):1–8.

    Article  Google Scholar 

  31. Larson PS, Mathanga DP, Campbell CH, Wilson ML. Distance to health services influences insecticide-treated net possession and use among six to 59 month-old children in Malawi. Malar J. 2012;11(1):1–9.

    Article  Google Scholar 

  32. Nkoka O, Chuang TW, Chuang KY, Chen YH. Factors associated with insecticide-treated net usage among women of childbearing age in Malawi: a multilevel analysis. Malar J. 2018;17(1):1–6.

    Article  Google Scholar 

  33. Yitayew AE, Enyew HD, Goshu YA. Utilization and Associated Factors of Insecticide Treated Bed Net among Pregnant Women Attending Antenatal Clinic of Addis Zemen Hospital, North-Western Ethiopia: An Institutional Based Study. Malar Res Treat. 2018;2018:3647184.

  34. Fuge TG, Ayanto SY, Gurmamo FL. Assessment of knowledge, attitude and practice about malaria and ITNs utilization among pregnant women in Shashogo District, Southern Ethiopia. Malar J. 2015;14(1):1–9.

    Article  Google Scholar 

  35. Kanmiki EW, Awoonor-Williams JK, Phillips JF, Kachur SP, Achana SF, Akazili J, et al. Socio-economic and demographic disparities in ownership and use of insecticide-treated bed nets for preventing malaria among rural reproductive-aged women in northern Ghana. Plos One. 2019;14(1):e0211365.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Darko E, Tetteh J, Ayanore MA, Damoah-Aferi I. Socio-demographic determinants associated with ownership and use of long lasting insecticide treated nets among pregnant women in the Wa Municipality of Ghana. Pan Afr Med J. 2019;33:81.

  37. Kimbi HK, Nkesa SB, Ndamukong-Nyanga JL, Sumbele IU, Atashili J, Atanga MB. Socio-demographic factors influencing the ownership and utilization of insecticide-treated bed nets among malaria vulnerable groups in the Buea Health District, Cameroon. BMC Res Notes. 2014;7(1):1–8.

    Article  Google Scholar 

  38. Inungu JN, Ankiba N, Minelli M, Mumford V, Bolekela D, Mukoso B, Onema W, Kouton E, Raji D. Use of Insecticide-Treated Mosquito Net among Pregnant Women and Guardians of Children under Five in the Democratic Republic of the Congo. Malar Res Treat. 2017;2017:5923696.

  39. Choonara S, Odimegwu CO, Elwange BC. Factors influencing the usage of different types of malaria prevention methods during pregnancy in Kenya. Afr Health Sci. 2015;15(2):413–9.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Ezire O, Adebayo SB, Idogho O, Bamgboye EA, Nwokolo E. Determinants of use of insecticide-treated nets among pregnant women in Nigeria. Int J Women's Health. 2015;7:655.

    Article  Google Scholar 

  41. Malaria RB. World malaria report 2005. Geneva: World Health Organization and UNICEF; 2005. p. 1–316.

  42. Obol JH, Ononge S, Orach CG. Utilisation of insecticide treated nets among pregnant women in Gulu: a post conflict district in northern Uganda. Afr Health Sci. 2013;13(4):962–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Belay M, Deressa W. Use of insecticide treated nets by pregnant women and associated factors in a pre-dominantly rural population in northern Ethiopia. Trop Med Int Health. 2008;13(10):1303–13.

    Article  PubMed  Google Scholar 

  44. Musa OI, Salaudeen GA, Jimoh RO. Awareness and use of insecticide treated nets among women attending ante-natal clinic in a northern state of Nigeria. J Pak Med Assoc. 2009;59:354.

    PubMed  Google Scholar 

  45. Eleazar C, Emenuga VN, Udoh IP, Ndilemeni UC. Factors Affecting Usage of ITN for Malaria Control by Pregnant Women in South East Nigeria. Europe PMC. 2020. https://doi.org/10.21203/rs.3.rs-98601/v1.

  46. Von Seidlein L, Ikonomidis K, Bruun R, Jawara M, Pinder M, Knols BG, et al. Airflow attenuation and bed net utilization: observations from Africa and Asia. Malar J. 2012;11(1):1–1.

    Google Scholar 

  47. Koenker HM, Loll D, Rweyemamu D, Ali AS. A good night’s sleep and the habit of net use: perceptions of risk and reasons for bed net use in Bukoba and Zanzibar. Malar J. 2013;12(1):1–2.

    Article  Google Scholar 

  48. Briët OJ, Yukich JO, Pfeiffer C, Miller W, Jaeger MS, Khanna N, et al. The effect of small solar powered ‘Bͻkͻͻ’net fans on mosquito net use: results from a randomized controlled cross-over trial in southern Ghana. Malar J. 2017;16(1):1–1.

    Article  Google Scholar 

  49. von Seidlein L, Ikonomidis K, Mshamu S, Nkya TE, Mukaka M, Pell C, et al. Affordable house designs to improve health in rural Africa: a field study from northeastern Tanzania. Lancet Planet Health. 2017;1(5):e188–99.

    Article  Google Scholar 

  50. Jaeger MS, Briët OJ, Keating J, Ahorlu CK, Yukich JO, Oppong S, et al. Perceptions on the effect of small electric fans on comfort inside bed nets in southern Ghana: a qualitative study. Malar J. 2016;15(1):1–7.

    Article  Google Scholar 

  51. Mbengue MA, Bei AK, Mboup A, Ahouidi A, Sarr M, Mboup S, et al. Factors influencing the use of malaria prevention strategies by women in Senegal: a cross-sectional study. Malar J. 2017;16(1):1–9.

    Article  Google Scholar 

  52. Ngwibete BA, James O. Attitudes toward utilization of insecticide-treated bed nets among pregnant women and care-takers of under-five. In: Infection Control. Tips; 2016.

    Google Scholar 

  53. Aluko JO, Oluwatosin AO. Utilization of insecticide treated nets during pregnancy among postpartum women in Ibadan, Nigeria: a cross-sectional study. BMC Pregnancy Childbirth. 2012;12:21.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Alawode OA, Chima V, Awoleye AF. Household characteristics as determinants of ownership of mosquito nets in urban households in Nigeria. Sci Afr. 2019;6:e00156.

    Google Scholar 

  55. Babalola S, Ricotta E, Awantang G, Lewicky N, Koenker H, Toso M. Correlates of intra-household ITN use in Liberia: a multilevel analysis of household survey data. Plos One. 2016;11(7):e0158331.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Dako-Gyeke M, Kofie HM. Factors influencing prevention and control of malaria among pregnant women resident in urban slums, southern Ghana. Afr J Reprod Health. 2015;19(1):44–53.

    PubMed  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge the academic staff of the Institute of Health Research (IHR) and Ghana Statistical Service (GSS) for their invaluable contribution to this work.

Funding

None.

Author information

Authors and Affiliations

Authors

Contributions

DK conceptualised, designed the study, and obtained the data. D. K analysed and interpreted the data. The entire manuscript was drafted by D.K. It was critically reviewed and revised by M.A.A, A.K.M, M. I, P. D, M. D, E. A, R.K.A. E.K.A. All authors approved the final version of the manuscript.

Corresponding author

Correspondence to Desmond Klu.

Ethics declarations

Ethics approval and consent to participate

The Ethical Review Committee of Ghana Health Services and Informed Consent Form Institutional Review Board approved the protocol for the 2019 Ghana Malaria Indicator Survey.

Informed consent was obtained from respondents before interviews were conducted. Again, all methods used were carried out in accordance with relevant guidelines and procedures.

Consent for publication

Not applicable.

Competing interests

None declared.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Klu, D., Aberese-Ako, M., Manyeh, A.K. et al. Mixed effect analysis of factors influencing the use of insecticides treated bed nets among pregnant women in Ghana: evidence from the 2019 Malaria Indicator Survey. BMC Pregnancy Childbirth 22, 258 (2022). https://doi.org/10.1186/s12884-022-04586-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12884-022-04586-2

Keywords