Magnitude and determinants of food insecurity among pregnant women in Nigeria: evidence from a nationwide cross-sectional survey

doi:10.21203/rs.3.rs-3334072/v1

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Magnitude and determinants of food insecurity among pregnant women in Nigeria: evidence from a nationwide cross-sectional survey

https://doi.org/10.21203/rs.3.rs-3334072/v1

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Background

Food security is crucial to improve maternal nutrition during pregnancy. However, evidence of the magnitude and social determinants of food insecurity among pregnant women is scarce in Nigeria. Therefore, this study used nationally representative data to assess the prevalence and determinants of food insecurity among pregnant women in Nigeria.

Methods

The study setting was Nigeria. The study is a secondary analysis of data from the Nigeria Demographic and Health Survey 2018 using a cross-sectional household survey design. We adjusted the data for sampling weight, stratification, and cluster sampling design. The dependent variable was food security status: food security (dietary diversity) and food insecurity (no dietary diversity). The independent variables included women's socio-demographic and household characteristics. We cross-tabulated food security status and pregnant women's characteristics to measure the association using the Chi-square statistics. We included all significant variables from the bivariate analysis in a complex sample logistic regression model to determine the adjusted effect of each independent variable on food insecurity. We set the statistical significance for all inferential analyses at p <0.05.

Results

The prevalence of food insecurity among pregnant women in Nigeria is 45%. Residing in the North-East (AOR:1.70, 95%CI:1.26-2.29, p<0.001), Southeast (AOR: 1.47, 95%CI:1.04-2.07, p=0.028) regions, having no education (AOR:1.86, 95%CI:1.28-2.70, p=0.001), primary education (AOR:1.86, 95%CI:1.28-2.69, p=0.001), married/living with a partner (AOR:3.33, 95%CI:1.28-8.67, p=0.014), widowed/divorced/separated (AOR:3.83,95%CI:1.68-8.73, p=0.001), non-exposure to television (AOR:1.55, 95%CI:1.26-1.92, p<0.001), healthcare access barrier (AOR:1.69, 95%CI:1.43-1.99, p<0.001) increased pregnant women's likelihood of being food-insecure.

Conclusions

The proportion of food-insecure pregnant women needs to improve in Nigeria. The government and its partners must address the cost of healthy diets, abate conflicts, and strengthen the implementation of food and nutrition policies. It is imperative to incorporate the social determinants of food insecurity identified in this study into policies and plans to improve food security among pregnant women in Nigeria.

Food security

food insecurity

dietary diversity

pregnant women

Nigeria

Food insecurity, described as the lack of nutritionally adequate and safe food or a limited ability to acquire necessary food in socially acceptable ways, is not only rising in sub-Saharan Africa but also more prevalent among women than men[1, 2]. Nigeria has the world's fifth-largest burden of people experiencing food insecurity. Food insecurity limits countries from eradicating hunger and malnutrition by constraining food availability, access, and utilization, especially among pregnant women and other vulnerable people in low-and middle-income countries[2-5]. Dietary diversity, reflecting individuals' access to various foods, measures food security[6-9]. Food-insecure pregnant women have low dietary diversity[8-10]. The magnitude of food insecurity among pregnant women was 41-84.4% in Ethiopia[7, 8, 10-19], 53.1-80.1% in other African countries[1, 20], and 30.2-51% globally[3, 9, 21, 22]. Food insecurity among pregnant women has worsened because of increasing poverty and disruption of primary health services associated with the COVID-19 pandemic[23-25]. Disparities in social determinants of health contribute to food insecurity. Consequently, health and nutrition stakeholders must anticipate and track food insecurity among pregnant women and its associated inequities and social determinants[23, 25].

Adequate dietary diversity during pregnancy provides women with sufficient energy, macronutrients and micronutrients to support pregnancy, positive birth outcomes and good health for the child[7]. Nevertheless, food insecurity among women accounts for seven per cent of the global disease burden and at least 20% of maternal deaths and poor maternal outcomes[26, 27]. Food insecurity among pregnant women also leads to disordered eating, gestational weight gain and diabetes[28-30], hypertension[30], stress, anxiety, and depression[31-33], maternal and infant anaemia[3, 26, 32], intrauterine growth retardation and low birth weight[3, 26, 34], premature childbirth[3, 26, 35], and poor child development with lifelong difficulties in adulthood[3, 32]. It is, therefore, critical to understand the factors that predict pregnant women's food security and nutritional adequacy to support both the short- and long-term women’s health interventions to address the adverse effects of food insecurity[5, 36].

Published studies on the social determinants of food insecurity among pregnant women are growing. The findings of these studies indicate that food insecurity and inadequate dietary diversity among pregnant women are associated with older age[19], being married[37] and unmarried[4], Christianity[37], residing in rural areas[8, 10, 11, 13, 21], low participation in household decision-making[21], low women empowerment[12], low education[1, 3, 8, 9, 12-17, 36-39], unemployment[36, 37], low socioeconomic status[1, 3, 6, 10, 12, 21, 39], low income[8, 9, 13-15, 17, 18, 36, 37, 40], pregnant women from male headed households[17], high parity[1, 17, 37], large family size[8, 10, 17], low antenatal care attendance[15, 18], low frequency of listening to radio[11], mobile phone use[11], and poor nutritional knowledge[13, 15, 16, 19, 21, 39-41].

Despite policies and reforms to diversify the economy and boost domestic food production, Nigeria's dependence on food imports has remained elevated[42]. The adverse effects of the COVID-19 pandemic, persistent conflict and population displacement, the increase in fuel price, the devaluation of the Nigerian Naira against the United States dollar, and the surge in food inflation have exacerbated food insecurity in Nigeria[42]. Although nutrition policies have articulated programmes to ensure women’s optimal nutrition, studies examining food insecurity have focused on women generally[43-45]. Just one study examined food insecurity among pregnant women in Nigeria, but the lack of a nationally representative sample limits the generalizability of its findings[37]. More studies with robust methodology are needed to investigate the magnitude and determinants of food insecurity among pregnant women in Nigeria. Evidence of inequities in social determinants of food insecurity will be helpful to policymakers in designing tailored interventions to improve maternal nutrition during pregnancy. Therefore, this study used nationally representative data to assess the prevalence and determinants of food insecurity among pregnant women in Nigeria.

Study setting

The study setting was Nigeria. The Nigerian population was 195,874,683 in 2018 and grew at about 3%. Nigeria comprises 36 states and a Federal Capital Territory, delineated into six geopolitical regions and 774 local government areas (LGAs). The LGAs are composed of wards. The wards encompass enumeration areas demarcated by grouping households within a defined geographical cluster. Nigeria has a large informal economy, accounting for more than half of its national income and over 80 per cent of employment. The population living under moderate to severe food insecurity increased from 36.5 per cent in 2015 to 57.7 per cent in 2020. About 47.1% of adults lived under moderate or severe food insecurity in 2018.

Study design

The study is a secondary analysis of data from the Nigeria Demographic and Health Survey 2018 based on a cross-sectional household survey design.

Sampling strategy

The primary study calculated a sample size of 42,000 households using the Demographic Health Survey sample size determination formula. The primary study used a two-stage stratified sampling technique to select households from a sampling frame of households listed in Nigeria's 2006 Population and Housing Census. The primary sampling unit is a cluster of enumeration areas (EAs). Each state and the Federal Capital Territory was stratified into urban and rural areas, creating 74 sampling strata. The study selected 1,400 (580 urban and 820 rural) EAs in the first stage. The second stage involved selecting 30 households from every cluster through equal probability systematic sampling.

Data collection

The survey was successfully carried out in 1,389 clusters in 36 states and Federal Capital Territory comprising 747 LGAs from August to December 2018. Fieldwork did not take place in eleven clusters because of deteriorating law-and-order situations. Replacements and changes to the pre-selected households were not allowed in the implementing stages to prevent bias. The primary study included women of reproductive age, permanent residents or visitors who stayed in the sampled household the night before the survey. The exclusion criteria were women who did not agree to provide consent and women who fell outside 15-49 years. Our secondary analysis included only women who were currently pregnant during data collection.

Variables

Dependent variable

The dependent variable was food insecurity among pregnant women using inadequate dietary diversity as a proxy. Therefore, Food insecurity was measured using a 24-hour dietary recall following the guidelines outlined for calculating the minimum dietary diversity for women of reproductive age (MDD-W) indicator. The study derived the MDD-W indicator using ten food groups. The food groups are grain, roots and tubers; other vit A rich fruits and vegetables; any dark green leafy vegetables; any other fruits; any other vegetables; meat, poultry and fish; any eggs; any beans or peas; any nuts or seeds; and any milk or milk products. The primary study asked pregnant women to describe the foods consumed in the past 24 hours. Consumption of food groups received a score of '1'. Each pregnant woman's score ranged from '0 to 10'. The cumulative dietary diversity score was categorized to construct a dichotomized outcome variable: food security (consuming five or more food groups implies dietary diversity) and food insecurity (consuming less than five of the ten food groups implies no dietary diversity).

Independent variables

The variables included individual and household characteristics. The study included age, marital status (Never in a union, married/living with a partner, and divorced/separated/widowed), sex of household head (female and male), religion (Christians, Islam, and Traditional religion/others), and gender attitude (good, bad). Gender attitudes were measured using five variables describing women's attitudes towards domestic violence, including whether beating was justified if the wife goes out without telling her husband, neglects the children, argues, refuses sex with her husband, and burns food. Women who answered “Yes” and “Do not know” were coded as 1, while women who responded “No” were coded as 0. Women were categorized into good gender attitude if they answered “No” to all five variables and poor gender attitude if they answered “Yes” or “Do not know” to any of the five questions.

Other characteristics included were region (North-Central, North-East, North-West, Southeast, South-South, and South-West), type of residence (urban and rural), highest education (no education, primary, secondary, and higher), employment (unemployed and employed), wealth index (poor, moderate, rich), radio exposure (not at all, yes), television exposure (not at all, yes), ownership of mobile phone (yes, no), family size (<5, ≥5), total children ever born (0, 1, 2-4, ≥5), and healthcare access barrier (yes, no). We derived the healthcare access barrier from four questions in the Demographic and Health Survey— whether a woman faced problems getting money, distance, companionship, and permission to see a doctor. Facing at least one or more problems (money, distance, companionship, and permission) implies a healthcare access barrier and is coded as "1". In contrast, if she did not report money, distance, companionship, and permission-related barriers, she is considered not to have a healthcare access barrier and coded as “0”.

Statistical analysis

The study analyzed the data with SPSS 20 (IBM Corp., Armonk, NY). Before analysis, we adjusted the data for sampling weights, stratification, and multistage sampling. Adjusting the data accounted for the non-proportional allocation of the sample to the different states and provided representative population estimates. We summarized women's characteristics using frequencies and percentages. We cross-tabulated food security and pregnant women's characteristics to measure the association using the Chi-square statistics. The significant independent variables during bivariate analyses did not show multicollinearity, given that the variance inflation factors ranged from 1.02 – 2.35. We included all significant variables from the bivariate analysis in the multivariable complex sample logistic regression model to determine the adjusted effect of each independent variable on food insecurity. The results of regression analysis were presented by crude odds ratio (COR) and adjusted odds ratio (AOR) with 95% confidence intervals (CIs) and p-values. We set the statistical significance for all inferential analyses at p <0.05.

Ethical consideration

Given that the study was a secondary data analysis, this study did not need further ethical approval. The primary study obtained ethical approval from the National Health Research Ethics Committee of Nigeria and the ICF Institutional Review Board. The study also obtained informed consent from the participants before administering the questionnaires.

Individual and household characteristics of pregnant women

Table 1 shows the characteristics of pregnant women in the study. Pregnant women from the North-West comprised about 39% of the sample. Approximately 61% of pregnant women had less than secondary education and are employed. About 60% of pregnant women did not view television. Most pregnant women reside in rural areas and male-headed households, are Moslems, and have a good gender attitude.

[Insert Table 1]

The magnitude of food insecurity among pregnant women in Nigeria, 2018

The prevalence of food insecurity among pregnant women in Nigeria is 45% (Figure 1).

[Insert Figure 1]

Factors associated with food insecurity among pregnant women in Nigeria

Table 2 shows that food insecurity among pregnant women significantly differed by region, education, place of residence, religion, frequency of listening to radio, frequency of watching television, ownership of a mobile phone, wealth index, current marital status, and healthcare access.

[Insert Table 2]

Determinants of food insecurity among pregnant women in Nigeria

Residing in the North-East (AOR:1.70, 95%CI:1.26-2.29, p<0.001), Southeast (AOR: 1.47, 95%CI:1.04-2.07, p=0.028) regions, having no education (AOR:1.86, 95%CI:1.28-2.70, p=0.001), primary education (AOR:1.86, 95%CI:1.28-2.69, p=0.001), married/living with a partner (AOR:3.33, 95%CI:1.28-8.67, p=0.014), widowed/divorced/separated (AOR:3.83,95%CI:1.68-8.73, p=0.001), non-exposure to television (AOR:1.55, 95%CI:1.26-1.92, p<0.001), healthcare access barrier (AOR:1.69, 95%CI:1.43-1.99, p<0.001) increased pregnant women’s likelihood of being food-insecure (Table 3).

[Insert Table 3]

The magnitude and risk factors for food insecurity among pregnant women found in this study merit further exploration. Forty-five per cent of pregnant women were food-insecure in this study. The prevalence of food insecurity among pregnant women in the current study is consistent with evidence from preceding studies[10, 21]. In contrast, our findings are much higher than those from earlier studies[9, 16] but lower than those from other studies [1, 3, 7, 8, 11-15, 17, 18, 20, 22]. The mixed findings on the magnitude of food insecurity across different settings relate to disparities in social determinants of health, methodological differences in the measurement of food insecurity, seasonal variations in the timing of studies, differing food consumption patterns, and the effectiveness of nutrition interventions.

In the current study, the prevalence of food insecurity among pregnant women indicates a concern to address the fundamental causes of food insecurity in Nigeria. First, the cost of healthy diets, a critical cause of food insecurity, can improve when government subsidizes farming and improves the livelihood of the citizens, especially women[46]. Second, the government must abate conflicts to enhance access to agricultural land-holding, enabling family farming[47]. The third approach is to ensure efficient and equitable implementation of health sector nutrition interventions. With health and nutrition stakeholders, the government has prioritized interventions in the National Multisectoral Plan of Action for Food and Nutrition 2021-2025 and the National Policy on Maternal, Infant and Young Child Nutrition in Nigeria 2021[48]. To improve food security and other nutrition outcomes, the government must prioritize these policies through improved funding, adequate and motivated human resources, and effective leadership and management[49].

In this study, food insecurity among pregnant women in North-Central and Southeast Nigeria significantly differed from other geopolitical zones. One plausible reason for this difference is increased donor-supported community-based maternal and child nutrition and food security interventions in Northern Nigeria between 2013 and 2017, improving access to a micronutrient, use of health facilities, nutritional counselling, and dietary diversity in Northern Nigeria[50]. However, in the North-Central region, food insecurity is related to the persisting farmers-herdsmen conflict, decreasing agricultural land-holding size and family farming in the region whose mainstay occupation is farming[47]. Declining family farming and farming experience reduce the chances of food insecurity[51]. On the other hand, marital status and education influence food insecurity in the Southeast region. Results of a previous study show that unmarried persons with higher education were more food secure in Southeast Nigeria[52]. Our findings suggest that the government needs to prioritize the North-Central and Southeast regions when designing agricultural and nutritional interventions.

Our finding that low education is a risk factor for food insecurity is similar to the results of previous studies[1, 3, 8, 9, 12-17, 36-39]. The influence of education might be related to three explanations. First, educated women have access to better-paying jobs and predictable incomes with high purchasing power. Since the lack of affordability is a common cause of food insecurity in Nigeria, educated women can purchase more variety of foods than uneducated women. Secondly, educated women have better knowledge of diverse food groups and dietary practices than women with low education. Education empowers women, improves their decision-making capacity, and provides them with accurate information, clearing all misconceptions and myths surrounding food taboos. Two meaningful changes that might improve dietary diversity practices among pregnant women with low education are targeted nutrition literacy and sustained investment in women's education.

When examining relationships between marital status and food insecurity, our study revealed that being married, widowed, or separated predisposed pregnant women to food insecurity. Although our findings are consistent with a prior study showing that single pregnant women were more likely to have a high dietary diversity than married women[37], we anticipated that marriage would protect pregnant women from food insecurity since single women have more significant barriers to healthcare than partnered women. Partnership brings additional social and economic support to married women[53]. Equally, given that being pregnant in a male-headed household predisposed women to food insecurity[17], we also expected that widowed/divorced/separated pregnant women would have high dietary diversity. Nevertheless, in our study, single pregnant women seem to have more economic freedom to invest in their healthcare and nutrition than married and widowed/divorced women[37].

Results from this study show that not viewing television predisposed pregnant women to food insecurity. Evidence that African women tend to trust nutritional information shared from mainstream media such as television[54]. In our study, pregnant women who do not use the television were less likely to access quality nutrition information. Therefore, television presents an opportunity to reach women with tailored nutrition messages, dispelling misconceptions, misinformation, and myths that limit women’s adoption of diverse healthy diets. Low household television ownership might limit the use of television for nutrition education and behaviour change communication. Whereas 43.2% of households own a television in Nigeria, about a similar proportion of women use television[55]. The vast disparities in television ownership across Nigerian states, varying from 4.4 to 89.8%, and the income and geographical inequalities further constrain the use of television in Nigeria[55]. Therefore, household television ownership must improve before effectively deploying television to reach women with nutrition messages.

Pregnant women facing barriers to healthcare access were more likely to be food-insecure than those without healthcare access barriers. The role of barriers to accessing healthcare may be due to low antenatal care attendance[15, 18], resulting in poor nutritional knowledge among pregnant women[13, 15, 16, 19, 21, 39-41]. In the current study, almost 53% of women with healthcare access barriers have nutrition education constraints, decreasing their awareness of the benefits and readiness to adopt diversified dietary practices. Women faced several types of barriers to healthcare: problems in getting money, distance, companionship, and permission to attend a health facility. Conversely, women who have conquered these barriers and attended antenatal care received nutrition education and counselling, which improved women's knowledge, perception and practices of dietary diversity in Malawi[41]. Therefore, we argue that eliminating pregnant women’s healthcare access barriers would improve their dietary diversity knowledge and practice.

The study has two main strengths. First, it used a nationally representative sample of pregnant women, increasing the generalizability of the findings. Second, it contributes to the growing scholarship and policy debates on food insecurity by exploring the social determinants of food insecurity in Nigeria. However, data availability within the NDHS limited the number of independent variables included in the study. Another limitation is that the study cannot establish a cause-and-effect relationship as the design was cross-sectional. The third limitation is that recall bias could have affected women's recall of the dietary practices. Furthermore, due to deteriorating law-and-order situations, the study did not collect data in eleven clusters. Finally, a qualitative study exploring the context of food-insecure pregnant women would be a great addition to the literature in future studies.

The purpose of this study, which is to determine the magnitude and determinants of food insecurity among pregnant women in Nigeria, is achieved. The proportion of food-insecure women needs to improve. While there is a need to address the fundamental causes of food insecurity in Nigeria, including cost, conflict, and weak implementation of food and nutrition policies, paying attention to the social determinants of food insecurity among pregnant women is equally imperative. The considerable regional variations and the influence of low education, marital status, non-exposure to television, and healthcare inaccessibility must be incorporated into policies and plans to improve food security among pregnant women in Nigeria.

AOR: Adjusted odd ratio; COR: Crude odd ratio; EAs: Enumeration areas; LGAs: Local government areas; MDD-W: Minimum dietary diversity for women of reproductive age; NDHS: Nigeria Demographic and Health Survey.

Ethics approval and consent to participate.

Since this study was a secondary analysis of the Nigeria Demographic and Health surveys (RDHS) data, which are publicly available, the study did not require any ethical approval. Only DHS program authorization was requested to download the dataset.

Consent for publication

Not applicable

Availability of data and material

The data used for this study are from the 2018 Nigeria Demographic and Health surveys (NDHS) and are publicly available here: https://dhsprogram.com/data/available-datasets.cfm Data was accessed by the researchers upon registration.

Competing interests

The authors report no conflict of interest.

Funding

The authors received no external funding for this study.

Authors' contributions

DCO conceptualized the study, conducted the literature review, abstracted and analysed the data, summarized the data, drafted the manuscript, critically reviewed and modified the intellectual content, and approved the final manuscript.

Acknowledgements

We thank the DHS Program for availing us access to the data.

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Table 1 Individual and household characteristics of pregnant women
Characteristics		Frequency (n)	Per cent (%)
Age	15-24	1495	35.3
	25-34	1990	47.0
	35-49	751	17.7
Region	North-Central	622	14.7
	North-East	800	18.9
	North-West	1660	39.2
	South-East	387	9.1
	South-South	316	7.4
	South-West	453	10.7
Place of residence	Urban	1515	35.8
Place of residence	Rural	2721	64.2
Highest educational level	No education	2052	48.4
	Primary	540	12.8
	Secondary	1319	31.1
	Higher	325	7.7
Religion	Christian	1442	34.1
	Islam	2769	65.4
	Traditionalist/Other	25	0.6
Family size	<5	1824	43.0
Family size	5 and above	2413	57.0
Sex of household head	Male	3925	92.7
Sex of household head	Female	311	7.3
Frequency of listening to radio	Not at all	2145	50.6
Frequency of listening to radio	Yes	2091	49.4
Frequency of watching television	Not at all	2538	59.9
Frequency of watching television	Yes	1698	40.1
Owns a mobile telephone	No	2161	51.0
Owns a mobile telephone	Yes	2075	49.0
Wealth index	Poor	1841	43.5
	Middle	896	21.2
	Rich	1499	35.4
Total children ever born	0	743	17.5
	1	725	17.1
	2-4	1727	40.8
	>4	1042	24.6
Respondent currently working	No	1670	39.4
Respondent currently working	Yes	2566	60.6
Gender attitude	Good	2835	66.9
Gender attitude	Poor	1401	33.1
Healthcare access barrier	No	1999	47.2
Healthcare access barrier	Yes	2237	52.8

Table 2 Prevalence of food insecurity among pregnant women in Nigeria, 2018
Characteristics		Food insecure		Food secure
Characteristics		n	% (95%C.I.)	n	% (95%C.I.)	X²	Sig.
Age	15-24	693	46.3(43.3-49.3)	803	53.7(50.7-56.7)	1.77	0.543
	25-34	886	44.5(41.6-47.5)	1104	55.5(52.5-58.4)
	35-49	328	43.6(39.6-47.7)	424	56.4(52.3-60.4)
Region	North-Central	341	54.8(50.2-59.4)	281	45.2(40.6-49.8)
	North-East	363	45.5(41.7-49.3)	436	54.5(50.7-58.3)	62.14	<0.001*
	North-West	766	46.1(42.7-49.6)	894	53.9(50.4-57.3)
	South-East	171	44.3(38.7-50.0)	216	55.7(50.0-61.3)
	South-South	121	38.5(32.1-45.3)	194	61.5(54.7-67.9)
	South-West	144	31.7(27.1-36.7)	309	68.3(63.3-72.9)
Place of residence	Urban	587	38.7(35.4-42.2)	928	61.3(57.8-64.6)	36.89	<0.001*
Place of residence	Rural	1319	48.5(46.2-50.8)	1402	51.5(49.2-53.8)
Highest educational level	No education	1042	50.8(47.9-53.7)	1010	49.2(46.3-52.1)
	Primary	266	49.3(44.5-54.0)	274	50.7(46.0-55.5)	92.09	<0.001*
	Secondary	507	38.4(35.3-41.6)	812	61.6(58.4-64.7)
	Higher	91	28.0(22.5-34.1)	234	72.0(65.9-77.5)
Religion	Christian	592	41.0(38.0-44.1)	851	59.0(55.9-62.0)
	Islam	1307	47.2(44.8-49.6)	1462	52.8(50.4-55.2)	16.85	0.003*
	Traditionalist/Other	7	29.8(13.2-54.3)	17	70.2(45.7-86.8)
Family size	<5	802	44.0(41.2-46.9)	1021	56.0(53.1-58.8)	1.28	0.362
Family size	5 and above	1104	45.8(43.3-48.3)	1309	54.2(51.7-56.7)
Sex of household head	Male	1782	45.4(43.4-47.4)	2143	54.6(52.6-56.6)	3.34	0.103
Sex of household head	Female	125	40.0(34.1-46.3)	187	60.0(53.7-65.9)
Frequency of listening to radio	Not at all	1063	49.6(47.0-52.2)	1082	50.4(47.8-53.0)	36.18	<0.001*
Frequency of listening to radio	Yes	843	40.3(37.7-43.0)	1248	59.7(57.0-62.3)
Frequency of watching television	Not at all	1301	51.3(48.9-53.6)	1237	48.7(46.4-51.1)	99.46	<0.001*
Frequency of watching television	Yes	605	35.6(32.7-38.6)	1093	64.4(61.4-67.3)
Owns a mobile telephone	No	1084	50.2(47.6-52.7)	1077	49.8(47.3-52.4)	47.28	<0.001*
Owns a mobile telephone	Yes	822	39.6(37.0-42.3)	1253	60.4(47.7-63.0)
wealth index	Poor	901	48.9(46.2-51.7)	940	51.1(48.3-53.8)
	Middle	413	46.1(41.8-50.4)	483	53.9(49.6-58.2)	29.64	<0.001*
	Rich	593	39.5(36.2-43.0)	906	60.5(57.0-63.8)
Total children ever born	0	299	40.2(35.8-44.9)	444	59.8(55.1-64.2)
	1	333	45.9(41.4-50.4)	393	54.1(49.6-58.6)	8.32	0.121
	2-4	790	45.7(43.0-48.4)	937	54.3(51.6-57.0)
	≥5	485	46.6(43.0-50.2)	556	53.4(49.8-57.0)
Current marital status	Never in union	34	37.6(27.0-49.6)	57	62.4(50.4-73.0)
	Married/living with partner	1867	45.4(43.5-47.3)	2248	54.6(52.7-46.5)	11.92	0.004*
	Widowed/Divorced/Separated	5	17.1(8.3-31.9)	26	82.9(68.1-91.7)
Respondent currently working	No	789	47.2(44.1-50.4)	881	52.8(49.6-55.9)	5.58	0.080
Respondent currently working	Yes	1117	43.5(41.0-46.1)	1449	56.5(53.9-59.0)
Gender attitude	Good	1270	44.8(42.4-47.2)	1565	55.2(52.8-57.6)	0.14	0.761
Gender attitude	Poor	636	45.4(42.3-48.5)	765	54.6(51.5-57.7)
Healthcare access barrier	No	729	36.4(33.8-39.2)	1270	63.6(60.8-66.2)	110.61	<0.001*
Healthcare access barrier	Yes	1178	52.6(50.1-55.1)	1060	47.4(44.9-49.9)
X²: Chi-square statistic; *Significant at p < 0.05

Table 3 Determinants of food insecurity among pregnant women in Nigeria, 2018
Factors		COR (95%CI)	Sig	AOR (95%CI)	Sig
	(Intercept)	0.05(0.01-0.20)	<0.001*	0.12(0.005-028)	<0.001
Region	North-Central	1.69(1.24-2.30)	0.001*	1.70(1.26-2.29)	0.001*
	North-East	0.82(0.59-1.15)	0.250	0.88(0.64-1.21)	0.421
	North-West	0.97(0.68-1.38)	0.857	1.03(0.75-1.43)	0.836
	South-East	1.58(1.10-2.27)	0.013*	1.47(1.04-2.07)	0.028*
	South-South	1.30(0.88-1.93)	0.184	1.22(0.84-1.77)	0.295
	South-West	1.00		1.00
Place of residence	Rural	1.02(0.81-1.28)	0.897
Place of residence	Urban	1.00
Highest educational level	No education	1.79(1.19-2.70)	0.005*	1.86(1.28-2.70)	0.001*
	Primary	1.81(1.23-2.67)	0.003*	1.86(1.28-2.69)	0.001*
	Secondary	1.34(0.96-1.87)	0.087	1.35(0.97-1.87)	0.072
	Higher	1.00		1.00
Current marital status	Married/ living with partner	3.29(1.26-8.54)	0.015*	3.33(1.28-8.67)	0.014*
	Widowed/Divorced/ Separated	3.78(1.66-8.63)	0.002*	3.83(1.68-8.73)	0.001*
	Never in union	1.00		1.00
Religion	Christian	2.24(0.74-6.73)	0.151
	Islam	2.64(0.87-8.03)	0.088
	Traditional/other	1.00
Frequency of listening to radio	Not at all	1.03(0.87-1.23)	0.721
Frequency of listening to radio	Yes	1.00
Frequency of watching television	Not at all	1.54(1.21-1.96)	<0.001*	1.55(1.26-1.92)	<0.001*
Frequency of watching television	Yes	1.00		1.00
Owns a mobile telephone	No	1.02(0.85-1.23)	0.798
Owns a mobile telephone	Yes	1.00
wealth index	Poor	0.97(0.77-1.22)	0.776
	Middle	1.02(0.81-1.30)	0.840
	Rich	1.00
Healthcare access	Yes	1.71(1.45-2.01)	<0.001*	1.69(1.43-1.99)	<0.001*
Healthcare access	No	1.00		1.00

COR: Crude odd ratio; AOR: Adjusted odd ratio; ^*Significant at p < 0.05

No competing interests reported.

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Magnitude and determinants of food insecurity among pregnant women in Nigeria: evidence from a nationwide cross-sectional survey

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