Determinants of Child Under-Five Mortality in Ghana: Analysis of the 2022 DHS Survey

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Significant sociodemographic and geographical discrepancies still exist in Ghana despite significant advances. Effective policy interventions require an understanding of the factors that contribute to death in children under five. Methods 39,305 women between the ages of 15 and 49 who gave birth within the five years before to the survey were included in a secondary analysis of the 2022 Ghana Demographic and Health Survey. To evaluate the relationships between under-five mortality and maternal age, education, marital status, household wealth, region, antenatal care, immunisation, postnatal care, and exclusive breastfeeding, descriptive statistics were conducted first, and then bivariate and multivariate logistic regression analyses were conducted. The threshold for statistical significance was fixed at p < 0.05. Results The percentage of mothers who reported child deaths under five was about 25.2%. In comparison to adolescents aged 15–19 years (p < 0.001), older maternal age was significantly linked to higher odds of under-five mortality, especially among women aged 25–29 years (AOR = 2.50), 30–34 years (AOR = 4.57), and 35–49 years (AOR = 8.44). All categories of marital status showed higher odds relative to women never in union. Protective factors included secondary (AOR = 0.55) and higher education (AOR = 0.25), richest household wealth (AOR = 0.42), exclusive breastfeeding (AOR = 0.85), and immunisation uptake, with children having 2–3 immunisation entries showing a 77% reduction in mortality risk (AOR = 0.23) ( p < 0.001). Conclusion Maternal health service use and sociodemographic disparities are the main causes of under-five mortality in Ghana. Strengthening maternal education, reducing socioeconomic disparities, and expanding immunisation and breastfeeding support are essential for achieving Sustainable Development Goal 3.2. Trial registration Not applicable. Under-five mortality Ghana maternal health sociodemographic factors immunisation breastfeeding Figures Figure 1 Introduction Despite significant progress in recent decades, child mortality under five remains a significant global public health concern. The global death rate decreased to 37 per 1,000 live births in 2023 from 94 per 1,000 live births in 1990. Nevertheless, 4.8 million children under five died in 2023, many of them from diseases that could have been prevented or cured ( 1 ). In low- and middle-income nations, where socioeconomic disparities and health system issues still pose a threat to child survival, this burden is especially great. A disproportionate amount of this death occurs in Sub-Saharan Africa, mostly as a result of avoidable causes such infectious illnesses (malaria, pneumonia, and diarrhoea), difficult deliveries, and inadequate care for mothers and newborns ( 1 ). Achieving Sustainable Development Goal 3.2, which calls for a U5MR of at least 25 per 1,000 live births by 2030, depends on lowering child mortality in this area. Under-five mortality in Ghana has steadily decreased; predictions for 2020 show a U5MR of roughly 42–44 per 1,000 live births ( 2 , 3 ). According to time series analyses, if current trends continue, the U5MR will be about 30.5 per 1,000 by 2030 ( 4 ). However, neonatal disorders like preterm, respiratory distress, and sepsis, as well as infectious diseases like malaria, are the leading causes of under-five mortality, which continues to be a significant public health problem ( 2 , 3 ). Regional disparities persist, with children in northern and rural areas at higher risk compared to those in urban and southern regions, reflecting inequalities in healthcare access and socioeconomic status ( 5 , 6 ). Ghanaian studies have identified several factors that influence child mortality. Higher mother education and female child sex are protective against death, whereas multiple births, high parity, and living in certain areas raise the risk, according to analyses of the 2014 Ghana Demographic and Health Survey (GDHS) ( 7 , 8 ). Urban-rural differences remain evident, with children in rural and northern areas experiencing higher mortality, largely influenced by socioeconomic conditions and access to healthcare ( 5 , 6 ). Malaria remains a critical contributor to under-five mortality in Ghana, with spatial analyses showing high malaria burden and district-level variation, particularly in northern regions ( 7 ). Environmental factors such as access to improved water and sanitation also significantly affect child survival, with children in households using pit toilets or borehole water at higher risk of death ( 8 , 9 ). Socioeconomic predictors, including maternal age, birth spacing, and health insurance coverage, further influence mortality outcomes ( 16 ). Despite these insights, significant gaps remain. Many studies rely on older data, limiting understanding of recent trends and emerging determinants such as urbanisation, climate change impacts on disease risk, and improvements in neonatal care. Few recent studies integrate individual-level factors with community and health system variables, such as quality of neonatal care or district-level malaria incidence, to provide a comprehensive view of child mortality drivers ( 7 , 5 ). Region-specific and longitudinal analyses are limited, hindering the design of targeted interventions. A thorough, current study of the factors influencing under-five mortality in Ghana is crucial in light of this backdrop. More accurate public health interventions will be made possible by taking into account individual, home, community, and health system aspects as well as recent data. Understanding these determinants is crucial for accelerating progress toward SDG 3.2, reducing preventable child deaths, and improving child survival outcomes in Ghana. Therefore, this study was carried out to investigate the prevalence and factors that contribute to under-five mortality in Ghana, with a particular emphasis on maternal health service use and sociodemographic traits. Materials and Methods Study Design Data from the 2022 Ghana Demographic and Health Survey (DHS), a nationally representative household survey that gathers comprehensive data on population, health, and nutrition variables, including maternal and child health outcomes, were secondary analysed for this study. The sample strategy used in the Demographic and Health Survey was two-stage. Enumeration Areas (EAs) were chosen in the first round using data from the Ghana Population and Housing Census of 2021. To guarantee a sufficient number of eligible participants, houses within each selected EA were carefully sampled in the second step. Under-five mortality was examined in connection to sociodemographic traits and maternal health service use using data from women of reproductive age (15–49 years) and their children under five. Study Population and Data Extraction The study population comprised women aged 15–49 years who reported having a live birth within the five years preceding the survey and had complete records on key variables, including sociodemographic characteristics, antenatal care attendance, postnatal care, childhood vaccinations, and breastfeeding status. From the 2022 Ghana Demographic and Health Survey (DHS) dataset, a total of 39,305 women met the inclusion criteria and were included in the analysis. Data extraction focused on variables relevant to under-five mortality, sociodemographic factors, and health service utilisation. Permission to use the data was granted by the DHS Program, and the dataset is publicly accessible at https://dhsprogram.com/Data/ , accessed on November 28, 2025. Clinical trial number: not applicable. This study is a secondary analysis of the 2022 Ghana Demographic and Health Survey (DHS) dataset and does not involve a clinical trial. Study Variables Under-five mortality, or the death of a child before the age of five, served as the primary outcome measure in this investigation. Age (15–19, 20–24, 25–29, 30–34, 35–49 years), marital status (never in union, married, living with partner, widowed, divorced, separated), place of residence (urban, rural), education level (no education, primary, secondary, higher), wealth index (poorest, poorer, middle, richer, richest), and region were among the independent variables. Health service utilisation factors included antenatal care (ANC) visits categorised as inadequate versus adequate, entries in pregnancy and postnatal care rosters (none, single, 2–3, 4 + entries), entries in immunisation rosters (none, single, 2–3 entries), and current breastfeeding status (yes/no). To ensure the robustness of the analysis, only respondents with complete information for all selected variables were included. This approach minimises bias and ensures that comparisons across sociodemographic categories are valid. Including participants with missing data could lead to unreliable estimates and reduced statistical power, particularly in multivariate analyses where all predictors must be accounted for simultaneously. Data Analysis The sociodemographic traits and health service utilisation of the participants were summarised using descriptive statistics, which were displayed as frequencies and percentages. The prevalence of under-five mortality was also estimated. Bivariate associations between independent variables and under-five mortality were assessed using Pearson’s chi-squared tests. In order to generate adjusted odds ratios (AORs) with 95% confidence intervals (CIs) and account for any confounding by sociodemographic factors, variables with statistically significant relationships at the bivariate level were incorporated into multivariate logistic regression models. The threshold for statistical significance was fixed at p < 0.05. Stata version 17 was used for all statistical analyses. Human Ethics and Consent to Participate declarations: Not applicable. This study used secondary data from the 2022 Ghana Demographic and Health Survey (DHS), which is publicly available and anonymized. Permission to use the dataset was obtained from the DHS Program. No additional ethical approval or participant consent was required. Results Sociodemographic Characteristics of Study Participants The sociodemographic details of the 39,305 women who were part of the study are shown in Table 1 . With a mean age of 36.5 ± 7.6 years, the majority of participants (61.6%) were between the ages of 35 and 49. Only a small proportion (1.2%) were adolescents aged 15–19 years. Most respondents were married (68.0%), while 15.0% were living with a partner. More than half of the participants resided in rural areas (57.1%), compared to 42.9% in urban areas. Regarding educational attainment, 38.2% of the women had no formal education, while only 5.2% had attained higher education. The distribution of participants across wealth quintiles showed that 29.9% were in the poorest category, while the richer and richest groups accounted for 15.2% and 11.4%, respectively. Regional representation of participants was broad and nationally reflective, with the highest proportions drawn from the Northern Region (8.8%), Oti Region (6.9%), Savannah Region (7.6%), and North East Region (7.2%). Table 1 Sociodemographic Characteristics of Study Participants Variables Frequency (N = 39,305) Percent (%) Age group (years) 15–19 464 1.2 20–24 2,464 6.3 25–29 4,782 12.2 30–34 7,359 18.7 35–49 24,236 61.6 Mean age (36.5 ± 7.6) Marital Status Never in union 1,957 5.0 Married 26,772 68.0 Living with a partner 5,876 15.0 Widowed 1,499 3.8 Divorced 1,201 3.1 Separated 2,000 5.1 Residence Urban 16,871 42.9 Rural 22,434 57.1 Education Level No education 14,995 38.2 Primary 6,914 17.6 Secondary 15,357 39.0 Higher 2,039 5.2 Wealth Index Poorest 11,751 29.9 Poorer 9,598 24.4 Middle 7,499 19.1 Richer 5,981 15.2 Richest 4,476 11.4 Region Western 1,984 5.0 Central 2,584 6.6 Greater Accra 2,131 5.4 Volta 2,037 5.2 Eastern 2,282 5.8 Ashanti 2,912 7.4 Western North 2,094 5.3 Ahafo 2,262 5.7 Bono 1,874 4.8 Bono East 2,561 6.5 Oti 2,711 6.9 Northern 3,451 8.8 Savannah 2,966 7.6 North East 2,835 7.2 Upper East 2,319 5.9 Upper West 2,302 5.9 Prevalence of Under-Five Mortality The distribution of under-five mortality among the 39,305 research participants is shown in Fig. 1 . The majority of mothers (74.8%) reported no under-five child death, while 25.2% had experienced the death of at least one child before the age of five. Thus, approximately one in four women in the sample had encountered under-five mortality, highlighting a substantial burden of child deaths within the population. Sociodemographic Factors Associated with Under-Five Mortality The bivariate analysis of the relationship between sociodemographic traits and under-five mortality among the 39,305 research participants is shown in Table 2 . Variations in under-five mortality were statistically significant for every sociodemographic variable examined. Table 2 Bivariate Analysis of Sociodemographic Factors Associated with Under-Five Mortality Under-Five Mortality Variables Alive < 5 years N (%) Died < 5 years N (%) Chi-Square (χ²) (p-Value) Age group (years) 15–19 439 (94.6) 25 (5.4) 20–24 2,281 (92.6) 183 (7.4) 25–29 4,247 (88.8) 535 (11.2) 1,800.00 < 0.001* 30–34 5,961 (81.0) 1,398 (19.0) 35–49 16,472 (68.0) 7,764 (32.0) Marital Status Never in union 1,761 (90.0) 196 (10.0) Married 19,879 (74.3) 6,893 (25.8) Living with a partner 4,373 (74.4) 1,503 (25.6) 305.78 < 0.001* Widowed 993 (66.2) 506 (33.8) Divorced 876 (72.9) 325 (27.1) Separated 1,518 (75.9) 482 (24.1) Place of Residence Urban 13,158 (78.0) 3,713 (22.0) 159.79 < 0.001* Rural 16,242 (72.4) 6,192 (27.6) Education Level No education 9,905 (66.1) 5,090 (33.9) Primary 4,844 (70.1) 2,070 (29.9) 1,600.00 < 0.001* Secondary 12,755 (83.1) 2,602 (16.9) Higher 1,896 (93.0) 143 (7.0) Wealth Index Poorest 8,114 (69.1) 3,637 (30.9) Poorer 6,882 (71.7) 2,716 (28.3) Middle 5,771 (77.0) 1,728 (23.0) 770.66 < 0.001* Richer 4,657 (77.9) 1,324 (22.1) Richest 3,976 (88.8) 500 (11.2) Region Western 1,451 (73.1) 533 (26.9) Central 1,919 (74.3) 665 (25.7) Greater Accra 1,796 (84.3) 335 (15.7) Volta 1,582 (77.7) 455 (22.3) Eastern 1,761 (77.2) 521 (22.8) Ashanti 2,295 (78.8) 617 (21.2) Western North 1,654 (79.0) 440 (21.0) Ahafo 1,836 (81.2) 426 (18.8) 642.04 < 0.001* Bono 1,535 (81.9) 339 (18.1) Bono East 1,892 (73.9) 669 (26.1) Oti 1,730 (63.8) 981 (36.2) Northern 2,283 (66.2) 1,168 (33.8) Savannah 2,045 (69.0) 921 (31.0) North East 2,168 (76.5) 667 (23.5) Upper East 1,776 (76.6) 543 (23.4) Upper West 1,677 (72.9) 625 (27.1) *Significant at p < 0.05 Table 3 summarises the unadjusted and adjusted logistic regression results for sociodemographic determinants of under-five mortality. Following adjustment for potential confounders, maternal age remained a significant predictor. Relative to mothers aged 15–19 years, the likelihood of experiencing an under-five death increased steadily with advancing age, with the greatest risk observed among mothers aged 35–49 years (AOR = 7.66, 95% CI: 5.07–11.56, p < 0.001). Marital status also showed significant associations after adjustment. Women living with a partner (AOR = 1.60, p < 0.001), widowed (AOR = 1.56, p < 0.001), divorced (AOR = 1.37, p = 0.003), separated (AOR = 1.38, p = 0.001), and married women (AOR = 1.32, 95% CI: 1.12–1.55, p = 0.001) all had higher odds of under-five mortality compared to women who had never been in union. Educational attainment displayed a protective pattern. Although the association for primary education was not significant after adjustment (AOR = 1.02, p = 0.488), women with secondary (AOR = 0.60, 95% CI: 0.56–0.64, p < 0.001) and higher education (AOR = 0.29, p < 0.001) had significantly lower odds of under-five mortality compared to those without any education. Household wealth followed a clear gradient, with increasing wealth associated with decreased odds of child mortality. The risk of under-five mortality was 58% lower for mothers in the wealthiest families than for those in the lowest (AOR = 0.42, 95% CI: 0.37–0.48, p < 0.001). Place of residence had no statistically significant effect in the adjusted model after adjusting for other sociodemographic variables (AOR = 0.95, p = 0.086). Significant regional disparities persisted in the adjusted model. The Central, Greater Accra, Volta, Eastern, Ashanti, Western North, Ahafo, Bono, Bono East, North East, Upper East, and Upper West regions have lower odds of under-five mortality than the Western Region. However, the Oti and Northern regions did not show significant associations after adjustment, although they were significant in crude models. The multivariate findings highlight maternal age, marital status, education level, household wealth, and region as independent predictors of under-five mortality in Ghana, underscoring persistent inequalities in child survival across sociodemographic groups. Table 3 Logistic Regression Analysis of Sociodemographic Factors Associated with Under-Five Mortality Variables COR (95% CI) (p-Value) AOR (95% CI) (p-Value) Age group (years) 15–19 Ref Ref 20–24 1.41 (0.92–2.17) 0.118 1.38 (0.90–2.14) 0.144 25–29 2.21 (1.46–3.34) < 0.001* 2.21 (1.45–3.36) < 0.001* 30–34 4.12 (2.74–6.19) < 0.001* 3.98 (2.63–6.02) < 0.001* 35–49 8.28 (5.53–12.40) < 0.001* 7.66 (5.07–11.56) < 0.001* Marital status Never in union Ref Ref Married 3.12 (2.68–3.62) < 0.001* 1.32 (1.12–1.55) 0.001* Living with a partner 3.09 (2.63–3.62) < 0.001* 1.60 (1.35–1.89) < 0.001* Widowed 4.58 (3.82–5.49) < 0.001* 1.56 (1.29–1.90) < 0.001* Divorced 3.33 (2.74–4.05) < 0.001* 1.37 (1.12–1.69) 0.003* No longer living together/separated 2.85 (2.38–3.41) < 0.001* 1.38 (1.14–1.67) 0.001* Education level No education Ref Ref Primary 0.83 (0.78–0.88) < 0.001* 1.02 (0.96–1.10) 0.488 Secondary 0.40 (0.38–0.42) < 0.001* 0.60 (0.56–0.64) < 0.001* Higher 0.15 (0.12–0.17) < 0.001* 0.29 (0.24–0.35) < 0.001* Wealth index Poorest Ref Ref Poorer 0.88 (0.83–0.93) < 0.001* 0.88 (0.82–0.94) < 0.001* Middle 0.67 (0.63–0.71) < 0.001* 0.75 (0.69–0.81) < 0.001* Richer 0.63 (0.59–0.68) < 0.001* 0.80 (0.72–0.88) < 0.001* Richest 0.28 (0.25–0.31) < 0.001* 0.42 (0.37–0.48) < 0.001* Place of residence Urban Ref Ref Rural 1.35 (1.29–1.42) < 0.001* 0.95 (0.89–1.01) 0.086 Region Western Ref Ref Central 0.94 (0.83–1.08) 0.390 0.82 (0.72–0.95) 0.007* Greater Accra 0.51 (0.44–0.59) < 0.001* 0.56 (0.48–0.66) < 0.001* Volta 0.78 (0.68–0.90) 0.001* 0.61 (0.53–0.71) < 0.001* Eastern 0.81 (0.70–0.93) 0.002* 0.71 (0.61–0.82) < 0.001* Ashanti 0.73 (0.64–0.84) < 0.001* 0.67 (0.58–0.77) < 0.001* Western North 0.72 (0.63–0.84) < 0.001* 0.55 (0.47–0.64) < 0.001* Ahafo 0.63 (0.55–0.73) < 0.001* 0.46 (0.39–0.53) < 0.001* Bono 0.60 (0.52–0.70) < 0.001* 0.51 (0.43–0.60) < 0.001* Bono East 0.96 (0.84–1.10) 0.574 0.68 (0.59–0.79) < 0.001* Oti 1.54 (1.36–1.75) < 0.001* 1.04 (0.91–1.19) 0.555 Northern 1.39 (1.23–1.57) < 0.001* 0.92 (0.80–1.06) 0.240 Savannah 1.23 (1.08–1.39) 0.002* 0.79 (0.69–0.91) 0.001* North East 0.84 (0.73–0.96) 0.008* 0.53 (0.45–0.61) < 0.001* Upper East 0.83 (0.72–0.96) 0.009* 0.60 (0.52–0.70) < 0.001* Upper West 1.01 (0.89–1.16) 0.834 0.67 (0.58–0.78) < 0.001* *Significant at p < 0.05 Health Service Utilisation Factors Associated to Mortality in Children Under Five The bivariate relationships between health service usage characteristics and under-five mortality among the 39,305 women who were part of the study are shown in Table 4 . Several health service indicators demonstrated statistically significant relationships with under-five mortality. Under-five mortality was significantly associated with maternal health service utilisation. ANC attendance was linked to child survival (χ² = 7.44, p = 0.006), with mothers having inadequate ANC visits showing a lower proportion of under-five deaths (20.7%) compared with those receiving adequate ANC (25.3%). Postnatal care roster entries were also significant (χ² = 238.92, p < 0.001); mothers with no documented entries had the highest under-five mortality (28.5%), those with 1 entry (21.8%) and 2–3 entries (22.6%), while 4 or more entries recorded the highest mortality (47.3%), reflecting high-risk pregnancies. Immunisation entries were strongly associated with mortality (χ² = 377.84, p < 0.001), with children having no entries at the highest risk (28.9%), 1 entry (21.3%), and 2–3 entries the lowest (15.9%). Exclusive breastfeeding was also significantly protective (χ² = 216.39, p < 0.001); under-five mortality was higher among children not exclusively breastfed (27.3%) compared with those who were exclusively breastfed (20.3%). Overall, these findings highlight that maternal and child health service utilisation, including ANC, postnatal care, immunisation, and exclusive breastfeeding, plays a critical role in under-five survival in Ghana. Table 4 Bivariate Analysis of Health Service Utilisation Factors Associated with Under-Five Mortality (N = 39,305) Under-Five Mortality Variables Alive < 5 years N (%) Died < 5 years N (%) Chi-Square (χ²) (p-Value) ANC Visit Inadequate 530 (79.3) 138 (20.7) 7.44 0.006* Adequate 28,870 (74.7) 9,767 (25.3) Entries in Pregnancy and Postnatal Care Roster No entries 13,865 (71.5) 5,523 (28.5) Single entry 12,510 (78.2) 3,483 (21.8) 238.92 < 0.001* 2–3 entries 2,996 (77.4) 873 (22.6) 4 + entries 29 (52.7) 26 (47.3) Entries in Immunisation Roster No entries 15,450 (71.1) 6,275 (28.9) Single entry 12,195 (78.7) 3,298 (21.3) 377.84 < 0.001* 2–3 entries 1,755 (84.1) 332 (15.9) Exclusive breastfeeding No 19,991 (72.7) 7,511 (27.3) 216.39 < 0.001* Yes 9,409 (79.7) 2,394 (20.3) *Significant at p < 0.05 The findings of the bivariate and multivariate logistic regression studies looking at the connection between under-five mortality and health service use are shown in Table 5 . Adequate ANC visits were linked to increased chances of under-five mortality in the crude model (COR = 1.30, 95% CI: 1.08–1.57; p = 0.007). However, after controlling for confounders, this connection weakened and lost statistical significance (AOR = 0.83, 95% CI: 0.68–1.02; p = 0.075). Entries in the pregnancy and postnatal care roster showed a strong and consistent association with under-five mortality. Although the adjusted analysis showed significantly higher risks of under-five mortality (AOR = 1.67, 95% CI: 1.51–1.86; p < 0.001), women with a single entry had lower crude odds (COR = 0.70, 95% CI: 0.67–0.73; p < 0.001) than mothers without entries. The likelihood of under-five mortality increased monotonically with more entries, with mothers having four or more entries showing the highest adjusted odds (AOR = 12.57, 95% CI: 6.68–23.65; p < 0.001). Similarly, entries in the immunisation roster were protective against under-five mortality. Children with single or 2–3 entries had significantly lower odds in both crude and adjusted analyses. For instance, in the adjusted model, children with two to three entries had odds that were 77% lower (AOR = 0.23, 95% CI: 0.19–0.28; p < 0.001). Furthermore, compared to non-nursing mothers, breastfeeding mothers had a 15% decreased adjusted risk of under-five mortality (AOR = 0.85, 95% CI: 0.79–0.93; p < 0.001). Table 5 Logistic Regression Analysis of Health Service Utilisation and Sociodemographic Factors Associated with Under-Five Mortality Variables COR (95% CI) (p-Value) AOR (95% CI) (p-Value) ANC Visit Inadequate Ref Ref Adequate 1.30 (1.08–1.57) 0.007* 0.83 (0.68–1.02) 0.075 Entries in Pregnancy and Postnatal Care Roster No entries Ref Ref Single entry 0.70 (0.67–0.73) < 0.001* 1.67 (1.51–1.86) < 0.001* 2–3 entries 0.73 (0.67–0.79) < 0.001* 3.49 (3.03–4.01) < 0.001* 4 + entries 2.25 (1.32–3.82) < 0.001* 12.57 (6.68–23.65) < 0.001* Entries in Immunisation Roster No entries Ref Ref Single entry 0.57 (0.51–0.64) < 0.001* 0.57 (0.51–0.64) < 0.001* 2–3 entries 0.47 (0.41–0.53) < 0.001* 0.23 (0.19–0.28) < 0.001* Exclusive breastfeeding No Ref Ref Yes 0.68 (0.64–0.71) < 0.001* 0.85 (0.79–0.93) < 0.001* *Significant at p < 0.05 Discussions Sociodemographic Factors Associated with Under-Five Mortality The findings of this study add to the body of information on sociodemographic drivers of under-five mortality in Ghana and highlight the persistence of child survival disparities associated with maternal, household, and contextual factors. The complex character of child mortality was highlighted by the significant variables that included maternal age, educational achievement, marital status, family affluence, and geographic location. Previous research has documented similar trends, such as Sarkodie ( 6 ), who emphasised the need for targeted interventions in rural areas and identified maternal age, wealth, and education as important factors influencing child survival. Likewise, Aheto ( 7 ) emphasised the role of maternal education and family planning in reducing under-five mortality, supporting the protective influence of higher educational attainment observed in the present analysis. The results of Kanmiki et al. ( 10 ), who found that women aged 35 to 49 had noticeably greater odds of dying before the age of five, are in line with the substantial correlation between advanced maternal age and increased risk of child mortality. This relationship may be partly attributable to biological risks associated with later pregnancies, including complications such as preterm delivery and low birthweight. In addition, older mothers may experience cumulative socioeconomic pressures, including caregiving responsibilities for multiple children or constrained access to timely healthcare, which could further compromise child survival. Maternal education emerged as a particularly strong protective factor. Educated mothers are more likely to possess the knowledge and skills necessary to adopt optimal childcare practices, including appropriate nutrition, hygiene, immunisation, and timely healthcare-seeking. Household wealth similarly reduced the likelihood of under-five mortality, likely by improving access to quality health services, nutritious foods, and safer living environments. Preventive practices such as exclusive breastfeeding and immunisation also demonstrated protective effects, reinforcing their role in strengthening immunity and reducing vulnerability to infectious diseases, which remain leading causes of child deaths in Ghana. Marital status was another important determinant, with women in certain marital categories experiencing higher risks of under-five mortality. This may reflect variations in economic security, emotional support, and caregiving capacity across household arrangements, particularly among widowed, separated, or cohabiting women who may face greater stress or resource constraints. Marked regional disparities in under-five mortality were also evident, particularly in northern and rural regions. These patterns mirror findings by Mohammed et al. ( 5 ) and Arku et al. ( 11 ), who attributed higher mortality in northern Ghana to weaker health infrastructure, environmental risks, and limited access to essential services. Although place of residence lost statistical significance after adjustment in the current study, this contrasts with some earlier research ( 6 ) and suggests that socioeconomic and maternal characteristics may mediate much of the observed urban–rural variation. Environmental factors, especially the availability of safe water sources and adequate sanitation facilities, were also found to be significant. Poor water quality and inadequate sanitation increase exposure to diarrhoeal and hygiene-related infections, which are major contributors to under-five mortality. This result is in line with research by Nyaaba et al. ( 8 ) and Fenta et al. ( 12 ), which showed that increased usage of clean energy, water, and sanitation significantly lowers child mortality in sub-Saharan Africa. Cleaner household environments reduce exposure to waterborne pathogens and indoor air pollution, thereby lowering the risk of both gastrointestinal and respiratory illnesses. The protective effect of household wealth observed in this study aligns with prior evidence ( 7 , 13 ), highlighting how broader socioeconomic conditions shape child health outcomes. Wealthier households are better able to maintain clean living circumstances, obtain timely medical attention, and secure sufficient nutrition, all of which promote child survival. Overall, the results support the theory that interrelated sociodemographic, environmental, and geographical factors are responsible for under-five mortality in Ghana. In order to address these issues, comprehensive interventions are needed that prioritise resource allocation to disadvantaged areas, delay high-risk childbearing, enhance household living conditions, provide access to clean water and sanitation, and support maternal education. In order to reduce avoidable child deaths in Ghana and accelerate progress toward Sustainable Development Goal 3.2, such a comprehensive approach is crucial. Health Service Utilisation Factors Associated to Mortality in Children Under Five The substantial associations between prenatal care (ANC), postnatal care, immunisation, and breastfeeding and child survival demonstrate the importance of health service usage determinants in Ghana's under-five mortality. The observed counterintuitive finding that mothers with adequate ANC visits had higher unadjusted under-five mortality likely reflects confounding by high-risk pregnancies, a pattern also noted in other studies, emphasising the complexity of interpreting ANC utilisation data ( 14 ). This is consistent with the findings of Guynn et al. ( 15 ), who showed that community-based interventions such as the Health-2-Go program considerably lower child mortality by enhancing access to healthcare, especially in remote and difficult-to-reach areas. This suggests that the context and quality of care are just as crucial as the frequency of utilisation. Immunisation uptake showed a strong protective effect against under-five mortality, consistent with Alhassan et al. ( 17 ), who reported positive correlations between immunisation coverage and child survival in Ghana’s Volta region. Children who are fully or partially immunised have a lower risk of dying because vaccines protect them from potentially deadly infectious diseases including measles, polio, and pneumonia, which are still leading causes of death for children under five in low- and middle-income countries. Immunised children are therefore more resilient to preventable infections, and mothers who ensure immunisation may also be more engaged with healthcare services, further improving child survival. Similarly, breastfeeding demonstrated a protective role, in line with Kolekang et al. ( 14 ), who found that early initiation and sustained breastfeeding significantly reduce child mortality risk. Breastfeeding reduces mortality because it provides infants with essential nutrients and antibodies that strengthen immunity and protect against common infections like diarrhoea and respiratory illnesses. Additionally, limiting exposure to tainted food or water a major source of infections in young children during the first six months of life is achieved through exclusive nursing. Moreover, sustained breastfeeding supports growth and development, improving overall health and survival prospects during the vulnerable early years. These results underscore the need to strengthen comprehensive maternal and child health services across the full continuum of care, as supported by Ahmed et al. ( 18 ), who highlighted that disruptions in essential health services during the COVID-19 pandemic led to increased child mortality in low- and middle-income countries, including Ghana. Strengths and limitations Strengths The results of this study can be applied to Ghanaian women of reproductive age since it used data from the 2022 Ghana Demographic and Health Survey, which used reliable and standardised data gathering techniques and is nationally representative. The large sample size ensured sufficient statistical power to identify meaningful relationships between sociodemographic characteristics, maternal healthcare utilisation, and under-five mortality. By employing multivariate logistic regression, the study accounted for potential confounding factors, enhancing the reliability of the observed risk and protective associations. Moreover, the analysis included various maternal and markers of child health, such as immunisation coverage and exclusive breastfeeding, providing a thorough evaluation of factors affecting child survival. Limitations Since it is impossible to determine the temporal order or direction of relationships between explanatory variables and under-five mortality, the cross-sectional nature of the DHS data restricts the ability to draw conclusions about causality. In addition, the study depended on respondents’ self-reported information, which may be affected by recall errors, particularly for sensitive events such as child deaths and patterns of health service use. The scope of the analysis was further constrained by the variables included in the DHS, limiting assessment of important influences such as the quality of healthcare delivery, maternal nutritional status, and environmental conditions. Moreover, exclusive breastfeeding was assessed using reported practices at the time of the survey rather than through longitudinal observation, which may not accurately reflect continued adherence to exclusive breastfeeding over the recommended period. Conclusion Given that a significant portion of women had lost a child before the child turned five, this study shows that under-five mortality is still a major public health issue in Ghana. Despite ongoing national and worldwide efforts to increase child survival, the findings demonstrate that mortality risks remain unevenly distributed among demographic groups. The intricate interaction between maternal and child health service usage and sociodemographic traits shapes child survival in Ghana, highlighting the multidimensional nature of under-five mortality. Older maternal age emerged as a significant risk factor, likely reflecting the cumulative biological, obstetric, and socioeconomic vulnerabilities associated with later childbearing, including higher prevalence of pregnancy complications and chronic health conditions. Marital disruption and lower household wealth were also associated with increased mortality risk, suggesting that reduced social support and financial constraints may limit access to timely healthcare, adequate nutrition, and safe living conditions for children. In contrast, higher maternal education and improved household wealth were consistently protective, highlighting the role of education in enhancing health knowledge, care-seeking behaviour, and the ability to navigate health systems, as well as the importance of economic resources in securing better living environments and healthcare access. Health service–related factors played a crucial protective role. Immunisation uptake and exclusive breastfeeding were strongly associated with reduced under-five mortality, reflecting their effectiveness in preventing infectious diseases, strengthening immunity, and supporting optimal child growth and development. However, persistent regional disparities point to underlying inequities in health system capacity, availability of skilled health personnel, infrastructure, and service quality across different parts of the country. These geographic inequalities suggest that national averages may mask substantial subnational gaps in child survival outcomes. Collectively, the findings indicate that further reductions in under-five mortality in Ghana cannot be achieved through healthcare coverage expansion alone. Strengthening female education and economic empowerment is essential for improving maternal autonomy, health literacy, and sustained engagement with health services. At the same time, targeted investments in underserved regions are required to improve health infrastructure, service delivery, and continuity of care. Expanding immunisation outreach and reinforcing sustained breastfeeding support through integrated maternal, newborn, and child health services remain central to preventing avoidable child deaths. In the end, achieving Sustainable Development Goal 3.2 more quickly and guaranteeing fair increases in child survival throughout Ghana require a concerted, multisectoral strategy that incorporates social protection, education, and responsive health systems. List of Abbreviations ANC Antenatal Care AOR Adjusted Odds Ratio CI Confidence Interval COR Crude Odds Ratio DHS Demographic and Health Survey GDHS Ghana Demographic and Health Survey GHS Ghana Health Service GSS Ghana Statistical Service SDG Sustainable Development Goal U5MR Under‑Five Mortality Rate Declarations Institutional Review Board Statement: The DHS Program granted permission to access the Maternal Health Survey data after a written request outlining the goals and parameters of the study was submitted. The anonymised dataset was only available to the research team, and anonymity was rigorously maintained in accordance with DHS data usage guidelines. Ethics approval and consent to participate: Human Ethics and Consent to Participate declarations: not applicable. Consent for publication: Not applicable. Data Availability Statement: With permission from the DHS program, data were collected from the program and are accessible at https://dhsprogram.com/Data/, viewed on November 28, 2025. Acknowledgements: The authors would like to express their profound gratitude to the DHS for granting them access to the DHS dataset used in this investigation. We also thank the institutions and colleagues who helped make this research feasible. Trial registration : Not applicable. Author Contributions: SA developed the concept, organised the research, and penned the paper. JKG edited the manuscript, helped analyse the data, and critically evaluated the study design. RD and MPA-B evaluated draft versions and provided methodological guidance. Important information about text rewriting and content validation was provided by OUL, AMK, and MAR. All authors read, reviewed, and approved the final version of the work. Funding: The authors provided all of the funding for the study. Conflicts of Interest: No conflicts of interest are disclosed by the authors. References World Health Organisation. Trends in maternal mortality 2000 to 2020: estimates by WHO, UNICEF, UNFPA, World Bank Group and UNDESA/Population Division. World Health Organisation; 2023. Kallah-Dagadu G, Donkor F, Duah M, Yeboah H, Arku D, Lotsi A. Investigation of Factors Influencing Infant Mortality at Greater Accra Regional Hospital, Ghana. Biomed Res Int. 2024;2024(1):6610617. Adja-Sai C, Zakariah S, Owusu-Sekyere F. (2024). PP326 Topic: AS09–Global Health/Resource Limited Setting/Health Inequalities/Impact of Global Warming/Other: A THREE-YEAR OVERVIEW OF UNDER-FIVE MORTALITY AT REBECCA AKUFO ADDO PAEDIATRIC INTENSIVE CARE UNIT/HIGH DEPENDENCY UNIT (RA-PICU/HDU). Pediatr Crit Care Med, 25(11S), e102. Adama ZK, Mettle FO, Baiden BM, Bii NK. Forecasting progress: analysing the trajectory of under-five child mortality for Ghana, Niger, Nigeria, and Sierra Leone towards SDG3 using ARIMA time series model. BMC Public Health. 2025;25(1):1607. Mohammed K, Abubakari AR, Amoak D, Antabe R, Luginaah I. (2023). Geographic disparities in the time to under-five mortality in Ghana. PLoS ONE, 18(9), e0291328. Sarkodie AO. Factors influencing under-five mortality in rural-urban Ghana: An applied survival analysis. Soc Sci Med. 2021;284:114185. Aheto JMK. Predictive model and determinants of under-five child mortality: evidence from the 2014 Ghana demographic and health survey. BMC Public Health. 2019;19(1):64. Nyaaba AA, Tanle A, Dadzie LK, Ayamga M. Determinants of Under-Five Mortality in Ghana: Evidence from the Ghana Demographic and Health Survey. Int J Translational Med Res Public Health. 2020;4(2):1–11. Touré S, Weeks J, Lopez-Carr D, Stow D. Evaluating links between dynamic urban landscapes and under-five child mortality in Accra, Ghana. Demographic Res. 2020;42:589–614. Kanmiki EW, Bawah AA, Agorinya I, Achana FS, Awoonor-Williams JK, Oduro AR, Akazili J. Socio-economic and demographic determinants of under-five mortality in rural northern Ghana. BMC Int health Hum rights. 2014;14(1):24. Arku RE, Bennett JE, Castro MC, Agyeman-Duah K, Mintah SE, Ware JH, Ezzati M. Geographical inequalities and social and environmental risk factors for under-five mortality in Ghana in 2000 and 2010: Bayesian spatial analysis of census data. PLoS Med. 2016;13(6):e1002038. Fenta HM, Chen D-G, Zewotir T, Rad NN. Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countries. Front Public Health. 2025;13:101234. Nasejje JB, Mbuvha R, Mwambi H. (2022). Use of a deep learning and random forest approach to track changes in the predictive nature of socioeconomic drivers of under-5 mortality rates in sub-Saharan Africa. BMJ open, 12(2), e049786. Kolekang A, Sarfo B, Danso-Appiah A, Dwomoh D, Akweongo P. Are maternal and child health initiatives helping to reduce under-five mortality in Ghana? Results of a quasi-experimental study using coarsened exact matching. BMC Pediatr. 2021;21(1):473. Guynn I, Lich KH, Manortey S, Frerichs L, Mansfield AJ, Shaibu M, Alder SC. (2025). The ‘Health-2-Go’programme’s impact on all-cause mortality and clinic utilisation for children 5 and under: a retrospective cohort analysis of an iCCM intervention in Ghana’s Barekese Subdistrict. BMJ Global Health, 10 (3). Alhassan AR. Under-Five Mortality in Ghana: Prevalence and Socioeconomic Predictors. SSRN Electron. J; 2021. Alhassan RK, Owusu-Agyei S, Ansah EK, Gyapong M, Ashinyo A, Ashinyo ME, Ekpor E. Trends and correlates of maternal, newborn and child health services utilisation in primary healthcare facilities: an explorative ecological study using DHIMSII data from one district in the Volta region of Ghana. BMC Pregnancy Childbirth. 2020;20(1):543. Ahmed T, Roberton T, Vergeer P, Hansen PM, Peters MA, Ofosu AA, Shapira G. Healthcare utilisation and maternal and child mortality during the COVID-19 pandemic in 18 low-and middle-income countries: An interrupted time-series analysis with mathematical modelling of administrative data. PLoS Med. 2022;19(8):e1004070. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board 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-8841953","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":600866812,"identity":"53f71a5e-d554-4055-848e-a3eee262f1c3","order_by":0,"name":"Samuel Antwi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYBADHjb2/ocPQAw+4jQkAFXynGE2AOslVguDnIQPmwSITVCLfPvpxM+FPw7LsEnwHqv8mmMnw8bA/PDRDTxaDM7kbpaekXCYh026L+227LZkoMPYjI1z8GlhyN0gzZNwm4dN5oDZbcltzEAtQO34tMj3v938G6xFIsGsWHJbPWEtDDdyt0FskcgxY/y47TBhLQY33m6z5kn7z8PGcyxZmnHbcR42ZgJ+ke/P3XybxybNXr69+eDHn9uq7fnZmx8+xuswZMDMAyaJVQ4CjD9IUT0KRsEoGAUjBgAAF1RB/X3X5pAAAAAASUVORK5CYII=","orcid":"","institution":"University of Ghana","correspondingAuthor":true,"prefix":"","firstName":"Samuel","middleName":"","lastName":"Antwi","suffix":""},{"id":600866813,"identity":"4fe04a95-7d7d-4a44-afda-d82b3bd4823b","order_by":1,"name":"John Kuumuori Ganle","email":"","orcid":"","institution":"University of Ghana","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"Kuumuori","lastName":"Ganle","suffix":""},{"id":600866814,"identity":"bd0ac36f-bb3c-4cf9-9939-0dac45fa755c","order_by":2,"name":"Mabel Pokua Amoako-Boateng","email":"","orcid":"","institution":"University of Cape Coast","correspondingAuthor":false,"prefix":"","firstName":"Mabel","middleName":"Pokua","lastName":"Amoako-Boateng","suffix":""},{"id":600866815,"identity":"7cd12610-ebbf-47b2-aecc-114b88a68f48","order_by":3,"name":"Ross Denkyi","email":"","orcid":"","institution":"University of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Ross","middleName":"","lastName":"Denkyi","suffix":""},{"id":600866816,"identity":"f9a3b497-5c5c-4c00-97fc-2a5b11532cdc","order_by":4,"name":"Obed Uwumbornyi Lasim","email":"","orcid":"","institution":"University of Cape Coast","correspondingAuthor":false,"prefix":"","firstName":"Obed","middleName":"Uwumbornyi","lastName":"Lasim","suffix":""},{"id":600866817,"identity":"689728bc-3d5c-41c6-9947-34cc9c5b2635","order_by":5,"name":"Agnes Millicent Kotoh","email":"","orcid":"","institution":"University of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Agnes","middleName":"Millicent","lastName":"Kotoh","suffix":""},{"id":600866818,"identity":"ffb89df5-c247-4e93-91ab-85c86be6c091","order_by":6,"name":"Muniratu Abdul Razak","email":"","orcid":"","institution":"University of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Muniratu","middleName":"Abdul","lastName":"Razak","suffix":""}],"badges":[],"createdAt":"2026-02-10 14:10:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8841953/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8841953/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104181744,"identity":"1fd0b5c3-ac5c-4bb6-9bf2-377895321a2c","added_by":"auto","created_at":"2026-03-08 17:29:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36731,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of Under-Five Mortality, 2022 DHS\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"PrevalenceUnderFive.png","url":"https://assets-eu.researchsquare.com/files/rs-8841953/v1/e2e0c4ca8455a00dff3790d3.png"},{"id":107182822,"identity":"789203cd-8f64-47bc-84fc-fdcf7f5bbdd6","added_by":"auto","created_at":"2026-04-17 17:55:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1224765,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8841953/v1/f5de5c6b-43eb-4b97-80a5-bbb3b07620bf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Determinants of Child Under-Five Mortality in Ghana: Analysis of the 2022 DHS Survey","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDespite significant progress in recent decades, child mortality under five remains a significant global public health concern. The global death rate decreased to 37 per 1,000 live births in 2023 from 94 per 1,000 live births in 1990. Nevertheless, 4.8\u0026nbsp;million children under five died in 2023, many of them from diseases that could have been prevented or cured (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In low- and middle-income nations, where socioeconomic disparities and health system issues still pose a threat to child survival, this burden is especially great. A disproportionate amount of this death occurs in Sub-Saharan Africa, mostly as a result of avoidable causes such infectious illnesses (malaria, pneumonia, and diarrhoea), difficult deliveries, and inadequate care for mothers and newborns (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Achieving Sustainable Development Goal 3.2, which calls for a U5MR of at least 25 per 1,000 live births by 2030, depends on lowering child mortality in this area.\u003c/p\u003e \u003cp\u003eUnder-five mortality in Ghana has steadily decreased; predictions for 2020 show a U5MR of roughly 42\u0026ndash;44 per 1,000 live births (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). According to time series analyses, if current trends continue, the U5MR will be about 30.5 per 1,000 by 2030 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). However, neonatal disorders like preterm, respiratory distress, and sepsis, as well as infectious diseases like malaria, are the leading causes of under-five mortality, which continues to be a significant public health problem (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Regional disparities persist, with children in northern and rural areas at higher risk compared to those in urban and southern regions, reflecting inequalities in healthcare access and socioeconomic status (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Ghanaian studies have identified several factors that influence child mortality. Higher mother education and female child sex are protective against death, whereas multiple births, high parity, and living in certain areas raise the risk, according to analyses of the 2014 Ghana Demographic and Health Survey (GDHS) (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Urban-rural differences remain evident, with children in rural and northern areas experiencing higher mortality, largely influenced by socioeconomic conditions and access to healthcare (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMalaria remains a critical contributor to under-five mortality in Ghana, with spatial analyses showing high malaria burden and district-level variation, particularly in northern regions (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Environmental factors such as access to improved water and sanitation also significantly affect child survival, with children in households using pit toilets or borehole water at higher risk of death (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Socioeconomic predictors, including maternal age, birth spacing, and health insurance coverage, further influence mortality outcomes (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite these insights, significant gaps remain. Many studies rely on older data, limiting understanding of recent trends and emerging determinants such as urbanisation, climate change impacts on disease risk, and improvements in neonatal care. Few recent studies integrate individual-level factors with community and health system variables, such as quality of neonatal care or district-level malaria incidence, to provide a comprehensive view of child mortality drivers (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Region-specific and longitudinal analyses are limited, hindering the design of targeted interventions. A thorough, current study of the factors influencing under-five mortality in Ghana is crucial in light of this backdrop. More accurate public health interventions will be made possible by taking into account individual, home, community, and health system aspects as well as recent data. Understanding these determinants is crucial for accelerating progress toward SDG 3.2, reducing preventable child deaths, and improving child survival outcomes in Ghana. Therefore, this study was carried out to investigate the prevalence and factors that contribute to under-five mortality in Ghana, with a particular emphasis on maternal health service use and sociodemographic traits.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eData from the 2022 Ghana Demographic and Health Survey (DHS), a nationally representative household survey that gathers comprehensive data on population, health, and nutrition variables, including maternal and child health outcomes, were secondary analysed for this study. The sample strategy used in the Demographic and Health Survey was two-stage. Enumeration Areas (EAs) were chosen in the first round using data from the Ghana Population and Housing Census of 2021. To guarantee a sufficient number of eligible participants, houses within each selected EA were carefully sampled in the second step. Under-five mortality was examined in connection to sociodemographic traits and maternal health service use using data from women of reproductive age (15\u0026ndash;49 years) and their children under five.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population and Data Extraction\u003c/h3\u003e\n\u003cp\u003eThe study population comprised women aged 15\u0026ndash;49 years who reported having a live birth within the five years preceding the survey and had complete records on key variables, including sociodemographic characteristics, antenatal care attendance, postnatal care, childhood vaccinations, and breastfeeding status. From the 2022 Ghana Demographic and Health Survey (DHS) dataset, a total of 39,305 women met the inclusion criteria and were included in the analysis. Data extraction focused on variables relevant to under-five mortality, sociodemographic factors, and health service utilisation. Permission to use the data was granted by the DHS Program, and the dataset is publicly accessible at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dhsprogram.com/Data/\u003c/span\u003e\u003cspan address=\"https://dhsprogram.com/Data/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, accessed on November 28, 2025.\u003c/p\u003e \u003cp\u003e \u003cb\u003eClinical trial number: not applicable.\u003c/b\u003e This study is a secondary analysis of the 2022 Ghana Demographic and Health Survey (DHS) dataset and does not involve a clinical trial.\u003c/p\u003e\n\u003ch3\u003eStudy Variables\u003c/h3\u003e\n\u003cp\u003eUnder-five mortality, or the death of a child before the age of five, served as the primary outcome measure in this investigation. Age (15\u0026ndash;19, 20\u0026ndash;24, 25\u0026ndash;29, 30\u0026ndash;34, 35\u0026ndash;49 years), marital status (never in union, married, living with partner, widowed, divorced, separated), place of residence (urban, rural), education level (no education, primary, secondary, higher), wealth index (poorest, poorer, middle, richer, richest), and region were among the independent variables. Health service utilisation factors included antenatal care (ANC) visits categorised as inadequate versus adequate, entries in pregnancy and postnatal care rosters (none, single, 2\u0026ndash;3, 4\u0026thinsp;+\u0026thinsp;entries), entries in immunisation rosters (none, single, 2\u0026ndash;3 entries), and current breastfeeding status (yes/no). To ensure the robustness of the analysis, only respondents with complete information for all selected variables were included. This approach minimises bias and ensures that comparisons across sociodemographic categories are valid. Including participants with missing data could lead to unreliable estimates and reduced statistical power, particularly in multivariate analyses where all predictors must be accounted for simultaneously.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eThe sociodemographic traits and health service utilisation of the participants were summarised using descriptive statistics, which were displayed as frequencies and percentages. The prevalence of under-five mortality was also estimated. Bivariate associations between independent variables and under-five mortality were assessed using Pearson\u0026rsquo;s chi-squared tests. In order to generate adjusted odds ratios (AORs) with 95% confidence intervals (CIs) and account for any confounding by sociodemographic factors, variables with statistically significant relationships at the bivariate level were incorporated into multivariate logistic regression models. The threshold for statistical significance was fixed at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Stata version 17 was used for all statistical analyses.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHuman Ethics and Consent to Participate declarations: Not applicable.\u003c/b\u003e This study used secondary data from the 2022 Ghana Demographic and Health Survey (DHS), which is publicly available and anonymized. Permission to use the dataset was obtained from the DHS Program. No additional ethical approval or participant consent was required.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic Characteristics of Study Participants\u003c/h2\u003e \u003cp\u003eThe sociodemographic details of the 39,305 women who were part of the study are shown in\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. With a mean age of 36.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6 years, the majority of participants (61.6%) were between the ages of 35 and 49. Only a small proportion (1.2%) were adolescents aged 15\u0026ndash;19 years.\u003c/p\u003e \u003cp\u003eMost respondents were married (68.0%), while 15.0% were living with a partner. More than half of the participants resided in rural areas (57.1%), compared to 42.9% in urban areas.\u003c/p\u003e \u003cp\u003eRegarding educational attainment, 38.2% of the women had no formal education, while only 5.2% had attained higher education. The distribution of participants across wealth quintiles showed that 29.9% were in the poorest category, while the richer and richest groups accounted for 15.2% and 11.4%, respectively.\u003c/p\u003e \u003cp\u003eRegional representation of participants was broad and nationally reflective, with the highest proportions drawn from the Northern Region (8.8%), Oti Region (6.9%), Savannah Region (7.6%), and North East Region (7.2%).\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\u003eSociodemographic Characteristics of Study Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \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 (N\u0026thinsp;=\u0026thinsp;39,305)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\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\u003e464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.2\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.3\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.2\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24,236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean age (36.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever in union\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26,772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with a partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeparated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\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 \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\u003e16,871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.9\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22,434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation Level\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 \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\u003e14,995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.2\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15,357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.0\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth Index\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 \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\u003e11,751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.9\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9,598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.4\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.1\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.2\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.4\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 \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreater Accra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAshanti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAhafo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSavannah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.6\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.9\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 Under-Five Mortality\u003c/h3\u003e\n\u003cp\u003eThe distribution of under-five mortality among the 39,305 research participants is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The majority of mothers (74.8%) reported no under-five child death, while 25.2% had experienced the death of at least one child before the age of five. Thus, approximately one in four women in the sample had encountered under-five mortality, highlighting a substantial burden of child deaths within the population.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eSociodemographic Factors Associated with Under-Five Mortality\u003c/h3\u003e\n\u003cp\u003eThe bivariate analysis of the relationship between sociodemographic traits and under-five mortality among the 39,305 research participants is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Variations in under-five mortality were statistically significant for every sociodemographic variable examined.\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\u003eBivariate Analysis of Sociodemographic Factors Associated with Under-Five Mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnder-Five Mortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlive\u0026thinsp;\u0026lt;\u0026thinsp;5 years\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDied\u0026thinsp;\u0026lt;\u0026thinsp;5 years\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChi-Square (χ\u0026sup2;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e(p-Value)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\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\u003e439 (94.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,281 (92.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e183 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,247 (88.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e535 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,800.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\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\u003e5,961 (81.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,398 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,472 (68.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,764 (32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital 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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever in union\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,761 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e196 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19,879 (74.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,893 (25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with a partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,373 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,503 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e305.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e993 (66.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e506 (33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e876 (72.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e325 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeparated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,518 (75.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e482 (24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003e13,158 (78.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,713 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e159.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\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\u003e16,242 (72.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,192 (27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation Level\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e9,905 (66.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,090 (33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,844 (70.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,070 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,600.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,755 (83.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,602 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,896 (93.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth Index\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003e8,114 (69.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,637 (30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,882 (71.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,716 (28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,771 (77.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,728 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e770.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\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\u003e4,657 (77.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,324 (22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,976 (88.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,451 (73.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e533 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,919 (74.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e665 (25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreater Accra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,796 (84.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e335 (15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,582 (77.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e455 (22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,761 (77.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e521 (22.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAshanti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,295 (78.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e617 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,654 (79.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e440 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAhafo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,836 (81.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e426 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e642.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,535 (81.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e339 (18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,892 (73.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e669 (26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,730 (63.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e981 (36.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,283 (66.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,168 (33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSavannah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,045 (69.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e921 (31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,168 (76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e667 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,776 (76.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e543 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,677 (72.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e625 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003e*Significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarises the unadjusted and adjusted logistic regression results for sociodemographic determinants of under-five mortality. Following adjustment for potential confounders, maternal age remained a significant predictor. Relative to mothers aged 15\u0026ndash;19 years, the likelihood of experiencing an under-five death increased steadily with advancing age, with the greatest risk observed among mothers aged 35\u0026ndash;49 years (AOR\u0026thinsp;=\u0026thinsp;7.66, 95% CI: 5.07\u0026ndash;11.56, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Marital status also showed significant associations after adjustment. Women living with a partner (AOR\u0026thinsp;=\u0026thinsp;1.60, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), widowed (AOR\u0026thinsp;=\u0026thinsp;1.56, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), divorced (AOR\u0026thinsp;=\u0026thinsp;1.37, p\u0026thinsp;=\u0026thinsp;0.003), separated (AOR\u0026thinsp;=\u0026thinsp;1.38, p\u0026thinsp;=\u0026thinsp;0.001), and married women (AOR\u0026thinsp;=\u0026thinsp;1.32, 95% CI: 1.12\u0026ndash;1.55, p\u0026thinsp;=\u0026thinsp;0.001) all had higher odds of under-five mortality compared to women who had never been in union.\u003c/p\u003e \u003cp\u003eEducational attainment displayed a protective pattern. Although the association for primary education was not significant after adjustment (AOR\u0026thinsp;=\u0026thinsp;1.02, p\u0026thinsp;=\u0026thinsp;0.488), women with secondary (AOR\u0026thinsp;=\u0026thinsp;0.60, 95% CI: 0.56\u0026ndash;0.64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and higher education (AOR\u0026thinsp;=\u0026thinsp;0.29, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) had significantly lower odds of under-five mortality compared to those without any education. Household wealth followed a clear gradient, with increasing wealth associated with decreased odds of child mortality. The risk of under-five mortality was 58% lower for mothers in the wealthiest families than for those in the lowest (AOR\u0026thinsp;=\u0026thinsp;0.42, 95% CI: 0.37\u0026ndash;0.48, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Place of residence had no statistically significant effect in the adjusted model after adjusting for other sociodemographic variables (AOR\u0026thinsp;=\u0026thinsp;0.95, p\u0026thinsp;=\u0026thinsp;0.086).\u003c/p\u003e \u003cp\u003eSignificant regional disparities persisted in the adjusted model. The Central, Greater Accra, Volta, Eastern, Ashanti, Western North, Ahafo, Bono, Bono East, North East, Upper East, and Upper West regions have lower odds of under-five mortality than the Western Region. However, the Oti and Northern regions did not show significant associations after adjustment, although they were significant in crude models. The multivariate findings highlight maternal age, marital status, education level, household wealth, and region as independent predictors of under-five mortality in Ghana, underscoring persistent inequalities in child survival across sociodemographic groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic Regression Analysis of Sociodemographic Factors Associated with Under-Five Mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\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\u003eCOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e(p-Value)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e(p-Value)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\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\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41 (0.92\u0026ndash;2.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38 (0.90\u0026ndash;2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.144\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\u003e2.21 (1.46\u0026ndash;3.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.21 (1.45\u0026ndash;3.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\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\u003e4.12 (2.74\u0026ndash;6.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.98 (2.63\u0026ndash;6.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.28 (5.53\u0026ndash;12.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.66 (5.07\u0026ndash;11.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital 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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever in union\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.12 (2.68\u0026ndash;3.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.32 (1.12\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with a partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.09 (2.63\u0026ndash;3.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.60 (1.35\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.58 (3.82\u0026ndash;5.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.56 (1.29\u0026ndash;1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.33 (2.74\u0026ndash;4.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.37 (1.12\u0026ndash;1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo longer living together/separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.85 (2.38\u0026ndash;3.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38 (1.14\u0026ndash;1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83 (0.78\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 (0.96\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.40 (0.38\u0026ndash;0.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60 (0.56\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\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\u003e0.15 (0.12\u0026ndash;0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29 (0.24\u0026ndash;0.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth index\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88 (0.83\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88 (0.82\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\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\u003e0.67 (0.63\u0026ndash;0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75 (0.69\u0026ndash;0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\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\u003e0.63 (0.59\u0026ndash;0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80 (0.72\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\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\u003e0.28 (0.25\u0026ndash;0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.42 (0.37\u0026ndash;0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.35 (1.29\u0026ndash;1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95 (0.89\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.086\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 \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94 (0.83\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82 (0.72\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.007*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreater Accra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.51 (0.44\u0026ndash;0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56 (0.48\u0026ndash;0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.78 (0.68\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61 (0.53\u0026ndash;0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81 (0.70\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.002*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71 (0.61\u0026ndash;0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAshanti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.73 (0.64\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 (0.58\u0026ndash;0.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.72 (0.63\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55 (0.47\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAhafo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.63 (0.55\u0026ndash;0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46 (0.39\u0026ndash;0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60 (0.52\u0026ndash;0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.51 (0.43\u0026ndash;0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96 (0.84\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 (0.59\u0026ndash;0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.54 (1.36\u0026ndash;1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04 (0.91\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.555\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.39 (1.23\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.80\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.240\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSavannah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23 (1.08\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.002*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79 (0.69\u0026ndash;0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\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\u003e0.84 (0.73\u0026ndash;0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.008*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53 (0.45\u0026ndash;0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83 (0.72\u0026ndash;0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.009*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60 (0.52\u0026ndash;0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01 (0.89\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 (0.58\u0026ndash;0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\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 \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e*Significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eHealth Service Utilisation Factors Associated to Mortality in Children Under Five\u003c/h2\u003e \u003cp\u003eThe bivariate relationships between health service usage characteristics and under-five mortality among the 39,305 women who were part of the study are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Several health service indicators demonstrated statistically significant relationships with under-five mortality.\u003c/p\u003e \u003cp\u003eUnder-five mortality was significantly associated with maternal health service utilisation. ANC attendance was linked to child survival (χ\u0026sup2; = 7.44, p\u0026thinsp;=\u0026thinsp;0.006), with mothers having inadequate ANC visits showing a lower proportion of under-five deaths (20.7%) compared with those receiving adequate ANC (25.3%). Postnatal care roster entries were also significant (χ\u0026sup2; = 238.92, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); mothers with no documented entries had the highest under-five mortality (28.5%), those with 1 entry (21.8%) and 2\u0026ndash;3 entries (22.6%), while 4 or more entries recorded the highest mortality (47.3%), reflecting high-risk pregnancies. Immunisation entries were strongly associated with mortality (χ\u0026sup2; = 377.84, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with children having no entries at the highest risk (28.9%), 1 entry (21.3%), and 2\u0026ndash;3 entries the lowest (15.9%). Exclusive breastfeeding was also significantly protective (χ\u0026sup2; = 216.39, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); under-five mortality was higher among children not exclusively breastfed (27.3%) compared with those who were exclusively breastfed (20.3%). Overall, these findings highlight that maternal and child health service utilisation, including ANC, postnatal care, immunisation, and exclusive breastfeeding, plays a critical role in under-five survival in Ghana.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate Analysis of Health Service Utilisation Factors Associated with Under-Five Mortality (N\u0026thinsp;=\u0026thinsp;39,305)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnder-Five Mortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlive\u0026thinsp;\u0026lt;\u0026thinsp;5 years\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDied\u0026thinsp;\u0026lt;\u0026thinsp;5 years\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChi-Square (χ\u0026sup2;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e(p-Value)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANC Visit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInadequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e530 (79.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138 (20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28,870 (74.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,767 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEntries in Pregnancy and Postnatal Care Roster\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo entries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13,865 (71.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,523 (28.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle entry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,510 (78.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,483 (21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e238.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3 entries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,996 (77.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e873 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026thinsp;+\u0026thinsp;entries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (52.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (47.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEntries in Immunisation Roster\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo entries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,450 (71.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,275 (28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle entry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,195 (78.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,298 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e377.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3 entries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,755 (84.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e332 (15.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExclusive breastfeeding\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003e19,991 (72.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,511 (27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e216.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e9,409 (79.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,394 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e*Significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/h2\u003e \u003cp\u003eThe findings of the bivariate and multivariate logistic regression studies looking at the connection between under-five mortality and health service use are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Adequate ANC visits were linked to increased chances of under-five mortality in the crude model (COR\u0026thinsp;=\u0026thinsp;1.30, 95% CI: 1.08\u0026ndash;1.57; p\u0026thinsp;=\u0026thinsp;0.007). However, after controlling for confounders, this connection weakened and lost statistical significance (AOR\u0026thinsp;=\u0026thinsp;0.83, 95% CI: 0.68\u0026ndash;1.02; p\u0026thinsp;=\u0026thinsp;0.075). Entries in the pregnancy and postnatal care roster showed a strong and consistent association with under-five mortality. Although the adjusted analysis showed significantly higher risks of under-five mortality (AOR\u0026thinsp;=\u0026thinsp;1.67, 95% CI: 1.51\u0026ndash;1.86; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), women with a single entry had lower crude odds (COR\u0026thinsp;=\u0026thinsp;0.70, 95% CI: 0.67\u0026ndash;0.73; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than mothers without entries. The likelihood of under-five mortality increased monotonically with more entries, with mothers having four or more entries showing the highest adjusted odds (AOR\u0026thinsp;=\u0026thinsp;12.57, 95% CI: 6.68\u0026ndash;23.65; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eSimilarly, entries in the immunisation roster were protective against under-five mortality. Children with single or 2\u0026ndash;3 entries had significantly lower odds in both crude and adjusted analyses. For instance, in the adjusted model, children with two to three entries had odds that were 77% lower (AOR\u0026thinsp;=\u0026thinsp;0.23, 95% CI: 0.19\u0026ndash;0.28; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, compared to non-nursing mothers, breastfeeding mothers had a 15% decreased adjusted risk of under-five mortality (AOR\u0026thinsp;=\u0026thinsp;0.85, 95% CI: 0.79\u0026ndash;0.93; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic Regression Analysis of Health Service Utilisation and Sociodemographic Factors Associated with Under-Five Mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\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\u003eCOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e(p-Value)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e(p-Value)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANC Visit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInadequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.30 (1.08\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.007*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83 (0.68\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEntries in Pregnancy and Postnatal Care Roster\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo entries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle entry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.70 (0.67\u0026ndash;0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.67 (1.51\u0026ndash;1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3 entries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.73 (0.67\u0026ndash;0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.49 (3.03\u0026ndash;4.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026thinsp;+\u0026thinsp;entries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.25 (1.32\u0026ndash;3.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.57 (6.68\u0026ndash;23.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEntries in Immunisation Roster\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo entries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle entry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.57 (0.51\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57 (0.51\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3 entries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.47 (0.41\u0026ndash;0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23 (0.19\u0026ndash;0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExclusive breastfeeding\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003e0.68 (0.64\u0026ndash;0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85 (0.79\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e*Significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussions","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic Factors Associated with Under-Five Mortality\u003c/h2\u003e \u003cp\u003eThe findings of this study add to the body of information on sociodemographic drivers of under-five mortality in Ghana and highlight the persistence of child survival disparities associated with maternal, household, and contextual factors. The complex character of child mortality was highlighted by the significant variables that included maternal age, educational achievement, marital status, family affluence, and geographic location. Previous research has documented similar trends, such as Sarkodie (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), who emphasised the need for targeted interventions in rural areas and identified maternal age, wealth, and education as important factors influencing child survival.\u003c/p\u003e \u003cp\u003eLikewise, Aheto (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) emphasised the role of maternal education and family planning in reducing under-five mortality, supporting the protective influence of higher educational attainment observed in the present analysis.\u003c/p\u003e \u003cp\u003eThe results of Kanmiki et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), who found that women aged 35 to 49 had noticeably greater odds of dying before the age of five, are in line with the substantial correlation between advanced maternal age and increased risk of child mortality. This relationship may be partly attributable to biological risks associated with later pregnancies, including complications such as preterm delivery and low birthweight. In addition, older mothers may experience cumulative socioeconomic pressures, including caregiving responsibilities for multiple children or constrained access to timely healthcare, which could further compromise child survival.\u003c/p\u003e \u003cp\u003eMaternal education emerged as a particularly strong protective factor. Educated mothers are more likely to possess the knowledge and skills necessary to adopt optimal childcare practices, including appropriate nutrition, hygiene, immunisation, and timely healthcare-seeking. Household wealth similarly reduced the likelihood of under-five mortality, likely by improving access to quality health services, nutritious foods, and safer living environments. Preventive practices such as exclusive breastfeeding and immunisation also demonstrated protective effects, reinforcing their role in strengthening immunity and reducing vulnerability to infectious diseases, which remain leading causes of child deaths in Ghana.\u003c/p\u003e \u003cp\u003eMarital status was another important determinant, with women in certain marital categories experiencing higher risks of under-five mortality. This may reflect variations in economic security, emotional support, and caregiving capacity across household arrangements, particularly among widowed, separated, or cohabiting women who may face greater stress or resource constraints.\u003c/p\u003e \u003cp\u003eMarked regional disparities in under-five mortality were also evident, particularly in northern and rural regions. These patterns mirror findings by Mohammed et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) and Arku et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), who attributed higher mortality in northern Ghana to weaker health infrastructure, environmental risks, and limited access to essential services. Although place of residence lost statistical significance after adjustment in the current study, this contrasts with some earlier research (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) and suggests that socioeconomic and maternal characteristics may mediate much of the observed urban\u0026ndash;rural variation.\u003c/p\u003e \u003cp\u003eEnvironmental factors, especially the availability of safe water sources and adequate sanitation facilities, were also found to be significant. Poor water quality and inadequate sanitation increase exposure to diarrhoeal and hygiene-related infections, which are major contributors to under-five mortality. This result is in line with research by Nyaaba et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) and Fenta et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), which showed that increased usage of clean energy, water, and sanitation significantly lowers child mortality in sub-Saharan Africa. Cleaner household environments reduce exposure to waterborne pathogens and indoor air pollution, thereby lowering the risk of both gastrointestinal and respiratory illnesses.\u003c/p\u003e \u003cp\u003eThe protective effect of household wealth observed in this study aligns with prior evidence (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), highlighting how broader socioeconomic conditions shape child health outcomes. Wealthier households are better able to maintain clean living circumstances, obtain timely medical attention, and secure sufficient nutrition, all of which promote child survival.\u003c/p\u003e \u003cp\u003eOverall, the results support the theory that interrelated sociodemographic, environmental, and geographical factors are responsible for under-five mortality in Ghana. In order to address these issues, comprehensive interventions are needed that prioritise resource allocation to disadvantaged areas, delay high-risk childbearing, enhance household living conditions, provide access to clean water and sanitation, and support maternal education. In order to reduce avoidable child deaths in Ghana and accelerate progress toward Sustainable Development Goal 3.2, such a comprehensive approach is crucial.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eHealth Service Utilisation Factors Associated to Mortality in Children Under Five\u003c/h2\u003e \u003cp\u003eThe substantial associations between prenatal care (ANC), postnatal care, immunisation, and breastfeeding and child survival demonstrate the importance of health service usage determinants in Ghana's under-five mortality. The observed counterintuitive finding that mothers with adequate ANC visits had higher unadjusted under-five mortality likely reflects confounding by high-risk pregnancies, a pattern also noted in other studies, emphasising the complexity of interpreting ANC utilisation data (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). This is consistent with the findings of Guynn et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), who showed that community-based interventions such as the Health-2-Go program considerably lower child mortality by enhancing access to healthcare, especially in remote and difficult-to-reach areas. This suggests that the context and quality of care are just as crucial as the frequency of utilisation.\u003c/p\u003e \u003cp\u003eImmunisation uptake showed a strong protective effect against under-five mortality, consistent with Alhassan et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), who reported positive correlations between immunisation coverage and child survival in Ghana\u0026rsquo;s Volta region. Children who are fully or partially immunised have a lower risk of dying because vaccines protect them from potentially deadly infectious diseases including measles, polio, and pneumonia, which are still leading causes of death for children under five in low- and middle-income countries. Immunised children are therefore more resilient to preventable infections, and mothers who ensure immunisation may also be more engaged with healthcare services, further improving child survival.\u003c/p\u003e \u003cp\u003eSimilarly, breastfeeding demonstrated a protective role, in line with Kolekang et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), who found that early initiation and sustained breastfeeding significantly reduce child mortality risk. Breastfeeding reduces mortality because it provides infants with essential nutrients and antibodies that strengthen immunity and protect against common infections like diarrhoea and respiratory illnesses. Additionally, limiting exposure to tainted food or water a major source of infections in young children during the first six months of life is achieved through exclusive nursing. Moreover, sustained breastfeeding supports growth and development, improving overall health and survival prospects during the vulnerable early years.\u003c/p\u003e \u003cp\u003e These results underscore the need to strengthen comprehensive maternal and child health services across the full continuum of care, as supported by Ahmed et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), who highlighted that disruptions in essential health services during the COVID-19 pandemic led to increased child mortality in low- and middle-income countries, including Ghana.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003eStrengths\u003c/h2\u003e \u003cp\u003eThe results of this study can be applied to Ghanaian women of reproductive age since it used data from the 2022 Ghana Demographic and Health Survey, which used reliable and standardised data gathering techniques and is nationally representative. The large sample size ensured sufficient statistical power to identify meaningful relationships between sociodemographic characteristics, maternal healthcare utilisation, and under-five mortality. By employing multivariate logistic regression, the study accounted for potential confounding factors, enhancing the reliability of the observed risk and protective associations. Moreover, the analysis included various maternal and markers of child health, such as immunisation coverage and exclusive breastfeeding, providing a thorough evaluation of factors affecting child survival.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eSince it is impossible to determine the temporal order or direction of relationships between explanatory variables and under-five mortality, the cross-sectional nature of the DHS data restricts the ability to draw conclusions about causality. In addition, the study depended on respondents\u0026rsquo; self-reported information, which may be affected by recall errors, particularly for sensitive events such as child deaths and patterns of health service use. The scope of the analysis was further constrained by the variables included in the DHS, limiting assessment of important influences such as the quality of healthcare delivery, maternal nutritional status, and environmental conditions. Moreover, exclusive breastfeeding was assessed using reported practices at the time of the survey rather than through longitudinal observation, which may not accurately reflect continued adherence to exclusive breastfeeding over the recommended period.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eGiven that a significant portion of women had lost a child before the child turned five, this study shows that under-five mortality is still a major public health issue in Ghana. Despite ongoing national and worldwide efforts to increase child survival, the findings demonstrate that mortality risks remain unevenly distributed among demographic groups. The intricate interaction between maternal and child health service usage and sociodemographic traits shapes child survival in Ghana, highlighting the multidimensional nature of under-five mortality.\u003c/p\u003e \u003cp\u003eOlder maternal age emerged as a significant risk factor, likely reflecting the cumulative biological, obstetric, and socioeconomic vulnerabilities associated with later childbearing, including higher prevalence of pregnancy complications and chronic health conditions. Marital disruption and lower household wealth were also associated with increased mortality risk, suggesting that reduced social support and financial constraints may limit access to timely healthcare, adequate nutrition, and safe living conditions for children. In contrast, higher maternal education and improved household wealth were consistently protective, highlighting the role of education in enhancing health knowledge, care-seeking behaviour, and the ability to navigate health systems, as well as the importance of economic resources in securing better living environments and healthcare access.\u003c/p\u003e \u003cp\u003eHealth service\u0026ndash;related factors played a crucial protective role. Immunisation uptake and exclusive breastfeeding were strongly associated with reduced under-five mortality, reflecting their effectiveness in preventing infectious diseases, strengthening immunity, and supporting optimal child growth and development. However, persistent regional disparities point to underlying inequities in health system capacity, availability of skilled health personnel, infrastructure, and service quality across different parts of the country. These geographic inequalities suggest that national averages may mask substantial subnational gaps in child survival outcomes.\u003c/p\u003e \u003cp\u003eCollectively, the findings indicate that further reductions in under-five mortality in Ghana cannot be achieved through healthcare coverage expansion alone. Strengthening female education and economic empowerment is essential for improving maternal autonomy, health literacy, and sustained engagement with health services. At the same time, targeted investments in underserved regions are required to improve health infrastructure, service delivery, and continuity of care. Expanding immunisation outreach and reinforcing sustained breastfeeding support through integrated maternal, newborn, and child health services remain central to preventing avoidable child deaths. In the end, achieving Sustainable Development Goal 3.2 more quickly and guaranteeing fair increases in child survival throughout Ghana require a concerted, multisectoral strategy that incorporates social protection, education, and responsive health systems.\u003c/p\u003e"},{"header":"List of Abbreviations","content":"\u003cul\u003e\n \u003cli\u003eANC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Antenatal Care\u003c/li\u003e\n \u003cli\u003eAOR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Adjusted Odds Ratio\u003c/li\u003e\n \u003cli\u003eCI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Confidence Interval\u003c/li\u003e\n \u003cli\u003eCOR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Crude Odds Ratio\u003c/li\u003e\n \u003cli\u003eDHS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Demographic and Health Survey\u003c/li\u003e\n \u003cli\u003eGDHS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ghana Demographic and Health Survey\u003c/li\u003e\n \u003cli\u003eGHS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Ghana Health Service\u003c/li\u003e\n \u003cli\u003eGSS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ghana Statistical Service\u003c/li\u003e\n \u003cli\u003eSDG \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Sustainable Development Goal\u003c/li\u003e\n \u003cli\u003eU5MR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Under‑Five Mortality Rate\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/strong\u003eThe DHS Program granted permission to access the Maternal Health Survey data after a written request outlining the goals and parameters of the study was submitted. The anonymised dataset was only available to the research team, and anonymity was rigorously maintained in accordance with DHS data usage guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e Human Ethics and Consent to Participate declarations: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eWith permission from the DHS program, data were collected from the program and are accessible at https://dhsprogram.com/Data/, viewed on November 28, 2025.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThe authors would like to express their profound gratitude to the DHS for granting them access to the DHS dataset used in this investigation. We also thank the institutions and colleagues who helped make this research feasible.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSA developed the concept, organised the research, and penned the paper. JKG edited the manuscript, helped analyse the data, and critically evaluated the study design. RD and MPA-B evaluated draft versions and provided methodological guidance. Important information about text rewriting and content validation was provided by OUL, AMK, and MAR. All authors read, reviewed, and approved the final version of the work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe authors provided all of the funding for the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eNo conflicts of interest are disclosed by the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organisation. Trends in maternal mortality 2000 to 2020: estimates by WHO, UNICEF, UNFPA, World Bank Group and UNDESA/Population Division. World Health Organisation; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKallah-Dagadu G, Donkor F, Duah M, Yeboah H, Arku D, Lotsi A. Investigation of Factors Influencing Infant Mortality at Greater Accra Regional Hospital, Ghana. Biomed Res Int. 2024;2024(1):6610617.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdja-Sai C, Zakariah S, Owusu-Sekyere F. (2024). PP326 Topic: AS09\u0026ndash;Global Health/Resource Limited Setting/Health Inequalities/Impact of Global Warming/Other: A THREE-YEAR OVERVIEW OF UNDER-FIVE MORTALITY AT REBECCA AKUFO ADDO PAEDIATRIC INTENSIVE CARE UNIT/HIGH DEPENDENCY UNIT (RA-PICU/HDU). Pediatr Crit Care Med, 25(11S), e102.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdama ZK, Mettle FO, Baiden BM, Bii NK. Forecasting progress: analysing the trajectory of under-five child mortality for Ghana, Niger, Nigeria, and Sierra Leone towards SDG3 using ARIMA time series model. BMC Public Health. 2025;25(1):1607.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMohammed K, Abubakari AR, Amoak D, Antabe R, Luginaah I. (2023). Geographic disparities in the time to under-five mortality in Ghana. PLoS ONE, 18(9), e0291328.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSarkodie AO. Factors influencing under-five mortality in rural-urban Ghana: An applied survival analysis. Soc Sci Med. 2021;284:114185.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAheto JMK. Predictive model and determinants of under-five child mortality: evidence from the 2014 Ghana demographic and health survey. BMC Public Health. 2019;19(1):64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNyaaba AA, Tanle A, Dadzie LK, Ayamga M. Determinants of Under-Five Mortality in Ghana: Evidence from the Ghana Demographic and Health Survey. Int J Translational Med Res Public Health. 2020;4(2):1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTour\u0026eacute; S, Weeks J, Lopez-Carr D, Stow D. Evaluating links between dynamic urban landscapes and under-five child mortality in Accra, Ghana. Demographic Res. 2020;42:589\u0026ndash;614.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanmiki EW, Bawah AA, Agorinya I, Achana FS, Awoonor-Williams JK, Oduro AR, Akazili J. Socio-economic and demographic determinants of under-five mortality in rural northern Ghana. BMC Int health Hum rights. 2014;14(1):24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArku RE, Bennett JE, Castro MC, Agyeman-Duah K, Mintah SE, Ware JH, Ezzati M. Geographical inequalities and social and environmental risk factors for under-five mortality in Ghana in 2000 and 2010: Bayesian spatial analysis of census data. PLoS Med. 2016;13(6):e1002038.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFenta HM, Chen D-G, Zewotir T, Rad NN. Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countries. Front Public Health. 2025;13:101234.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNasejje JB, Mbuvha R, Mwambi H. (2022). Use of a deep learning and random forest approach to track changes in the predictive nature of socioeconomic drivers of under-5 mortality rates in sub-Saharan Africa. BMJ open, 12(2), e049786.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKolekang A, Sarfo B, Danso-Appiah A, Dwomoh D, Akweongo P. Are maternal and child health initiatives helping to reduce under-five mortality in Ghana? Results of a quasi-experimental study using coarsened exact matching. BMC Pediatr. 2021;21(1):473.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuynn I, Lich KH, Manortey S, Frerichs L, Mansfield AJ, Shaibu M, Alder SC. (2025). The \u0026lsquo;Health-2-Go\u0026rsquo;programme\u0026rsquo;s impact on all-cause mortality and clinic utilisation for children 5 and under: a retrospective cohort analysis of an iCCM intervention in Ghana\u0026rsquo;s Barekese Subdistrict. BMJ Global Health, \u003cem\u003e10\u003c/em\u003e(3).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlhassan AR. Under-Five Mortality in Ghana: Prevalence and Socioeconomic Predictors. SSRN Electron. J; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlhassan RK, Owusu-Agyei S, Ansah EK, Gyapong M, Ashinyo A, Ashinyo ME, Ekpor E. Trends and correlates of maternal, newborn and child health services utilisation in primary healthcare facilities: an explorative ecological study using DHIMSII data from one district in the Volta region of Ghana. BMC Pregnancy Childbirth. 2020;20(1):543.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed T, Roberton T, Vergeer P, Hansen PM, Peters MA, Ofosu AA, Shapira G. Healthcare utilisation and maternal and child mortality during the COVID-19 pandemic in 18 low-and middle-income countries: An interrupted time-series analysis with mathematical modelling of administrative data. PLoS Med. 2022;19(8):e1004070.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Under-five mortality, Ghana, maternal health, sociodemographic factors, immunisation, breastfeeding","lastPublishedDoi":"10.21203/rs.3.rs-8841953/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8841953/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGlobally, under-five child mortality is still a significant public health concern that disproportionately affects low- and middle-income nations. Significant sociodemographic and geographical discrepancies still exist in Ghana despite significant advances. Effective policy interventions require an understanding of the factors that contribute to death in children under five.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e39,305 women between the ages of 15 and 49 who gave birth within the five years before to the survey were included in a secondary analysis of the 2022 Ghana Demographic and Health Survey. To evaluate the relationships between under-five mortality and maternal age, education, marital status, household wealth, region, antenatal care, immunisation, postnatal care, and exclusive breastfeeding, descriptive statistics were conducted first, and then bivariate and multivariate logistic regression analyses were conducted. The threshold for statistical significance was fixed at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe percentage of mothers who reported child deaths under five was about 25.2%. In comparison to adolescents aged 15\u0026ndash;19 years (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), older maternal age was significantly linked to higher odds of under-five mortality, especially among women aged 25\u0026ndash;29 years (AOR\u0026thinsp;=\u0026thinsp;2.50), 30\u0026ndash;34 years (AOR\u0026thinsp;=\u0026thinsp;4.57), and 35\u0026ndash;49 years (AOR\u0026thinsp;=\u0026thinsp;8.44). All categories of marital status showed higher odds relative to women never in union. Protective factors included secondary (AOR\u0026thinsp;=\u0026thinsp;0.55) and higher education (AOR\u0026thinsp;=\u0026thinsp;0.25), richest household wealth (AOR\u0026thinsp;=\u0026thinsp;0.42), exclusive breastfeeding (AOR\u0026thinsp;=\u0026thinsp;0.85), and immunisation uptake, with children having 2\u0026ndash;3 immunisation entries showing a 77% reduction in mortality risk (AOR\u0026thinsp;=\u0026thinsp;0.23) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eMaternal health service use and sociodemographic disparities are the main causes of under-five mortality in Ghana. Strengthening maternal education, reducing socioeconomic disparities, and expanding immunisation and breastfeeding support are essential for achieving Sustainable Development Goal 3.2.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e","manuscriptTitle":"Determinants of Child Under-Five Mortality in Ghana: Analysis of the 2022 DHS Survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 17:29:37","doi":"10.21203/rs.3.rs-8841953/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":"d29043ab-80da-43f4-a622-5dbc27c568e9","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-17T17:54:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 17:29:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8841953","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8841953","identity":"rs-8841953","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}