An assessment of Individual, community and state-level factors associated with inadequate iodised salt consumption among pregnant and lactating women in Nigeria

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Ameyaw, Efua Mensima, Oyelola A Adegboye, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2812946/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Iodine deficiency is the most common cause of thyroid disease, and in its severe form can result in cretinism; the impairment of the brain development of a child. Pregnant and breastfeeding women daily iodine requirement is elevated due to physiological changes in iodine metabolism, requiring up to double the iodine intake of other women. Despite the introduction of salt iodisation in many countries to control iodine deficiency disorders, adverse effects of inadequate iodine intake continue to be a problem. Methods This study utilised the Multiple Indicator Cluster Survey to assess factors associated with inadequate iodised salt consumption among pregnant women and breastfeeding mothers in Nigeria. The descriptive analysis was presented using frequencies and percentages. The prevalence of adequate and inadequate iodised salt consumption with their 95% confidence interval were computed. Several multi-level mixed effect log-binomial logistic regressions was used to explore the factors associated with inadequate iodised salt consumption. The Loglikelihood, Akaike Information Criterion and Bayesian Information Criterion were used to assess the goodness of fit of the models. All analyses were adjusted for the complex survey design and analysed using Stata 15.0 at p < 0.05. Results Our findings revealed that pregnant and breastfeeding women living in most deprived communities, with no formal education, poor wealth status, and those residing in the North West and South West region were more likely to consume salt with inadequate iodine. Conclusions There is a need to enhance women’s economic opportunities and empowerment as well as sensitisation on their nutritional requirements during pregnancy and breastfeeding. Epidemiology Salt Iodine-deficiency pregnant women breastfeeding mothers Cross-sectional survey Multi-level analysis Nigeria Figures Figure 1 Background Iodine is an essential element that directly affects thyroid gland secretions, which is necessary for fetal normal growth and development, and to a great extent, control heart action, nerve response to stimuli, and improve the motor and cognitive functions of a child ( 1 , 2 ). Worldwide, iodine deficiency is the most common cause of thyroid disease. In its severe form, particularly during gestation and in the first months following birth can result in cretinism; the impairment of the brain development of a child ( 3 ). Fortunately, iodine deficiency can be prevented by adequate dietary intake of iodine, which is most often achieved by adding iodine to salt ( 3 ). Salt is a compound composed primarily of sodium (Na) and chloride (Cl) and is of great importance to human and animal health ( 4 , 5 ). Sodium is an essential nutrient for human health via its role as an electrolyte and osmotic solute ( 5 ). Iodised salt, containing potassium iodide, is the most common source of natural forms of iodine, which is an essential micronutrient for normal human growth and development ( 6 , 7 ). World Health Organization (WHO) and the International Council for the Control of Iodine Deficiency Disorders (ICCIDD) had proposed salt iodisation strategy has a universal intervention to control and eliminate Iodine deficiency and advocated that adequately iodised salt must not only reach the entire affected population, but also those groups that are the most susceptible which are pregnant women, breastfeeding mothers and young children ( 3 ). Pregnant women daily iodine requirement is elevated due to physiological changes in iodine metabolism ( 8 , 9 ). The recommended daily iodine intake is 150 µg/L for adults, 220 µg/L for pregnant women, and 290 µg/L for lactating mothers ( 3 ). Adequate dietary intake of Iodine is critical for brain development, and iodine deficiency is the single most important preventable cause of brain damage and irreversible mental retardation ( 3 , 7 , 10 , 11 ). Despite the introduction of salt iodisation in many countries to control iodine deficiency, adverse effects of inadequate intake continue to be a problem, with an estimated 1.9 billion people at risk worldwide ( 12 ). In Turkey, a study revealed that iodine deficiency still remains a serious problem among pregnant women after eight years of compulsory salt iodination in the country ( 13 ). The majority of people using non-iodised salt in most Sub-Saharan African (SSA) countries is among poor, younger women and those who were pregnant ( 14 ). Also, there exist geographical variations among countries. For example, the proportion of people with no iodised salt ranges from 29.5% in Senegal, 21.3% in Tanzania, 14% in Ethiopia, 11.6% in Malawi and 10.8% in Angola ( 14 ). In addition, an assessment of iodine status among pregnant women in a rural community in Ghana revealed a prevalence of 42.5% iodine deficiency ( 15 ). Although, Nigeria was the first African country to be declared iodine sufficient in 2007, a recent national survey has shown that only about seven in ten households consume salt with adequate iodine content (≥ 15 ppm) with variation across states ( 16 ). Some studies conducted at community and state levels have shown striking differences in iodine deficiency among women. For example, a study in Zaria, Northwestern Nigeria, revealed iodine sufficiency among pregnant women ( 17 ), while another study showed that residents of Nanka and Oba towns of Anambra State, Southeastern Nigeria, were at risk of iodine deficiency disorders ( 18 ). Therefore, this study utilised national representative data to assess individual- and household-, community- and state-level factors associated with inadequate iodised salt consumption among pregnant women and breastfeeding mothers in Nigeria. Materials And Methods Data sources The Nigeria Multiple Indicator Cluster Survey (MICS) conducted between September 2016 to January 2017 was utilised for this study. The 2016-17 Nigeria MICS was designed to provide national, regional and state-level estimates and considered urban and rural differences. This cross-sectional survey is aimed at developing evidence-based policies and programmes and for monitoring progress toward national goals and global commitments. A two-stage sampling procedure was adopted using the National Integrated Survey of Households round 2 (NISH2) extracted from the 2006 Population Census as sampling frame and the basis for selecting Enumeration Areas (EAs). The Primary Sampling Units (PSUs) consisted of EAs selected in each state, while households within each EAs were selected at the second stage. The states within each of the six geo-political regions were used as the sampling strata. The MICS 2016-17 used four types of questionnaire, namely household, women, men, and under-five children questionnaire to elicit information on demographic, household, women, men and children health indicators. Information on the availability of salt for cooking and also testing for its iodine content was included in the household questionnaire. Further details on sampling technique, data collection and administration are provided in the report ( 16 ). Outcome Variable In this study, we extracted information on the iodine content in salt among women who were pregnant or currently breastfeeding. The amount of iodine in salt samples were categorised into three, namely: ( 1 ) salt in the household do not contain iodine ( 2 ) more than 0 parts per million (ppm) and less than 15 ppm ( 3 ) 15 ppm or more. To investigate factors associated with salt consumption with inadequate iodine content; respondents who consumed salt containing 15 ppm iodine or more were considered as having adequate iodine intake, while those who consumed salt with no iodine or less than 15 ppm were deemed deficient in iodine. Explanatory Variables The explanatory variables were grouped into individual- and household-, community, and state-level characteristics. Individual factors considered were respondent age group (15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49 years), educational status (none, primary, secondary/technical, higher and non-formal), exposure to mass media (measured using access to radio and/or television), number of children ever born (0, 1–2, 3–4, 5 or more), currently working (no vs yes). The household characteristics included, sex of household head (male vs female), the religion of household head (Christianity, Islam and others), ethnicity of household head (Hausa, Igbo, Yoruba and other ethnic groups) and the household wealth quintiles (poorest, poorer, middle, richer and richest). Community-level characteristics were explored using two variables, place of residence (urban vs rural) and community socio-economic status. Community refers to people living in the same locality (EAs). Community socio-economic deprivation was computed using a principal component analysis (PCA) comprising of wealth status (asset index in the poorest and poorer quintiles), unemployed, no formal education and illiteracy - those who cannot read at all. The standardised score was then categorised into tertiles (1 – least deprived communities to 3 – most deprived communities). Similarly, for the state-level characteristics, we extracted state socio-economic deprivation status using PCA and grouped into tertiles (1 – least deprived states to 3 – most deprived states) and also included regions (North Central, North East, North West, South East, South-South and South-West). (see supplementary table 1). Data Analysis The descriptive analysis was presented using frequencies and percentages as well as the prevalence and 95% confidence interval (CI) of adequate and inadequate salt consumption. The prevalence was computed as the proportion of breastfeeding or pregnant women with adequate and inadequate iodine content in salt by women’s background characteristics. Similarly, the test of homogeneity of the proportion of inadequate iodised salt intake across the categories of each individual/household-, community and state characteristics were reported based on the corrected Pearson χ2 statistic. To account for the complex survey design, the Pearson χ2 statistic is transformed into an F-statistic with non-integer degrees of freedom using a second-order Rao and Scott correction ( 19 , 20 ). Then, five multi-level mixed effect log-binomial logistic regression models were fitted to the data in order of complexity. First, a null model (Model 1, with no explanatory variables) was fitted to the data to explore the variation due to community and state effects only. The second model (Model 2) included individual and household variables, while the third model (Model 3) had only community characteristics. In the fourth model (Model 4), we examined only the state-level variables. The full model (Model 5) considered all individual, community and state-level variables. The Loglikelihood, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to assess the goodness of fits of the models. A lower value of the model statistic is said to be a better fit. More succinctly, if the difference between two information criteria (IC) value is greater than 10, this implies that the model with a smaller IC is superior while a difference of 4 to 10 suggest a moderate superiority and a difference less than 4 implies that the two models are indistinguishable ( 21 , 22 ). All analyses were adjusted for the complex survey design and analysed using Stata 15.0 (StataCorp LLC, College Station, Texas, USA). Statistical Inferences were based on a 5% level of significance. Ethical Consideration This study was based on an analysis of a publicly available secondary dataset–the Multiple Indicator Cluster Survey; thus, no additional ethical clearance is required. Before conducting the survey, ethical clearance was obtained from the National Health Research Committee, and informed consent was taken from each participant before conducting the interview. Information on privacy, confidentiality and the right of respondents to withdraw from the study at any time were clearly stated ( 16 ). Results Descriptive statistics Data from a total of 4911 pregnant and breastfeeding women were eligible for the study. One in ten women were adolescents, and 56.7% had no or non-formal education (Table 1 ). Almost one in ten (10.8%) reported never having any childbirth, only 20.7% of the women were currently working, and 46.6% had no access to television or radio. About half of the household heads had no or non-formal education, were males (92.8%), are majorly Muslims (71.9%), and from the Hausa ethnic group (60%). Wealth was evenly distributed among each category of the quintiles in the study population. For the community characteristics, 76.4% of the respondents resided in rural areas, and one-third were least deprived. The majority (seven in ten) of the respondents were from the Northern states, particularly, North-western region (44.4%), whereas 34.8% of respondents are living in the least deprived state compared to 31.3% of the respondents who are living in the poorest states. Table 1 Descriptive summaries of respondents’ background characteristics. Variables Frequency (%) Individual and Household characteristics Age group 15–19 502 (10.2%) 20–24 1053 (21.4%) 25–29 1273 (25.94%) 30–34 967 (19.7%) 35–39 653 (13.3%) 40–44 312 (6.3%) 45–49 151 (3.1%) Level of Education None 1579 (32.2%) Primary 684 (13.9%) Secondary/technical 1140 (23.2%) Higher 307 (6.3%) Non-formal 1200 (24.4%) Exposure to mass media No 2287 (46.6%) Yes (TV/radio) 2624 (53.4%) Children ever born None 531 (10.8%) 1–2 1621 (33.0%) 3–4 1271 (25.9%) 5 or more 1489 (30.3%) Currently working Yes 1016 (20.7%) No 3895 (79.3%) Sex of household head Male 4556 (92.8%) Female 355 (7.2%) Religion of household head Christianity 1341 (27.3%) Islam 3530 (71.9%) Others 40 (0.8%) Ethnicity of household head Hausa 2967 (60.4%) Igbo 275 (5.6%) Yoruba 455 (9.3%) Other ethnic groups 1214 (24.7%) Education of household head None 1217 (24.8%) Primary 769 (15.7%) Secondary/technical 1007 (20.5%) Higher 605 (12.3%) Non-formal 1314 (26.8%) Wealth status Poorest 968 (19.7%) Poorer 975 (19.8%) Middle 984 (20.0%) Richer 993 (20.2%) Richest 992 (20.2%) Community characteristics Place of residence Urban 1159 (23.6%) Rural 3752 (76.4%) Socio-economic status 1 (Least deprived) 1651 (33.6%) 2 (More deprived) 1627 (33.1%) 3 (Most deprived) 1633 (33.3%) State and regional characteristics Socio-economic status 1 (Least deprived) 1707 (34.8%) 2 (More deprived) 1667 (33.9%) 3 (Most deprived) 1536 (31.3%) Region North Central 840 (17.1%) North East 932 (19.0%) North West 2179 (44.4%) South East 175 (5.6%) South South 337 (6.9%) South West 448 (9.1%) Total 4911 (100%) Prevalence Of Adequate And Inadequate Iodine Content In Salt The prevalence of inadequate iodised salt consumption among pregnant and breastfeeding mothers was 35.2% (95% CI: 33.1–37.5), as shown in Table 2 . Inadequate consumption of iodised salt was highest among pregnant and breastfeeding women aged 45–49 years (48.2%; 95%CI: 37.8–58.8), as well as those with non-formal education (52.7%; 95%CI: 47.7–57.6) and no education (34.6%; 95%CI: 31.3–38.1). Respondents who were exposed to mass media (30.0%), currently working (22.9%), and female headed-household (26.8%) had a lower prevalence of consuming salt with inadequate iodine compared to those with no access to mass media (41.2%), not working (38.4%) and male-headed household (35.9%), respectively. Wealth status was associated with intake of salt deficient in iodine; for example, 46.8% (95% CI: 42.1–51.5) of those in the poorest wealth quintile consume salt with inadequate iodine, while only 21.5% (95% CI: 17.6–25.9) among those in the richest quintile. Similarly, iodised salt intake was associated with community socio-economic deprivation and state socio-economic deprivation. For example, respondents in communities that are least deprived (23.0% vs 41.9%) and those in the least deprived states (22.6% vs 46.0%) had a lower prevalence of inadequate iodised salt intake compared to the respondent in the most deprived communities and states. Also, inadequate iodised salt intake was higher among respondents who reside in the rural (37.0% vs 29.3%) compared to urban areas and among those who are Hausas (p = 43.1%; 95%CI: 39.9–46.3) compared to all other ethnic groups. Almost one in ten pregnant or breastfeeding women in the North West consume salt with inadequate iodine. The corrected Pearson χ2 statistic also suggest that the proportion of inadequate iodised salt consumption differs across the categories of each background characteristics considered (p < 0.05 for all variables). Furthermore, the geographic distribution of inadequate iodised salt consumption among pregnant and breastfeeding mothers by states is shown in Fig. 1 . the spatial map revealed the high burden of inadequate iodised salt intake in the Northwestern region; particularly with the highest burden in Zamfara (70.4%), Kebbi (67.1%) and Ekiti state (64.8%) in the Southwestern region. Table 2 Prevalence of Iodised salt intake by women’s individual/household, community and state-level characteristics Variables Prevalence (95% CI) Prevalence (95% CI) F-statistic † p-value Adequate Iodized Salt Inadequate Iodized Salt Overall 64.8(62.5–67.0) 35.2(33.1–37.5) Individual and Household characteristics Age group p < 0.001 15–19 54.4(48.3–60.5) 45.6(39.5–51.7) 20–24 68.1(63.7–72.1) 31.9(27.9–36.3) 25–29 66.7(63.3–70.0) 33.3(30.0-36.7) 30–34 68.3(64.4–72.1) 31.7(27.9–35.6) 35–39 63.5(58.9–68.0) 36.5(32.0-41.2) 40–44 60.1(52.7–67.0) 39.9(33.0-47.3) 45–49 51.8(41.2–62.2) 48.2(37.8–58.8) Level of Education p < 0.001 No education 65.4(61.9–68.7) 34.6(31.3–38.1) Primary 68.3(63.3–72.9) 31.7(27.1–36.7) Secondary/technical 75.3(71.6–78.8) 24.7(21.2–28.4) Higher 82.8(75.5–88.2) 17.2(11.8–24.5) Non-formal 47.3(42.4–52.3) 52.7(47.7–57.6) Exposure to mass media p < 0.001 No 58.8(55.6–62.0) 41.2(38.1–44.4) Yes (TV/radio) 70.0(67.1–72.6) 30.0(27.4–32.9) Parity p = 0.010 0 (None) 68.5(62.9–73.5) 31.5(26.5–37.1) 1–2 67.1(63.9–70.2) 32.9(29.8–36.1) 3–4 65.3(61.4–69.0) 34.7(31.0-38.7) 5 or more 60.5(57.0-63.9) 39.5(36.1–43.0) Currently working p < 0.001 Yes 77.1(73.7–80.1) 22.9(19.9–26.3) No 61.6(60.0-64.1) 38.4(35.9–41.0) Sex of household head p = 0.005 Male 64.1(61.8–66.4) 35.9(33.6–38.2) Female 73.3(67.2–78.6) 26.8(21.4–32.8) Religion of household head p < 0.001 Christianity 76.8(73.7–79.5) 23.2(20.5–26.3) Islam 60.1(57.2–62.9) 39.9(37.1–42.8) Others 76.1(61.6–86.3) 24.0(13.7–38.4) Ethnicity of household head p < 0.001 Hausa 56.9(53.7–60.1) 43.1(39.9–46.3) Igbo 85.4(80.5–89.2) 14.6(10.8–19.5) Yoruba 74.4(69.0-79.2) 25.6(20.8–31.0) Other ethnic groups 75.7(71.8–79.2) 24.3(20.8–28.2) Education of household head p < 0.001 None 71.3(67.7–74.7) 28.7(25.3–32.3) Primary 67.5(62.1–72.5) 32.5(27.5–37.9) Secondary/technical 70.7(66.7–74.4) 29.3(25.6–33.3) Higher 71.8(65.4–77.5) 28.2(22.5–34.6) Non-formal 49.3(44.6–54.2) 50.7(45.9–55.5)) Wealth status p < 0.001 Poorest 53.2(48.5–57.9) 46.8(42.1–51.5) Poorer 58.9(54.2–63.5) 41.1(36.5–45.8) Middle 64.1(58.6–69.2) 36.0(30.8–41.4) Richer 68.7(63.9–73.2) 31.3(26.8–36.1) Richest 78.5(74.1–82.4) 21.5(17.6–25.9) Community characteristics Place of residence p = 0.003 Urban 70.7(66.4–74.6) 29.3(25.4–33.6) Rural 63.0(60.3–65.5) 37.0(34.5–39.7) Socio-economic status p < 0.001 1 (Least deprived) 77.0(73.5–80.2) 23.0(19.8–26.5) 2 (More deprived) 59.1(54.8–63.2) 40.9(36.8–45.2) 3 (Most deprived) 58.1(54.0-62.1) 41.9(37.9–46.0) State and regional characteristics Socio-economic status p < 0.001 1 (Least deprived) 77.4(74.4–80.1) 22.6(19.9–25.6) 2 (More deprived) 61.8(57.7–65.8) 38.2(34.2–42.3) 3 (Most deprived) 54.0(49.6–58.3) 46.0(41.8–50.4) Region p < 0.001 North Central 82.8(78.6–86.2) 17.3(13.8–21.4) North East 69.8(64.0–75.0) 30.2(25.0–36.0) North West 49.6(46.3–53.0) 50.4(47.0-53.8) South East 86.5(81.4–90.4) 13.5(9.6–18.6) South South 82.6(77.6–86.7) 17.4(13.3–22.4) South West 72.4(66.9–77.3) 27.6(22.7–33.1) † Corrected Pearson χ2 statistic accounting for the complex survey design Muti-level Mixed Effect Log-binomial Regression Model We fitted five multi-level mixed effect log-binomial regression models to our data. The null model (Model 1) showed a high intracluster correlation (ICC) of 45.3% (95%CI 40.3–50.3), an indication of greater dependency between levels. Similar results were obtained for models 2–5, suggesting the appropriateness of a multi-level approach. After adjusting for individual and household characteristics in Model 2, we found a direct negative significant association between increasing wealth status and inadequate iodised salt intake. Respondents in the poorer, middle, richer and richest quintiles were 32%, 47%, 35% and 62% less likely to consume salt with inadequate iodine compared to those in the poorest households. Also, pregnant and breastfeeding mothers who were Igbos (aRR 0.29; 95%CI 0.16–0.54) and other ethnic groups (aRR 0.49; 95%CI 0.35–0.70) were less likely to consume salt with inadequate iodine compared to Hausas. However, respondents with no formal education were 1.8 times (95%CI: 1.36–2.42) more likely to consume salt with deficient iodine compared to those with no education, and households whose head had a secondary, higher, and non-formal education were 50%, 59% and 94% more likely to consume salt with inadequate iodine compared to those with no education. In Model 3, we adjusted for the community socio-economic status. Pregnant and breastfeeding mothers residing in moderately and most deprived communities were 3.5 (95%CI: 2.57–4.73) and 4.7 times (95%CI: 3.38–6.55) more likely to consume salt with inadequate iodine than those from least deprived communities. Similarly, Model 4 showed that those residing in moderately and most deprived states were 1.9 (95%CI: 1.14-3.00) and 2.6 (95%CI: 1.50–4.44) times more likely to consume salt with inadequate iodine than those from least deprived states. Also, respondents from the North West and those from South West were 5.1 (95%CI: 3.18–8.30) and 2.9 (95%CI: 1.77–4.59) times more likely to consume salt with inadequate iodine compared to those from the North-Central region. In the fully adjusted model (Model 5), including individual/household, community and state-level characteristics. Our analysis showed that respondents with no-formal education were 1.7 (95%CI: 1.25–2.31) times more likely to consume inadequately iodised salt compared to those with no education. Similarly, household heads with no formal education (aRR 1.71; 95%CI: 1.16–2.52) and secondary education (aRR 1.44; 95%CI: 1.02–2.04) were associated with inadequate iodised salt intake compared to those with no education. Respondents in the middle (aRR 0.64; 95%CI: 0.42–0.97) and richest (aRR 0.51; 95%CI: 0.26–0.99) wealth quintiles were less likely to consume inadequately iodised salt compared to those in the poorest quintile. Also, respondents in the most deprived communities were 96% more likely to consume salt with inadequate iodine than those in the least deprived communities. Women in the Northwestern region and those from the Southwestern region were 4.0 and 3.5 times, respectively, more likely to consume salt with inadequate iodine compared to pregnant and breastfeeding women residing in the North-Central region. Results from the model fit revealed that model 5 has the best fit based on loglikelihood (-2721.61) and AIC (5525.22) while the BIC showed that both model 1 and Model 5 are indistinguishable (BIC: 5792.44 vs 5791.69) (Table 3 ). Table 3. Factors associated with inadequate iodised salt intake among pregnant and breastfeeding mothers from multi-level logistic regression Variables Null Model 1 a Model 2 b Model 3 c Model 4 d Model 5 e RR(95% CI) aRR(95% CI) aRR(95% CI) aRR(95% CI) aRR(95% CI) Individual and Household characteristics Age group 15-19 Reference Reference 20-24 0.84(0.56-1.28) 0.91(0.60-1.38) 25-29 0.92(0.61-1.39) 1.01(0.67-1.53) 30-34 0.77(0.49-1.22) 0.87(0.54-1.38) 35-39 0.89(0.55-1.44) 0.98(0.60-1.60) 40-44 1.24(0.71-2.15) 1.38(0.78-2.44) 45-49 1.37(0.71-2.63) 1.46(0.76-2.80) Level of Education None Reference Reference Primary 1.01(0.73-1.65) 1.30(0.84-2.03) Secondary/technical 1.02(0.65-1.60) 1.26(0.72-2.20) Higher 0.61(0.32-1.14) 0.78(0.38-1.59) Non-formal 1.81(1.36-2.42) 1.70(1.25-2.31) Exposure to mass media No Reference Reference Yes (TV/radio) 0.86(0.68-1.07) 0.87(0.69-1.09) Parity 0 (None) Reference Reference 1-2 0.97(0.68-1.37) 0.94(0.66-1.09) 3-4 1.03(0.69-1.55) 0.96(0.64-1.45) 5 or more 1.01(0.65-1.56) 0.90(0.57-1.40) Currently working No Reference Reference Yes 0.83(0.63-1.09) 0.99(0.74-1.34) Sex of household head Male Reference Reference female 1.27(0.86-1.89) 1.30(0.88-1.94) Religion of household head Christianity Reference Reference Islam 1.07(0.76-1.52) 0.87(0.60-1.25) Others 0.71(0.31-1.65) 0.70(0.29-1.68) Ethnicity of household head Hausa Reference Reference Igbo 0.29(0.16-0.54) 0.42(0.18-1.01) Yoruba 0.93(0.58-1.50) 0.99(0.51-1.92) Other ethnic group 0.49(0.35-0.70) 0.86(0.58-1.28) Education of Household head None Reference Reference Primary 1.30(0.90-1.89) 1.24(0.85-1.82) Secondary/technical 1.50(1.07-2.11) 1.44(1.02-2.04) Higher 1.59(1.01-2.50) 1.45(0.91-2.32) Non-formal 1.94(1.33-2.83) 1.71(1.16-2.52) Wealth status Poorest Reference Reference Poorer 0.68(0.48-0.97) 0.75(0.53-1.06) Middle 0.53(0.36-0.80) 0.64(0.42-0.97) Richer 0.65(0.43-0.98) 0.86(0.54-1.38) Richest 0.38(0.22-0.67) 0.51(0.26-0.99) Community characteristics Place of residence Urban Reference Reference Rural 0.79(0.57-1.08) 0.85(0.58-1.23) Socio-economic status 1 (Least deprived) Reference Reference 2 (More deprived) 3.49(2.57-4.73) 1.56(0.95-2.54) 3 (Most deprived) 4.71(3.38-6.55) 1.96(1.04-3.72) State and regional characteristics Socio-economic status 1 (Least deprived) Reference Reference 2 (More deprived) 1.85(1.14-3.00) 1.27(0.75-2.17) 3 (Most deprived) 2.58(1.50-4.44) 1.65(0.90-3.01) Region North Central Reference Reference North East 1.29(0.71-2.35) 1.41(0.75-2.65) North West 5.14(3.18-8.30) 4.01(2.27-7.08) South East 0.88(0.50-1.56) 2.02(0.77-5.33) South South 1.23(0.74-2.03) 1.57(0.89-2.76) South West 2.85(1.77-4.59) 3.46(1.79-6.68) Random effect ICC 45.3(40.3-50.3) 38.7(33.4-44.3) 43.2(38.1-48.4) 37.9(32.8-43.4) 37.5(32.2-43.1) Model fit statistic Loglikelihood -2906.564 -2764.482 -2851.675 -2778.321 -2721.608 AIC 5817.127 5590.964 5713.350 5574.642 5525.216 BIC 5830.126 5792.441 5745.846 5633.135 5791.685 RR relative risk, aRR adjusted relative risk, CI confidence interval, ICC intracluster correlation The aRR in bold implies significance at 5% a Null ModeI 1 – baseline model without any explanatory variables (unconditional model) b Model 2 – adjusted for only individual and household-level factors c Model 3 – adjusted for only community-level factors d Model 4 – adjusted for only state-level factors e Model 5 – adjusted for individual and household-, community-, and country-level factors (full model) Discussion Iodine deficiency is a global public health threat, especially for pregnant, lactating women and children under two years old. The focus of this retrospective cross-sectional study was to investigate factors associated with inadequate iodised salt consumption among pregnant and lactating women in Nigeria. This study was expedient in light of the limited empirical literature on iodised salt consumption in Nigeria. The overall prevalence of inadequate iodised salt consumption among pregnant and lactating women in this study was 35.2%. The multi-level mixed-effect logistic model showed that pregnant and lactating women with non-formal education were more likely to consume inadequately iodised salt compared to those with formal education after adjusting for other multivariable factors. We found households with uneducated heads to be associated with increased risks of inadequate iodised salt consumption. This is likely due to nutritional education which are sometimes received by those with formal education as part of their usual lessons. In addition to formal education, non-formal education could be a promising platform for routing nutrition and its related educational and advocacy interventions. The importance of education to the consumption of iodised salt has been reported in studies from other sub-Saharan African countries such as Ethiopia (Tariku & Mazengia, 2019) and Ghana (Buxton & Baguune, 2012). Non-formal education in Nigeria targets children, youths and adults who either have dropped out of school or have never been to school (Adewale 2009). Our findings are similar to those reported by Udofia, Yawson, Aduful et al. 2014; Narayan 2000 and Gweshengwe & Hassan, 2020, that women living in the most deprived communities were more likely to consume salt with inadequate iodine compared to those who reside in the least deprived communities. Residents of deprived communities are likely to be less endowed economically and may have little negotiation and purchasing power (Narayan 2000). Without a strong negotiation and purchasing power, one can easily be persuaded to improvise with whatever they come across, even if they are fully aware of the adverse effects associated with that action (French, Tangney, Crane et al. 2019). Pregnant and breastfeeding women who belong to the top household wealth quintiles were less likely to consume inadequate iodised salt compared to those in the poorest category. Wealth or richness is associated with good nutrition and good health status, as empirical research suggests (Hong & Mishra, 2006; Angeles-Agdeppa, Lenighan, Jacquier et al, 2019). Wealthy persons usually tend to live in clean, hygienic and well-planned settlements, access quality healthcare and have frequent check-ups (Armah, Ekumah, Yawson et al, 2018). The indigent, however, is usually concerned with how to put food on the table and cater for the necessities of life as purported by Maslow’s Hierarchy of Needs (Maslow & Lewis, 1987). These substantial variations may account for the findings in this study. Enhancing women’s economic opportunities by training them in various skills can increase their employability prospects and thereby make them economically sound to enable them to take the right nutrition, including iodised salt. This study also revealed that those in Northwestern and Southwestern regions were more likely to consume salt with inadequate iodine compared to pregnant and breastfeeding women in the North- Central region. This suggests inequality in the distribution of iodised salt within Nigeria or disparity in the consumption pattern of iodised salt. Context appropriate education on iodised salt utilisation would be recommended in those regions with relatively low consumption of iodised salt. These educational campaigns can be channelled through widely accessed media channels such as radio or television. Strengths And Limitations Of The Study Unlike previous studies on salt iodisation ( 18 , 23 , 24 ) this study focused on two key populations, pregnant and lactating women. It also followed rigorous and appropriate analytical procedures, thereby generating robust and reliable findings. The findings are also generalisable to all pregnant and lactating women in Nigeria, and its lessons/recommendations are useful for other sub-Saharan African countries. One of the major limitations of this paper is the cross-sectional nature of the study design, which do not allow for causal inference of the associated factors. WHO recommendation is not to have too much iodine in salt but a concentration of between 15 to 40 ppm of iodine. However, the classification of iodine content in salt samples in the MICS dataset into three main categories – 0 ppm, < 15 ppm and ≥ 15ppm limit our investigation to examine the range of iodine content in salt at the household level. More so, the urinary iodine concentration test was not collected; this would have provided additional insight into the iodine status of pregnant and breastfeeding mothers. Conclusion The study revealed the prevalence of pregnant and lactating women in Nigeria with inadequate iodised salt consumption as well as other associated factors. Findings are suggestive that measures to overcome inadequate iodised salt consumption include ensuring equitable distribution of essential food commodities among the more and most deprived communities. Besides, there is the need to enhance women’s economic opportunities by training them in various skills that can increase their employability prospects and thereby making them economically sound to enable them to take proper nutrition, including iodised salt. Both formal and non-formal educational initiatives on nutrition are extremely important and should be prioritised by the Nigerian government in its efforts to ensure adequate consumption of iodised salt among pregnant and lactating mothers. Abbreviations WHO - World Health Organization (WHO) ICCIDD - International Council for the Control of Iodine Deficiency Disorders MICS - Multiple Indicator Cluster Survey AIC - Akaike Information Criterion BIC - Bayesian Information Criterion ppm – part per million NISH2 - National Integrated Survey of Households round 2 EA – Enumeration Areas PSU – Primary Sampling Unit PCA - Principal Component Analysis CI – Confidence Interval aRR – adjusted relative risk Declarations Ethics approval and consent to participate: Ethics approval was not required for this study since the data is secondary and is available in the public domain. More details regarding DHS data and ethical standards are available at: http://goo.gl/ny8T6X. All methods were performed in accordance with the relevant guidelines and regulations (e.g., Declaration of Helsinki). Acknowledgements : The authors thank the MEASURE DHS project for their support and for free access to the original data. Conflict of interest: The authors declare that they have no conflicts of interest. Funding: The authors received no funding for this study. Data availability statement: Data for this study were sourced from the Multiple Indicator Cluster Surveys and available here: https://mics.unicef.org/surveys Authors Contributions: YOK conceptualized, designed, analyzed, and wrote the methodology as well as the results sections of the manuscript. EKA contributed to the analysis and the discussion of the manuscript. EM, contributed to the introductory section of the manuscript. OAA and YS contributed to the interpretation and revision of the manuscript. YS had final responsibility to submit. All authors read, agreed, and approved the final manuscript. Acknowledgments: The authors acknowledge the Multiple Indicator Cluster Survey for granting permission and access to the data used for this study. References Chung HR, 2014. Iodine and thyroid function. Annals of pediatric endocrinology & metabolism, 19(1), p.8. 2014. Skeaff SA. Iodine deficiency in pregnancy: the effect on neurodevelopment in the child. Nutrients 2011;3(2):265-273 doi:103390/nu3020265. 2011. WHO. Assessment of iodine deficiency disorders and monitoring their elimination : a guide for programme managers, 3rd ed. World Health Organization. https://apps.who.int/iris/handle/10665/43781. 2007. Wood FO, Ralston RH, Hills JM. Salt. Encyclopedia Britannica. https://www.britannica.com/science/salt. 2021. Nissen SE. US dietary guidelines: an evidence-free zone. 2016. Thomson CD, Skeaff SA. Iodine status and deficiency disorders in New Zealand. Preedy VR, Burrow GN and Watson RR Comprehensive Handbook of Iodine-Nutritional, Biochemical Pathological and Therapeutic aspects, 1252. 2009. Kapil U. Health consequences of iodine deficiency. Sultan Qaboos University medical journal. 2007;7(3):267-72. Glinoer D. The importance of iodine nutrition during pregnancy. Public Health Nutr 2007;10:1542–6. 2007. Mao G, Zhu W, Mo Z, Wang Y, Wang X, Lou X, et al. Iodine deficiency in pregnant women after the adoption of the new provincial standard for salt iodization in Zhejiang Province, China. . BMC pregnancy and childbirth, 18(1), 1-7. 2018. Zimmermann MB, Boelaert K. Iodine deficiency and thyroid disorders. . The lancet Diabetes & endocrinology, 3(4), 286-295. 2015. Zimmermann MB, Gizak M, Abbott K, Andersson M, Lazarus JH. Iodine deficiency in pregnant women in Europe. . The lancet Diabetes & endocrinology, 3(9), 672-674. 2015. Zimmermann MB, Andersson M. Update on iodine status worldwide. Current Opinion in Endocrinology, Diabetes and Obesity, 19(5), 382-387. 2012. Kut A, Gursoy A, Şenbayram S, Bayraktar N, Budakoğlu Iİ, Akgün HS. Iodine intake is still inadequate among pregnant women eight years after mandatory iodination of salt in Turkey. . Journal of endocrinological investigation, 33(7), 461-464. 2010. Ba D, Ssentongo P, Liao D, Du P, Kjerulff K. Non-iodised salt consumption among women of reproductive age in sub-Saharan Africa: A population-based study. . Public Health Nutrition, 23(15), 2759-2769 doi:101017/S1368980019003616. 2020. Simpong DL, Adu P, Bashiru R, Morna MT, Yeboah FA, Akakpo K, et al. Assessment of iodine status among pregnant women in a rural community in ghana-a cross sectional study. . Archives of Public Health, 74(1), 1-5. 2016. MICS. National Bureau of Statistics (NBS) and United Nations Children’s Fund (UNICEF). 2017 Multiple Indicator Cluster Survey 2016-17, Survey Findings Report. Abuja, Nigeria: National Bureau of Statistics and United Nations Children’s Fund. 2017. Jibril MEB, Abbiyesuku FM, Aliyu IS, Randawa AJ, Adamu R, Akuyam SA, et al. Nutritional iodine status of pregnant women in Zaria, North-Western Nigeria. Sub-Saharan African Journal of Medicine, 3(1), 41. 2016. Olife IC, Anajekwu, B. A., & Onuogbu, A. K. . Assessment of iodine status of some selected populations in Anambra state, Nigeria. BCAIJ, 7(3), 2013 [97-101]. 2013. Rao JNK, Scott AJ. The analysis of categorical data from complex sample surveys: Chi-squared tests for goodness of fit and independence in two-way tables. Journal of the American Statistical Association 1981;76:221-30. Rao JNK, Scott AJ. On chi-squared tests for multiway contingency tables with cell proportions estimated from survey data. Annals of Statistics. 1984;12:46-60. Kareem YO, Morhason-Bello IO, Adebowale AS, Akinyemi JO, Yusuf OB. Robustness of zero-augmented models over generalized linear models in analysing fertility data in Nigeria. BMC Research Notes. 2019;12(1):815. Pan W. Akaike’s information criterion in generalized estimating equations. Biometrics 2001;57(1):120–5. 2001. Ugo J, & Chinwe, E. . A pilot study of iodine and anthropometric status of primary school children in Obukpa, a rural Nigerian community. Journal of public Health and Epidemiology, 4(9), 246-252. 2012. Umenwanne EO, & Akinyele, I. O. Inadequate salt iodization and poor knowledge, attitudes, and practices regarding iodine-deficiency disorders in an area of endemic goitre in south-eastern Nigeria. Food and Nutrition Bulletin, 21(3), 311-315. 2000. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2812946","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":191593447,"identity":"1b9f78d0-f03a-42b1-971a-d0754de6ffb1","order_by":0,"name":"Yusuf Olushola Kareem","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYFACxsYDHw5AWA+ABA8fEVoaDs6AaGE2AGlhI8aewzwQLWwSYJKQct32ww0HeM7Y5RvcSH9W+TXHToaNgfnhoxt4tJidSWw4IHEj2XLDjRyz27LbkoEOYzM2zsGn5QBQi8EHZgODGzlstyW3MQO18LBJ49Vy/mHDgYQP9QYghxVLbqsnQssNoC0HbhwGakkwY/y47TAxWh42HGw4c9xA8swbY2nGbcd52JgJ+eV8+sPHf45VG/AdT3/48ee2ant+9uaHj/FpgQOFA8C45AGxmIlRDgLyDcCE8INY1aNgFIyCUTCiAACX+FMxf1pGgQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-9076-2129","institution":"UNFPA","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yusuf","middleName":"Olushola","lastName":"Kareem","suffix":""},{"id":191593448,"identity":"52959d33-489a-435f-9296-780257063035","order_by":1,"name":"Edward K. Ameyaw","email":"","orcid":"","institution":"aculty of Health, University of Technology Sydney, NSW, Australia","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Edward","middleName":"K.","lastName":"Ameyaw","suffix":""},{"id":191593449,"identity":"bc841a9a-a45f-439a-9e3a-4799eb078469","order_by":2,"name":"Efua Mensima","email":"","orcid":"","institution":"Maternal and Child Health Unit, Directorate of University Health Services, University for Development Studies, Tamale Ghana","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Efua","middleName":"","lastName":"Mensima","suffix":""},{"id":191593450,"identity":"aeee7b17-6b39-4822-99b3-b2d59977765e","order_by":3,"name":"Oyelola A Adegboye","email":"","orcid":"https://orcid.org/0000-0002-9793-8024","institution":"Public Health and Tropical Medicine, College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, QLD, Australia","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Oyelola","middleName":"A","lastName":"Adegboye","suffix":""},{"id":191593451,"identity":"e45e4414-5ae4-456a-b6e8-5e5ac4fbd593","order_by":4,"name":"Sanni Yaya","email":"","orcid":"https://orcid.org/0000-0002-4876-6043","institution":"School of International Development and Global Studies, University of Ottawa, Ottawa, Canada.","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sanni","middleName":"","lastName":"Yaya","suffix":""}],"badges":[],"createdAt":"2023-04-13 12:52:40","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-2812946/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2812946/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":35786793,"identity":"d5ffdd8d-29ee-4253-818d-c9c4331ed077","added_by":"auto","created_at":"2023-04-14 21:39:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":60675,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical distribution of inadequate salt iodisation consumption among pregnant and breastfeeding mothers\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2812946/v1/dcc809b7934c6cc050c07673.png"},{"id":35786795,"identity":"42f7671d-7674-4e99-a45d-3a6848380ad4","added_by":"auto","created_at":"2023-04-14 21:39:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":770666,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2812946/v1/ae89c5b9-b5b1-43b0-85fe-ef64077d8dae.pdf"},{"id":35786794,"identity":"7d27a066-c9da-40eb-a777-47884d135704","added_by":"auto","created_at":"2023-04-14 21:39:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15997,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-2812946/v1/c85ec45b9bb41602593b3e21.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAn assessment of Individual, community and state-level factors associated with inadequate iodised salt consumption among pregnant and lactating women in Nigeria\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eIodine is an essential element that directly affects thyroid gland secretions, which is necessary for fetal normal growth and development, and to a great extent, control heart action, nerve response to stimuli, and improve the motor and cognitive functions of a child (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Worldwide, iodine deficiency is the most common cause of thyroid disease. In its severe form, particularly during gestation and in the first months following birth can result in cretinism; the impairment of the brain development of a child (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Fortunately, iodine deficiency can be prevented by adequate dietary intake of iodine, which is most often achieved by adding iodine to salt (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSalt is a compound composed primarily of sodium (Na) and chloride (Cl) and is of great importance to human and animal health (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Sodium is an essential nutrient for human health via its role as an electrolyte and osmotic solute (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Iodised salt, containing potassium iodide, is the most common source of natural forms of iodine, which is an essential micronutrient for normal human growth and development (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). World Health Organization (WHO) and the International Council for the Control of Iodine Deficiency Disorders (ICCIDD) had proposed salt iodisation strategy has a universal intervention to control and eliminate Iodine deficiency and advocated that adequately iodised salt must not only reach the entire affected population, but also those groups that are the most susceptible which are pregnant women, breastfeeding mothers and young children (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePregnant women daily iodine requirement is elevated due to physiological changes in iodine metabolism (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The recommended daily iodine intake is 150 \u0026micro;g/L for adults, 220 \u0026micro;g/L for pregnant women, and 290 \u0026micro;g/L for lactating mothers (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Adequate dietary intake of Iodine is critical for brain development, and iodine deficiency is the single most important preventable cause of brain damage and irreversible mental retardation (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the introduction of salt iodisation in many countries to control iodine deficiency, adverse effects of inadequate intake continue to be a problem, with an estimated 1.9\u0026nbsp;billion people at risk worldwide (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In Turkey, a study revealed that iodine deficiency still remains a serious problem among pregnant women after eight years of compulsory salt iodination in the country (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The majority of people using non-iodised salt in most Sub-Saharan African (SSA) countries is among poor, younger women and those who were pregnant (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Also, there exist geographical variations among countries. For example, the proportion of people with no iodised salt ranges from 29.5% in Senegal, 21.3% in Tanzania, 14% in Ethiopia, 11.6% in Malawi and 10.8% in Angola (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In addition, an assessment of iodine status among pregnant women in a rural community in Ghana revealed a prevalence of 42.5% iodine deficiency (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough, Nigeria was the first African country to be declared iodine sufficient in 2007, a recent national survey has shown that only about seven in ten households consume salt with adequate iodine content (\u0026ge;\u0026thinsp;15 ppm) with variation across states (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Some studies conducted at community and state levels have shown striking differences in iodine deficiency among women. For example, a study in Zaria, Northwestern Nigeria, revealed iodine sufficiency among pregnant women (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), while another study showed that residents of Nanka and Oba towns of Anambra State, Southeastern Nigeria, were at risk of iodine deficiency disorders (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Therefore, this study utilised national representative data to assess individual- and household-, community- and state-level factors associated with inadequate iodised salt consumption among pregnant women and breastfeeding mothers in Nigeria.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cp\u003eThe Nigeria Multiple Indicator Cluster Survey (MICS) conducted between September 2016 to January 2017 was utilised for this study. The 2016-17 Nigeria MICS was designed to provide national, regional and state-level estimates and considered urban and rural differences. This cross-sectional survey is aimed at developing evidence-based policies and programmes and for monitoring progress toward national goals and global commitments. A two-stage sampling procedure was adopted using the National Integrated Survey of Households round 2 (NISH2) extracted from the 2006 Population Census as sampling frame and the basis for selecting Enumeration Areas (EAs). The Primary Sampling Units (PSUs) consisted of EAs selected in each state, while households within each EAs were selected at the second stage. The states within each of the six geo-political regions were used as the sampling strata. The MICS 2016-17 used four types of questionnaire, namely household, women, men, and under-five children questionnaire to elicit information on demographic, household, women, men and children health indicators. Information on the availability of salt for cooking and also testing for its iodine content was included in the household questionnaire. Further details on sampling technique, data collection and administration are provided in the report (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eOutcome Variable\u003c/h3\u003e\n\u003cp\u003eIn this study, we extracted information on the iodine content in salt among women who were pregnant or currently breastfeeding. The amount of iodine in salt samples were categorised into three, namely: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) salt in the household do not contain iodine (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) more than 0 parts per million (ppm) and less than 15 ppm (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) 15 ppm or more. To investigate factors associated with salt consumption with inadequate iodine content; respondents who consumed salt containing 15 ppm iodine or more were considered as having adequate iodine intake, while those who consumed salt with no iodine or less than 15 ppm were deemed deficient in iodine.\u003c/p\u003e\n\u003ch3\u003eExplanatory Variables\u003c/h3\u003e\n\u003cp\u003eThe explanatory variables were grouped into individual- and household-, community, and state-level characteristics. Individual factors considered were respondent age group (15\u0026ndash;19, 20\u0026ndash;24, 25\u0026ndash;29, 30\u0026ndash;34, 35\u0026ndash;39, 40\u0026ndash;44, 45\u0026ndash;49 years), educational status (none, primary, secondary/technical, higher and non-formal), exposure to mass media (measured using access to radio and/or television), number of children ever born (0, 1\u0026ndash;2, 3\u0026ndash;4, 5 or more), currently working (no vs yes). The household characteristics included, sex of household head (male vs female), the religion of household head (Christianity, Islam and others), ethnicity of household head (Hausa, Igbo, Yoruba and other ethnic groups) and the household wealth quintiles (poorest, poorer, middle, richer and richest). Community-level characteristics were explored using two variables, place of residence (urban vs rural) and community socio-economic status. Community refers to people living in the same locality (EAs). Community socio-economic deprivation was computed using a principal component analysis (PCA) comprising of wealth status (asset index in the poorest and poorer quintiles), unemployed, no formal education and illiteracy - those who cannot read at all. The standardised score was then categorised into tertiles (1 \u0026ndash; least deprived communities to 3 \u0026ndash; most deprived communities). Similarly, for the state-level characteristics, we extracted state socio-economic deprivation status using PCA and grouped into tertiles (1 \u0026ndash; least deprived states to 3 \u0026ndash; most deprived states) and also included regions (North Central, North East, North West, South East, South-South and South-West). (see supplementary table 1).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eThe descriptive analysis was presented using frequencies and percentages as well as the prevalence and 95% confidence interval (CI) of adequate and inadequate salt consumption. The prevalence was computed as the proportion of breastfeeding or pregnant women with adequate and inadequate iodine content in salt by women\u0026rsquo;s background characteristics. Similarly, the test of homogeneity of the proportion of inadequate iodised salt intake across the categories of each individual/household-, community and state characteristics were reported based on the corrected Pearson χ2 statistic. To account for the complex survey design, the Pearson χ2 statistic is transformed into an F-statistic with non-integer degrees of freedom using a second-order Rao and Scott correction (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Then, five multi-level mixed effect log-binomial logistic regression models were fitted to the data in order of complexity. First, a null model (Model 1, with no explanatory variables) was fitted to the data to explore the variation due to community and state effects only. The second model (Model 2) included individual and household variables, while the third model (Model 3) had only community characteristics. In the fourth model (Model 4), we examined only the state-level variables. The full model (Model 5) considered all individual, community and state-level variables. The Loglikelihood, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to assess the goodness of fits of the models. A lower value of the model statistic is said to be a better fit. More succinctly, if the difference between two information criteria (IC) value is greater than 10, this implies that the model with a smaller IC is superior while a difference of 4 to 10 suggest a moderate superiority and a difference less than 4 implies that the two models are indistinguishable (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). All analyses were adjusted for the complex survey design and analysed using Stata 15.0 (StataCorp LLC, College Station, Texas, USA). Statistical Inferences were based on a 5% level of significance.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical Consideration\u003c/h3\u003e\n\u003cp\u003eThis study was based on an analysis of a publicly available secondary dataset\u0026ndash;the Multiple Indicator Cluster Survey; thus, no additional ethical clearance is required. Before conducting the survey, ethical clearance was obtained from the National Health Research Committee, and informed consent was taken from each participant before conducting the interview. Information on privacy, confidentiality and the right of respondents to withdraw from the study at any time were clearly stated (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive statistics\u003c/h2\u003e \u003cp\u003eData from a total of 4911 pregnant and breastfeeding women were eligible for the study. One in ten women were adolescents, and 56.7% had no or non-formal education (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Almost one in ten (10.8%) reported never having any childbirth, only 20.7% of the women were currently working, and 46.6% had no access to television or radio. About half of the household heads had no or non-formal education, were males (92.8%), are majorly Muslims (71.9%), and from the Hausa ethnic group (60%). Wealth was evenly distributed among each category of the quintiles in the study population. For the community characteristics, 76.4% of the respondents resided in rural areas, and one-third were least deprived. The majority (seven in ten) of the respondents were from the Northern states, particularly, North-western region (44.4%), whereas 34.8% of respondents are living in the least deprived state compared to 31.3% of the respondents who are living in the poorest states.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive summaries of respondents\u0026rsquo; background characteristics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIndividual and Household characteristics\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e502 (10.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1053 (21.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1273 (25.94%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e967 (19.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e653 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e312 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of Education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1579 (32.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e684 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary/technical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1140 (23.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e307 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-formal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1200 (24.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExposure to mass media\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2287 (46.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes (TV/radio)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2624 (53.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildren ever born\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e531 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1621 (33.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1271 (25.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5 or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1489 (30.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrently working\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1016 (20.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3895 (79.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex of household head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4556 (92.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e355 (7.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion of household head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristianity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1341 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3530 (71.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity of household head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHausa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2967 (60.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIgbo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e275 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoruba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e455 (9.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther ethnic groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1214 (24.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation of household head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1217 (24.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e769 (15.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary/technical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1007 (20.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e605 (12.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-formal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1314 (26.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e968 (19.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e975 (19.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e984 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e993 (20.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e992 (20.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCommunity characteristics\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1159 (23.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3752 (76.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocio-economic status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 (Least deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1651 (33.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 (More deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1627 (33.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 (Most deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1633 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eState and regional characteristics\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocio-economic status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 (Least deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1707 (34.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 (More deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1667 (33.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 (Most deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1536 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e840 (17.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e932 (19.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2179 (44.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e175 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e337 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e448 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e4911 (100%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePrevalence Of Adequate And Inadequate Iodine Content In Salt\u003c/h3\u003e\n\u003cp\u003eThe prevalence of inadequate iodised salt consumption among pregnant and breastfeeding mothers was 35.2% (95% CI: 33.1\u0026ndash;37.5), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Inadequate consumption of iodised salt was highest among pregnant and breastfeeding women aged 45\u0026ndash;49 years (48.2%; 95%CI: 37.8\u0026ndash;58.8), as well as those with non-formal education (52.7%; 95%CI: 47.7\u0026ndash;57.6) and no education (34.6%; 95%CI: 31.3\u0026ndash;38.1). Respondents who were exposed to mass media (30.0%), currently working (22.9%), and female headed-household (26.8%) had a lower prevalence of consuming salt with inadequate iodine compared to those with no access to mass media (41.2%), not working (38.4%) and male-headed household (35.9%), respectively. Wealth status was associated with intake of salt deficient in iodine; for example, 46.8% (95% CI: 42.1\u0026ndash;51.5) of those in the poorest wealth quintile consume salt with inadequate iodine, while only 21.5% (95% CI: 17.6\u0026ndash;25.9) among those in the richest quintile. Similarly, iodised salt intake was associated with community socio-economic deprivation and state socio-economic deprivation. For example, respondents in communities that are least deprived (23.0% vs 41.9%) and those in the least deprived states (22.6% vs 46.0%) had a lower prevalence of inadequate iodised salt intake compared to the respondent in the most deprived communities and states. Also, inadequate iodised salt intake was higher among respondents who reside in the rural (37.0% vs 29.3%) compared to urban areas and among those who are Hausas (p\u0026thinsp;=\u0026thinsp;43.1%; 95%CI: 39.9\u0026ndash;46.3) compared to all other ethnic groups. Almost one in ten pregnant or breastfeeding women in the North West consume salt with inadequate iodine. The corrected Pearson χ2 statistic also suggest that the proportion of inadequate iodised salt consumption differs across the categories of each background characteristics considered (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all variables).\u003c/p\u003e \u003cp\u003eFurthermore, the geographic distribution of inadequate iodised salt consumption among pregnant and breastfeeding mothers by states is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. the spatial map revealed the high burden of inadequate iodised salt intake in the Northwestern region; particularly with the highest burden in Zamfara (70.4%), Kebbi (67.1%) and Ekiti state (64.8%) in the Southwestern region.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of Iodised salt intake by women\u0026rsquo;s individual/household, community and state-level characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePrevalence (95% CI)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ePrevalence (95% CI)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eF-statistic\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026dagger;\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdequate Iodized Salt\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInadequate Iodized Salt\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOverall\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.8(62.5\u0026ndash;67.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.2(33.1\u0026ndash;37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIndividual and Household characteristics\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.4(48.3\u0026ndash;60.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.6(39.5\u0026ndash;51.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.1(63.7\u0026ndash;72.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.9(27.9\u0026ndash;36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.7(63.3\u0026ndash;70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.3(30.0-36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.3(64.4\u0026ndash;72.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.7(27.9\u0026ndash;35.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63.5(58.9\u0026ndash;68.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.5(32.0-41.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60.1(52.7\u0026ndash;67.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.9(33.0-47.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51.8(41.2\u0026ndash;62.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.2(37.8\u0026ndash;58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of Education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65.4(61.9\u0026ndash;68.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.6(31.3\u0026ndash;38.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.3(63.3\u0026ndash;72.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.7(27.1\u0026ndash;36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary/technical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.3(71.6\u0026ndash;78.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.7(21.2\u0026ndash;28.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82.8(75.5\u0026ndash;88.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.2(11.8\u0026ndash;24.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-formal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47.3(42.4\u0026ndash;52.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.7(47.7\u0026ndash;57.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExposure to mass media\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.8(55.6\u0026ndash;62.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.2(38.1\u0026ndash;44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes (TV/radio)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70.0(67.1\u0026ndash;72.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.0(27.4\u0026ndash;32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 (None)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.5(62.9\u0026ndash;73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.5(26.5\u0026ndash;37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67.1(63.9\u0026ndash;70.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.9(29.8\u0026ndash;36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65.3(61.4\u0026ndash;69.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.7(31.0-38.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5 or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60.5(57.0-63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.5(36.1\u0026ndash;43.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrently working\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77.1(73.7\u0026ndash;80.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.9(19.9\u0026ndash;26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.6(60.0-64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.4(35.9\u0026ndash;41.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex of household head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.1(61.8\u0026ndash;66.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.9(33.6\u0026ndash;38.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73.3(67.2\u0026ndash;78.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.8(21.4\u0026ndash;32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion of household head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristianity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76.8(73.7\u0026ndash;79.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.2(20.5\u0026ndash;26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60.1(57.2\u0026ndash;62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.9(37.1\u0026ndash;42.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76.1(61.6\u0026ndash;86.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.0(13.7\u0026ndash;38.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity of household head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHausa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.9(53.7\u0026ndash;60.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.1(39.9\u0026ndash;46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIgbo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85.4(80.5\u0026ndash;89.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.6(10.8\u0026ndash;19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoruba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74.4(69.0-79.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.6(20.8\u0026ndash;31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther ethnic groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.7(71.8\u0026ndash;79.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.3(20.8\u0026ndash;28.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation of household head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71.3(67.7\u0026ndash;74.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.7(25.3\u0026ndash;32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67.5(62.1\u0026ndash;72.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.5(27.5\u0026ndash;37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary/technical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70.7(66.7\u0026ndash;74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.3(25.6\u0026ndash;33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71.8(65.4\u0026ndash;77.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.2(22.5\u0026ndash;34.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-formal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.3(44.6\u0026ndash;54.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.7(45.9\u0026ndash;55.5))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.2(48.5\u0026ndash;57.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.8(42.1\u0026ndash;51.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.9(54.2\u0026ndash;63.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.1(36.5\u0026ndash;45.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.1(58.6\u0026ndash;69.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.0(30.8\u0026ndash;41.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.7(63.9\u0026ndash;73.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.3(26.8\u0026ndash;36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78.5(74.1\u0026ndash;82.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.5(17.6\u0026ndash;25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCommunity characteristics\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70.7(66.4\u0026ndash;74.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.3(25.4\u0026ndash;33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63.0(60.3\u0026ndash;65.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.0(34.5\u0026ndash;39.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocio-economic status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 (Least deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77.0(73.5\u0026ndash;80.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.0(19.8\u0026ndash;26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 (More deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.1(54.8\u0026ndash;63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.9(36.8\u0026ndash;45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 (Most deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.1(54.0-62.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.9(37.9\u0026ndash;46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eState and regional characteristics\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocio-economic status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 (Least deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77.4(74.4\u0026ndash;80.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.6(19.9\u0026ndash;25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 (More deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.8(57.7\u0026ndash;65.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.2(34.2\u0026ndash;42.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 (Most deprived)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.0(49.6\u0026ndash;58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.0(41.8\u0026ndash;50.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82.8(78.6\u0026ndash;86.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.3(13.8\u0026ndash;21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.8(64.0\u0026ndash;75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.2(25.0\u0026ndash;36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.6(46.3\u0026ndash;53.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.4(47.0-53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86.5(81.4\u0026ndash;90.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.5(9.6\u0026ndash;18.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82.6(77.6\u0026ndash;86.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.4(13.3\u0026ndash;22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72.4(66.9\u0026ndash;77.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.6(22.7\u0026ndash;33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u003cem\u003e\u0026dagger;\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eCorrected Pearson χ2 statistic accounting for the complex survey design\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eMuti-level Mixed Effect Log-binomial Regression Model\u003c/h3\u003e\n\u003cp\u003eWe fitted five multi-level mixed effect log-binomial regression models to our data. The null model (Model 1) showed a high intracluster correlation (ICC) of 45.3% (95%CI 40.3\u0026ndash;50.3), an indication of greater dependency between levels. Similar results were obtained for models 2\u0026ndash;5, suggesting the appropriateness of a multi-level approach. After adjusting for individual and household characteristics in Model 2, we found a direct negative significant association between increasing wealth status and inadequate iodised salt intake. Respondents in the poorer, middle, richer and richest quintiles were 32%, 47%, 35% and 62% less likely to consume salt with inadequate iodine compared to those in the poorest households. Also, pregnant and breastfeeding mothers who were Igbos (aRR 0.29; 95%CI 0.16\u0026ndash;0.54) and other ethnic groups (aRR 0.49; 95%CI 0.35\u0026ndash;0.70) were less likely to consume salt with inadequate iodine compared to Hausas. However, respondents with no formal education were 1.8 times (95%CI: 1.36\u0026ndash;2.42) more likely to consume salt with deficient iodine compared to those with no education, and households whose head had a secondary, higher, and non-formal education were 50%, 59% and 94% more likely to consume salt with inadequate iodine compared to those with no education.\u003c/p\u003e \u003cp\u003eIn Model 3, we adjusted for the community socio-economic status. Pregnant and breastfeeding mothers residing in moderately and most deprived communities were 3.5 (95%CI: 2.57\u0026ndash;4.73) and 4.7 times (95%CI: 3.38\u0026ndash;6.55) more likely to consume salt with inadequate iodine than those from least deprived communities. Similarly, Model 4 showed that those residing in moderately and most deprived states were 1.9 (95%CI: 1.14-3.00) and 2.6 (95%CI: 1.50\u0026ndash;4.44) times more likely to consume salt with inadequate iodine than those from least deprived states. Also, respondents from the North West and those from South West were 5.1 (95%CI: 3.18\u0026ndash;8.30) and 2.9 (95%CI: 1.77\u0026ndash;4.59) times more likely to consume salt with inadequate iodine compared to those from the North-Central region.\u003c/p\u003e \u003cp\u003eIn the fully adjusted model (Model 5), including individual/household, community and state-level characteristics. Our analysis showed that respondents with no-formal education were 1.7 (95%CI: 1.25\u0026ndash;2.31) times more likely to consume inadequately iodised salt compared to those with no education. Similarly, household heads with no formal education (aRR 1.71; 95%CI: 1.16\u0026ndash;2.52) and secondary education (aRR 1.44; 95%CI: 1.02\u0026ndash;2.04) were associated with inadequate iodised salt intake compared to those with no education. Respondents in the middle (aRR 0.64; 95%CI: 0.42\u0026ndash;0.97) and richest (aRR 0.51; 95%CI: 0.26\u0026ndash;0.99) wealth quintiles were less likely to consume inadequately iodised salt compared to those in the poorest quintile. Also, respondents in the most deprived communities were 96% more likely to consume salt with inadequate iodine than those in the least deprived communities. Women in the Northwestern region and those from the Southwestern region were 4.0 and 3.5 times, respectively, more likely to consume salt with inadequate iodine compared to pregnant and breastfeeding women residing in the North-Central region. Results from the model fit revealed that model 5 has the best fit based on loglikelihood (-2721.61) and AIC (5525.22) while the BIC showed that both model 1 and Model 5 are indistinguishable (BIC: 5792.44 vs 5791.69) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Factors associated with inadequate iodised salt intake among pregnant and breastfeeding mothers from multi-level logistic regression\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cem\u003eNull Model 1\u003csup\u003ea\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cem\u003eModel 2\u003csup\u003eb\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cem\u003eModel 3\u003csup\u003ec\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u003cem\u003eModel 4\u003csup\u003ed\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cem\u003eModel 5\u003csup\u003ee\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20%\"\u003e\n \u003cp\u003e\u003cem\u003eRR(95% CI)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20%\"\u003e\n \u003cp\u003e\u003cem\u003eaRR(95% CI)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20%\"\u003e\n \u003cp\u003e\u003cem\u003eaRR(95% CI)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.96153846153846%\"\u003e\n \u003cp\u003e\u003cem\u003eaRR(95% CI)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.03846153846154%\"\u003e\n \u003cp\u003e\u003cem\u003eaRR(95% CI)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cem\u003eIndividual and Household characteristics\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e15-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e20-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.84(0.56-1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.91(0.60-1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e25-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.92(0.61-1.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.01(0.67-1.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e30-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.77(0.49-1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.87(0.54-1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e35-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.89(0.55-1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.98(0.60-1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e40-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e1.24(0.71-2.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.38(0.78-2.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e45-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e1.37(0.71-2.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.46(0.76-2.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLevel of Education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e1.01(0.73-1.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.30(0.84-2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eSecondary/technical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e1.02(0.65-1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.26(0.72-2.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.61(0.32-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.78(0.38-1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eNon-formal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.81(1.36-2.42)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.70(1.25-2.31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposure to mass media\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eYes (TV/radio)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.86(0.68-1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.87(0.69-1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e0 (None)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e1-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.97(0.68-1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.94(0.66-1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e3-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e1.03(0.69-1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.96(0.64-1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e5 or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e1.01(0.65-1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.90(0.57-1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrently working\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.83(0.63-1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.99(0.74-1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex of household head\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e1.27(0.86-1.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.30(0.88-1.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion of household head\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eChristianity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eIslam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e1.07(0.76-1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.87(0.60-1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.71(0.31-1.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.70(0.29-1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity of household head\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eHausa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eIgbo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.29(0.16-0.54)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.42(0.18-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eYoruba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.93(0.58-1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.99(0.51-1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eOther ethnic group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.49(0.35-0.70)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.86(0.58-1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation of Household head\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e1.30(0.90-1.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.24(0.85-1.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eSecondary/technical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.50(1.07-2.11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.44(1.02-2.04)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.59(1.01-2.50)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.45(0.91-2.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eNon-formal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.94(1.33-2.83)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.71(1.16-2.52)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003ePoorer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.68(0.48-0.97)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.75(0.53-1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.53(0.36-0.80)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.64(0.42-0.97)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eRicher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.65(0.43-0.98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.86(0.54-1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.38(0.22-0.67)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.51(0.26-0.99)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cem\u003eCommunity characteristics\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e0.79(0.57-1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e0.85(0.58-1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocio-economic status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e1 (Least deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e2 (More deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.49(2.57-4.73)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.56(0.95-2.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e3 (Most deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.71(3.38-6.55)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.96(1.04-3.72)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cem\u003eState and regional characteristics\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocio-economic status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e1 (Least deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e2 (More deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.85(1.14-3.00)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.27(0.75-2.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e3 (Most deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.58(1.50-4.44)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.65(0.90-3.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eNorth Central\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eNorth East\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e1.29(0.71-2.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.41(0.75-2.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eNorth West\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.14(3.18-8.30)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.01(2.27-7.08)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eSouth East\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e0.88(0.50-1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e2.02(0.77-5.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eSouth South\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e1.23(0.74-2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e1.57(0.89-2.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eSouth West\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.85(1.77-4.59)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.46(1.79-6.68)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eRandom effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eICC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e45.3(40.3-50.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e38.7(33.4-44.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e43.2(38.1-48.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e37.9(32.8-43.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e37.5(32.2-43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eModel fit statistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eLoglikelihood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e-2906.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e-2764.482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e-2851.675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e-2778.321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e-2721.608\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eAIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e5817.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e5590.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e5713.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e5574.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e5525.216\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.503725782414307%\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e5830.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e5792.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.49925484351714%\"\u003e\n \u003cp\u003e5745.846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.24441132637854%\"\u003e\n \u003cp\u003e5633.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.754098360655737%\"\u003e\n \u003cp\u003e5791.685\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eRR relative risk, aRR adjusted relative risk, CI confidence interval, ICC intracluster correlation\u003c/p\u003e\n\u003cp\u003eThe aRR in bold implies significance at 5%\u003c/p\u003e\n\u003cp\u003ea Null ModeI 1 \u0026ndash; baseline model without any explanatory variables (unconditional model)\u003c/p\u003e\n\u003cp\u003eb Model 2 \u0026ndash; adjusted for only individual and household-level factors\u003c/p\u003e\n\u003cp\u003ec Model 3 \u0026ndash; adjusted for only community-level factors\u003c/p\u003e\n\u003cp\u003ed Model 4 \u0026ndash; adjusted for only state-level factors\u003c/p\u003e\n\u003cp\u003ee Model 5 \u0026ndash; adjusted for individual and household-, community-, and country-level factors (full model)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIodine deficiency is a global public health threat, especially for pregnant, lactating women and children under two years old. The focus of this retrospective cross-sectional study was to investigate factors associated with inadequate iodised salt consumption among pregnant and lactating women in Nigeria. This study was expedient in light of the limited empirical literature on iodised salt consumption in Nigeria. The overall prevalence of inadequate iodised salt consumption among pregnant and lactating women in this study was 35.2%. The multi-level mixed-effect logistic model showed that pregnant and lactating women with non-formal education were more likely to consume inadequately iodised salt compared to those with formal education after adjusting for other multivariable factors. We found households with uneducated heads to be associated with increased risks of inadequate iodised salt consumption. This is likely due to nutritional education which are sometimes received by those with formal education as part of their usual lessons. In addition to formal education, non-formal education could be a promising platform for routing nutrition and its related educational and advocacy interventions. The importance of education to the consumption of iodised salt has been reported in studies from other sub-Saharan African countries such as Ethiopia (Tariku \u0026amp; Mazengia, 2019) and Ghana (Buxton \u0026amp; Baguune, 2012). Non-formal education in Nigeria targets children, youths and adults who either have dropped out of school or have never been to school (Adewale 2009).\u003c/p\u003e \u003cp\u003eOur findings are similar to those reported by Udofia, Yawson, Aduful et al. 2014; Narayan 2000 and Gweshengwe \u0026amp; Hassan, 2020, that women living in the most deprived communities were more likely to consume salt with inadequate iodine compared to those who reside in the least deprived communities. Residents of deprived communities are likely to be less endowed economically and may have little negotiation and purchasing power (Narayan 2000). Without a strong negotiation and purchasing power, one can easily be persuaded to improvise with whatever they come across, even if they are fully aware of the adverse effects associated with that action (French, Tangney, Crane et al. 2019).\u003c/p\u003e \u003cp\u003ePregnant and breastfeeding women who belong to the top household wealth quintiles were less likely to consume inadequate iodised salt compared to those in the poorest category. Wealth or richness is associated with good nutrition and good health status, as empirical research suggests (Hong \u0026amp; Mishra, 2006; Angeles-Agdeppa, Lenighan, Jacquier et al, 2019). Wealthy persons usually tend to live in clean, hygienic and well-planned settlements, access quality healthcare and have frequent check-ups (Armah, Ekumah, Yawson et al, 2018). The indigent, however, is usually concerned with how to put food on the table and cater for the necessities of life as purported by Maslow\u0026rsquo;s Hierarchy of Needs (Maslow \u0026amp; Lewis, 1987). These substantial variations may account for the findings in this study. Enhancing women\u0026rsquo;s economic opportunities by training them in various skills can increase their employability prospects and thereby make them economically sound to enable them to take the right nutrition, including iodised salt.\u003c/p\u003e \u003cp\u003eThis study also revealed that those in Northwestern and Southwestern regions were more likely to consume salt with inadequate iodine compared to pregnant and breastfeeding women in the North- Central region. This suggests inequality in the distribution of iodised salt within Nigeria or disparity in the consumption pattern of iodised salt. Context appropriate education on iodised salt utilisation would be recommended in those regions with relatively low consumption of iodised salt. These educational campaigns can be channelled through widely accessed media channels such as radio or television.\u003c/p\u003e"},{"header":"Strengths And Limitations Of The Study","content":"\u003cp\u003eUnlike previous studies on salt iodisation (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) this study focused on two key populations, pregnant and lactating women. It also followed rigorous and appropriate analytical procedures, thereby generating robust and reliable findings. The findings are also generalisable to all pregnant and lactating women in Nigeria, and its lessons/recommendations are useful for other sub-Saharan African countries. One of the major limitations of this paper is the cross-sectional nature of the study design, which do not allow for causal inference of the associated factors. WHO recommendation is not to have too much iodine in salt but a concentration of between 15 to 40 ppm of iodine. However, the classification of iodine content in salt samples in the MICS dataset into three main categories \u0026ndash; 0 ppm, \u0026lt;\u0026thinsp;15 ppm and \u0026ge;\u0026thinsp;15ppm limit our investigation to examine the range of iodine content in salt at the household level. More so, the urinary iodine concentration test was not collected; this would have provided additional insight into the iodine status of pregnant and breastfeeding mothers.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study revealed the prevalence of pregnant and lactating women in Nigeria with inadequate iodised salt consumption as well as other associated factors. Findings are suggestive that measures to overcome inadequate iodised salt consumption include ensuring equitable distribution of essential food commodities among the more and most deprived communities. Besides, there is the need to enhance women\u0026rsquo;s economic opportunities by training them in various skills that can increase their employability prospects and thereby making them economically sound to enable them to take proper nutrition, including iodised salt. Both formal and non-formal educational initiatives on nutrition are extremely important and should be prioritised by the Nigerian government in its efforts to ensure adequate consumption of iodised salt among pregnant and lactating mothers.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eWHO - World Health Organization (WHO)\u003c/p\u003e \u003cp\u003eICCIDD - International Council for the Control of Iodine Deficiency Disorders\u003c/p\u003e \u003cp\u003eMICS - Multiple Indicator Cluster Survey\u003c/p\u003e \u003cp\u003eAIC - Akaike Information Criterion\u003c/p\u003e \u003cp\u003eBIC - Bayesian Information Criterion\u003c/p\u003e \u003cp\u003eppm \u0026ndash; part per million\u003c/p\u003e \u003cp\u003eNISH2 - National Integrated Survey of Households round 2\u003c/p\u003e \u003cp\u003eEA \u0026ndash; Enumeration Areas\u003c/p\u003e \u003cp\u003ePSU \u0026ndash; Primary Sampling Unit\u003c/p\u003e \u003cp\u003ePCA - Principal Component Analysis\u003c/p\u003e \u003cp\u003eCI \u0026ndash; Confidence Interval\u003c/p\u003e \u003cp\u003eaRR \u0026ndash; adjusted relative risk\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eEthics approval was not required for this study since the data is secondary and is available in the public domain. More details regarding DHS data and ethical standards are available at: http://goo.gl/ny8T6X. All methods were performed in accordance with the relevant guidelines and regulations (e.g., Declaration of Helsinki).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: The authors thank the MEASURE DHS project for their support and for free access to the original data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe authors received no funding for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u0026nbsp;\u003c/strong\u003eData for this study were sourced from the Multiple Indicator Cluster Surveys and available here: https://mics.unicef.org/surveys\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions:\u0026nbsp;\u003c/strong\u003eYOK conceptualized, designed, analyzed, and wrote the methodology as well as the results sections of the manuscript. EKA contributed to the analysis and the discussion of the manuscript. EM, contributed to the introductory section of the manuscript. OAA and YS contributed to the interpretation and revision of the manuscript. YS had final responsibility to submit. All authors read, agreed, and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eThe authors acknowledge the Multiple Indicator Cluster Survey for granting permission and access to the data used for this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eChung HR, 2014. Iodine and thyroid function. Annals of pediatric endocrinology \u0026amp; metabolism, 19(1), p.8. 2014.\u003c/li\u003e\n \u003cli\u003eSkeaff SA. Iodine deficiency in pregnancy: the effect on neurodevelopment in the child. Nutrients 2011;3(2):265-273 doi:103390/nu3020265. 2011.\u003c/li\u003e\n \u003cli\u003eWHO. Assessment of iodine deficiency disorders and monitoring their elimination : a guide for programme managers, 3rd ed. World Health Organization. https://apps.who.int/iris/handle/10665/43781. 2007.\u003c/li\u003e\n \u003cli\u003eWood FO, Ralston RH, Hills JM. Salt. Encyclopedia Britannica. https://www.britannica.com/science/salt. 2021.\u003c/li\u003e\n \u003cli\u003eNissen SE. US dietary guidelines: an evidence-free zone. 2016.\u003c/li\u003e\n \u003cli\u003eThomson CD, Skeaff SA. Iodine status and deficiency disorders in New Zealand. Preedy VR, Burrow GN and Watson RR Comprehensive Handbook of Iodine-Nutritional, Biochemical Pathological and Therapeutic aspects, 1252. 2009.\u003c/li\u003e\n \u003cli\u003eKapil U. Health consequences of iodine deficiency. Sultan Qaboos University medical journal. 2007;7(3):267-72.\u003c/li\u003e\n \u003cli\u003eGlinoer D. The importance of iodine nutrition during pregnancy. Public Health Nutr 2007;10:1542\u0026ndash;6. 2007.\u003c/li\u003e\n \u003cli\u003eMao G, Zhu W, Mo Z, Wang Y, Wang X, Lou X, et al. Iodine deficiency in pregnant women after the adoption of the new provincial standard for salt iodization in Zhejiang Province, China. . BMC pregnancy and childbirth, 18(1), 1-7. 2018.\u003c/li\u003e\n \u003cli\u003eZimmermann MB, Boelaert K. Iodine deficiency and thyroid disorders. . The lancet Diabetes \u0026amp; endocrinology, 3(4), 286-295. 2015.\u003c/li\u003e\n \u003cli\u003eZimmermann MB, Gizak M, Abbott K, Andersson M, Lazarus JH. Iodine deficiency in pregnant women in Europe. . The lancet Diabetes \u0026amp; endocrinology, 3(9), 672-674. 2015.\u003c/li\u003e\n \u003cli\u003eZimmermann MB, Andersson M. Update on iodine status worldwide. Current Opinion in Endocrinology, Diabetes and Obesity, 19(5), 382-387. 2012.\u003c/li\u003e\n \u003cli\u003eKut A, Gursoy A, Şenbayram S, Bayraktar N, Budakoğlu Iİ, Akg\u0026uuml;n HS. Iodine intake is still inadequate among pregnant women eight years after mandatory iodination of salt in Turkey. . Journal of endocrinological investigation, 33(7), 461-464. 2010.\u003c/li\u003e\n \u003cli\u003eBa D, Ssentongo P, Liao D, Du P, Kjerulff K. Non-iodised salt consumption among women of reproductive age in sub-Saharan Africa: A population-based study. . Public Health Nutrition, 23(15), 2759-2769 doi:101017/S1368980019003616. 2020.\u003c/li\u003e\n \u003cli\u003eSimpong DL, Adu P, Bashiru R, Morna MT, Yeboah FA, Akakpo K, et al. Assessment of iodine status among pregnant women in a rural community in ghana-a cross sectional study. . Archives of Public Health, 74(1), 1-5. 2016.\u003c/li\u003e\n \u003cli\u003eMICS. National Bureau of Statistics (NBS) and United Nations Children\u0026rsquo;s Fund (UNICEF). 2017 Multiple Indicator Cluster Survey 2016-17, Survey Findings Report. Abuja, Nigeria: National Bureau of Statistics and United Nations Children\u0026rsquo;s Fund. 2017.\u003c/li\u003e\n \u003cli\u003eJibril MEB, Abbiyesuku FM, Aliyu IS, Randawa AJ, Adamu R, Akuyam SA, et al. Nutritional iodine status of pregnant women in Zaria, North-Western Nigeria. Sub-Saharan African Journal of Medicine, 3(1), 41. 2016.\u003c/li\u003e\n \u003cli\u003eOlife IC, Anajekwu, B. A., \u0026amp; Onuogbu, A. K. . Assessment of iodine status of some selected populations in Anambra state, Nigeria. BCAIJ, 7(3), 2013 [97-101]. 2013.\u003c/li\u003e\n \u003cli\u003eRao JNK, Scott AJ. The analysis of categorical data from complex sample surveys: Chi-squared tests for goodness of fit and independence in two-way tables. Journal of the American Statistical Association 1981;76:221-30.\u003c/li\u003e\n \u003cli\u003eRao JNK, Scott AJ. On chi-squared tests for multiway contingency tables with cell proportions estimated from survey data. Annals of Statistics. 1984;12:46-60.\u003c/li\u003e\n \u003cli\u003eKareem YO, Morhason-Bello IO, Adebowale AS, Akinyemi JO, Yusuf OB. Robustness of zero-augmented models over generalized linear models in analysing fertility data in Nigeria. BMC Research Notes. 2019;12(1):815.\u003c/li\u003e\n \u003cli\u003ePan W. Akaike\u0026rsquo;s information criterion in generalized estimating equations. Biometrics 2001;57(1):120\u0026ndash;5. 2001.\u003c/li\u003e\n \u003cli\u003eUgo J, \u0026amp; Chinwe, E. . A pilot study of iodine and anthropometric status of primary school children in Obukpa, a rural Nigerian community. Journal of public Health and Epidemiology, 4(9), 246-252. 2012.\u003c/li\u003e\n \u003cli\u003eUmenwanne EO, \u0026amp; Akinyele, I. O. Inadequate salt iodization and poor knowledge, attitudes, and practices regarding iodine-deficiency disorders in an area of endemic goitre in south-eastern Nigeria. Food and Nutrition Bulletin, 21(3), 311-315. 2000.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Salt, Iodine-deficiency, pregnant women, breastfeeding mothers, Cross-sectional survey, Multi-level analysis, Nigeria","lastPublishedDoi":"10.21203/rs.3.rs-2812946/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2812946/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIodine deficiency is the most common cause of thyroid disease, and in its severe form can result in cretinism; the impairment of the brain development of a child. Pregnant and breastfeeding women daily iodine requirement is elevated due to physiological changes in iodine metabolism, requiring up to double the iodine intake of other women. Despite the introduction of salt iodisation in many countries to control iodine deficiency disorders, adverse effects of inadequate iodine intake continue to be a problem.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study utilised the Multiple Indicator Cluster Survey to assess factors associated with inadequate iodised salt consumption among pregnant women and breastfeeding mothers in Nigeria. The descriptive analysis was presented using frequencies and percentages. The prevalence of adequate and inadequate iodised salt consumption with their 95% confidence interval were computed. Several multi-level mixed effect log-binomial logistic regressions was used to explore the factors associated with inadequate iodised salt consumption. The Loglikelihood, Akaike Information Criterion and Bayesian Information Criterion were used to assess the goodness of fit of the models. All analyses were adjusted for the complex survey design and analysed using Stata 15.0 at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOur findings revealed that pregnant and breastfeeding women living in most deprived communities, with no formal education, poor wealth status, and those residing in the North West and South West region were more likely to consume salt with inadequate iodine.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThere is a need to enhance women\u0026rsquo;s economic opportunities and empowerment as well as sensitisation on their nutritional requirements during pregnancy and breastfeeding.\u003c/p\u003e","manuscriptTitle":"An assessment of Individual, community and state-level factors associated with inadequate iodised salt consumption among pregnant and lactating women in Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-04-14 21:39:29","doi":"10.21203/rs.3.rs-2812946/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1ddbeb60-054a-4fe4-9fce-f64c12cb6848","owner":[],"postedDate":"April 14th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":20699972,"name":"Epidemiology"}],"tags":[],"updatedAt":"2023-04-14T21:39:29+00:00","versionOfRecord":[],"versionCreatedAt":"2023-04-14 21:39:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2812946","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2812946","identity":"rs-2812946","version":["v1"]},"buildId":"oE6Zbj460LM0Up2FdVbMZ","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}