Health System and Socioeconomic Determinants of Delayed Initiation of Breastfeeding Among Cesarean Deliveries in Kenya: Analysis of the 2022 Kenya Demographic and Health Survey

Health System and Socioeconomic Determinants of Delayed Initiation of Breastfeeding Among Cesarean Deliveries in Kenya: Analysis of the 2022 Kenya Demographic and Health Survey | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Health System and Socioeconomic Determinants of Delayed Initiation of Breastfeeding Among Cesarean Deliveries in Kenya: Analysis of the 2022 Kenya Demographic and Health Survey Charles Wanjiku This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9186315/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Timely initiation of breastfeeding within one hour of birth reduces neonatal mortality and supports optimal child development. Women who deliver by cesarean section (CS) face disproportionate barriers to early breastfeeding, yet the determinants of these delays remain poorly characterized in Kenya. Objective To examine health system and socioeconomic determinants of delayed breastfeeding initiation among CS-delivered women in Kenya using nationally representative data from the 2022 Kenya Demographic and Health Survey (KDHS 2022). Methods The analytical sample comprised 536 women who delivered by CS in the two years preceding the survey, had a live birth, and had valid breastfeeding timing data. Delayed initiation was defined as first breastfeeding occurring more than one hour after birth. Multilevel logistic regression models were used to account for community-level clustering. Predictors included facility type, facility level, antenatal care (ANC) adequacy, postnatal care (PNC) within 48 hours, maternal education, household wealth, urban-rural residence, birth size, plurality, and birth order. Results Among CS-delivered women, 63.3% experienced delayed breastfeeding initiation (weighted: 66.1%). The intraclass correlation coefficient from the null multilevel model was 18.8%, confirming significant community-level clustering. In the fully adjusted model, no predictor reached statistical significance at p < 0.05. Multiple birth showed the strongest borderline association (AOR = 2.80; 95% CI: 0.85–9.30; p = 0.092). Higher education trended toward increased odds of delay (AOR = 1.39; 95% CI: 0.90–2.15; p = 0.140). Model fit did not improve significantly with addition of socioeconomic or child-level variables. Conclusion Delayed breastfeeding initiation is highly prevalent among CS-delivered women in Kenya. Meaningful community-level clustering suggests that facility practices and contextual factors are important drivers. Targeted postnatal breastfeeding support protocols for CS mothers, including Baby-Friendly Hospital Initiative adaptations, are urgently needed. breastfeeding initiation cesarean section multilevel analysis postnatal care 1. Introduction Breastfeeding is among the most effective and low-cost interventions available for reducing neonatal and infant mortality. The World Health Organization (WHO) recommends that all newborns be put to the breast within one hour of birth, a practice referred to as timely initiation of breastfeeding (TIBF). Early initiation facilitates the transfer of colostrum — a nutrient-dense secretion rich in immunoglobulins, lactoferrin, and growth factors — that establishes passive immunity, stimulates gastrointestinal maturation, and supports the mother-infant bond critical to continued exclusive breastfeeding (WHO, 2023; Ballard & Morrow, 2013 ). Globally, failure to initiate breastfeeding within the first hour is associated with a significant increase in the risk of neonatal death, diarrheal disease, acute respiratory illness, and suboptimal cognitive development (Victora et al., 2016 ; Edmond et al., 2006 ). In sub-Saharan Africa, estimated rates of TIBF range from 50% to 75%, with considerable heterogeneity by country, delivery setting, and socioeconomic subgroup (UNICEF, 2021 ). Among women who deliver by cesarean section (CS), these barriers are compounded by several physiological and procedural factors: delayed onset of lactogenesis secondary to surgical stress, routine separation of mother and infant during postoperative recovery, restricted mobility and postoperative pain, and the frequent absence of structured breastfeeding support protocols in maternity facilities (Hobbs et al., 2016 ; Prior et al., 2012 ; Rowe-Murray & Fisher, 2002 ). CS rates in Kenya have risen markedly, from 6.5% in 2008–2009 to 14.6% in 2022 (KNBS, 2023). This upward trend mirrors patterns across low- and middle-income countries, where the medicalization of childbirth has not been matched by equivalent investment in postnatal breastfeeding support. CS deliveries in Kenya are concentrated among wealthier, more educated, and urban women, raising questions about whether the socioeconomic predictors of CS also shape breastfeeding outcomes within this population (Kujabi et al., 2021 ). Existing Kenyan literature on breastfeeding determinants has predominantly analyzed the general population, giving limited attention to CS-delivered women as a distinct subgroup whose determinants may differ substantially from the broader population. Furthermore, most prior studies apply conventional logistic regression to survey data, ignoring the hierarchical structure created by clustering of women within communities and health facilities. This produces downwardly biased standard errors and may inflate the statistical significance of individual-level predictors (Goldstein, 2011 ). This study addresses these gaps by analyzing health system and socioeconomic determinants of delayed TIBF specifically among CS-delivered women in Kenya using the 2022 KDHS, the most recent nationally representative dataset available. Multilevel logistic regression is employed to properly account for community-level clustering. The specific objectives were to: (i) estimate the prevalence of delayed TIBF among CS-delivered women; (ii) examine associations between health system factors — facility type, facility level, ANC adequacy, and PNC within 48 hours — and delayed TIBF; (iii) examine associations between socioeconomic factors — maternal education, household wealth, and urban-rural residence — and delayed TIBF; and (iv) quantify community-level clustering in delayed TIBF using the intraclass correlation coefficient (ICC). 2. Literature Review 2.1 Global Significance of Timely Breastfeeding Initiation The evidence linking early breastfeeding with neonatal survival is robust. In a landmark Ghanaian cohort study, Edmond et al. ( 2006 ) demonstrated that initiating breastfeeding within one hour of birth was associated with a 22% reduction in neonatal mortality compared to initiation at one to 23 hours, rising to 45% when compared with initiation after 24 hours. Subsequent analyses from South Asia and sub-Saharan Africa have broadly replicated these findings even after controlling for birth setting and maternal socioeconomic characteristics (Debes et al., 2013 ). The biological mechanism is well established: colostrum contains secretory immunoglobulin A, lactoferrin, lysozymes, and growth factors that establish intestinal barrier function and confer passive humoral immunity before the neonate's own immune system matures (Ballard & Morrow, 2013 ). Globally, TIBF is one of eight core indicators for monitoring infant and young child feeding practices recommended by WHO and UNICEF (WHO/UNICEF, 2021 ). The latest estimates indicate that only 44% of newborns worldwide are breastfed within the first hour of birth, with particularly low rates in facility-delivered births where institutional protocols frequently disrupt early skin-to-skin contact (UNICEF, 2021 ; Victora et al., 2016 ). 2.2 Cesarean Section and Breastfeeding: Mechanisms and Evidence CS delivery is consistently associated with delayed breastfeeding initiation across diverse settings. A systematic review by Hobbs et al. ( 2016 ) identified 21 studies predominantly from high-income countries, finding that CS-delivered women were significantly less likely to initiate breastfeeding early compared to those who delivered vaginally. The pathways are multiple and interact. Regional or general anesthesia may cause maternal sedation and neonatal neurobehavioral depression, delaying rooting and suckling reflexes (Zanardo et al., 2010 ). Postoperative pain, restricted maternal mobility, and intravenous lines physically impede the positioning required for early breastfeeding. Standard institutional practices frequently separate the mother and neonate during postoperative monitoring, interrupting the sensitive early period for skin-to-skin contact and breastfeeding (Rowe-Murray & Fisher, 2002 ). Evidence from low- and middle-income countries is consistent with these findings. Shifraw et al. ( 2018 ) in Ethiopia found CS delivery was among the strongest predictors of delayed TIBF (AOR = 3.2). Similar findings have been reported from Nigeria and Tanzania, where facility-level constraints including staff shortages and absent lactation counselors compound the physiological barriers (Ogbo et al., 2019 ; Agho et al., 2011 ). In Kenya, analysis of KDHS 2014 data confirmed that CS-delivered women were significantly less likely to initiate within one hour, though formal examination of predictors within the CS subgroup was not conducted (Kamunya et al., 2021 ). A key limitation of much of this literature is the failure to distinguish elective from emergency CS, which may differ in their effects on immediate postoperative maternal-infant contact — a gap that persists in the present study as well. 2.3 Health System Factors and Breastfeeding Outcomes The health system context shapes TIBF through structural factors — the availability of breastfeeding-friendly protocols — and through the practices of individual providers. The Baby-Friendly Hospital Initiative (BFHI), launched by WHO and UNICEF in 1991, provides a framework for hospitals to support TIBF through ten steps that include immediate skin-to-skin contact, early breastfeeding support, and restriction of formula supplementation (WHO/UNICEF, 2009). Evidence from multiple LMICs suggests BFHI implementation is associated with higher rates of early initiation, though implementation fidelity is often incomplete in resource-constrained settings (Perez-Escamilla et al., 2016 ). In Kenya, the landscape of maternity facilities ranges from government district hospitals to private clinics and faith-based mission hospitals. Private facility delivery is associated with higher CS rates but not necessarily better breastfeeding support, partly because private facilities serve wealthier clients whose expectations of care may not prioritize early breastfeeding (Kujabi et al., 2021 ). ANC provides an opportunity for breastfeeding education and preparation prior to delivery, and PNC within 48 hours is the most proximate contact during which TIBF support can be reinforced. However, evidence on these associations specifically within the CS subgroup remains sparse, and the content quality of these contacts is not captured in household survey data. 2.4 Socioeconomic Determinants of Breastfeeding Initiation The relationship between socioeconomic status and TIBF is paradoxical in the African context. Unlike in high-income countries, wealthier and more educated women in sub-Saharan Africa are sometimes less likely to initiate breastfeeding promptly, partly because they are more likely to deliver by CS, have access to infant formula, and be exposed to breast milk substitute marketing (Victora et al., 2016 ; Rollins et al., 2016 ). Mgongo et al. ( 2017 ) in Tanzania found higher maternal education independently associated with delayed TIBF after controlling for delivery mode, attributing this to the greater likelihood of facility delivery among educated women and lower priority given to immediate breastfeeding in these settings. Household wealth has shown a similar inverse association with TIBF in several KDHS-based analyses (Kamunya et al., 2021 ). Urban residence adds further ambiguity: urban women are more likely to have facility deliveries and access to trained staff, but are also more exposed to formula marketing and may face time pressures associated with employment. 2.5 Methodological Gaps A recurring limitation in the breastfeeding literature is the use of single-level regression for outcomes that are clustered within communities and facilities. Mothers sharing a community share contextual exposures — local norms, facility practices, community support structures — that create within-cluster correlation in outcomes. Ignoring this underestimates standard errors, inflates significance, and obscures the contribution of contextual factors (Goldstein, 2011 ). Recent studies applying multilevel models to breastfeeding in Nigeria and Ethiopia found ICC values of 5–25%, indicating meaningful clustering (Ogbo et al., 2019 ; Shifraw et al., 2018 ). None, however, restricted analysis to CS-delivered women as a distinct subgroup, where facility-level factors are likely to be more dominant. The present study addresses this gap directly. 3. Methods 3.1 Data Source and Study Design This study used data from the 2022 Kenya Demographic and Health Survey (KDHS 2022), a nationally representative cross-sectional household survey conducted by the Kenya National Bureau of Statistics (KNBS) with technical support from ICF International. The KDHS employs a stratified two-stage cluster sampling design, with enumeration areas as primary sampling units and households as secondary sampling units. Data were collected from women aged 15–49 years on reproductive health, child health, nutrition, and health service utilization. Full methodological details are available in the survey report (KNBS, 2023). 3.2 Study Population and Sample Selection The target population was women who had delivered by CS in the two years preceding the survey, had a live birth, and had complete breastfeeding timing data. Child age in months was calculated as the difference between the date of interview (v008) and date of birth (b3). CS delivery was identified using variable m17 (coded 1 = cesarean). Breastfeeding timing was captured by variable m34, which records time to first breastfeeding using a combined hour-day scheme (0–199 = hours; 200–299 = days). Cases coded 994 (never breastfed), children who had died at interview (b5 = 0), and cases with missing values on delivery mode or breastfeeding timing were excluded. The final analytical sample comprised 536 mother-child pairs. 3.3 Outcome Variable The outcome was delayed breastfeeding initiation, defined as first breastfeeding more than one hour after birth, consistent with WHO guidelines. A binary variable was constructed: 1 = delayed (> 1 hour), 0 = timely (≤ 1 hour). Hour values were extracted for m34 codes 0–199; day-coded values (200–299) were converted to hours by multiplying (m34 − 200) × 24. Among the 536 women, 339 (63.3%) experienced delayed initiation. 3.4 Explanatory Variables Health system variables included facility type (public vs. private/NGO/FBO), facility level (hospital vs. health centre or dispensary), ANC adequacy (≥ 4 vs. < 4 visits, consistent with the WHO focused ANC threshold applicable at the time of these births), and PNC within 48 hours (derived from variable m63). Socioeconomic variables included maternal education (no education; primary; secondary and above), household wealth index (collapsed from five DHS quintiles into three groups: lower, middle, upper), and urban-rural residence. Child-level covariates included birth size as reported by the mother (large/very large; average; small/very small), plurality (singleton vs. multiple), and birth order (first; second-third; fourth or higher). 3.5 Statistical Analysis Survey-weighted proportions were calculated for all variables using the svyset command in Stata 17. Cross-tabulations with the Pearson chi-square design-based test examined bivariate associations. Unadjusted odds ratios (UOR) with 95% confidence intervals were estimated for each predictor using separate bivariate multilevel logistic regression models (melogit), with women nested within community clusters (v001) to account for clustering. Multivariable analysis proceeded in three stages. A null multilevel model with no predictors estimated the baseline ICC using the formula ICC = τ² / (τ² + π²/3), where π²/3 = 3.29. Model 1 added health system predictors; Model 2 additionally included socioeconomic variables; Model 3 further included child-level covariates. Likelihood ratio tests compared nested models. Model fit was assessed using AIC and BIC. Survey weights (v005/1,000,000) were applied to descriptive analyses. Statistical significance was set at p < 0.05; borderline findings (0.05 ≤ p < 0.10) are also reported. All analyses were conducted in Stata/IC 17.0. 3.6 Ethical Considerations The 2022 KDHS was approved by the Kenya Medical Research Institute Ethics Review Committee and ICF's Institutional Review Board. All participants provided informed consent. The present analysis used anonymized, publicly available secondary data and required no additional ethical clearance. 4. Results 4.1 Sample Characteristics Table 1 presents characteristics of the 536 CS-delivered women in the analytical sample. The mean child age was 11.7 months (SD = 6.9), consistent with the restriction to births in the preceding 24 months. The vast majority of deliveries occurred in hospitals (92.9%), and in private or faith-based/NGO facilities (88.4%). Nearly three-quarters (73.9%) had adequate ANC (≥ 4 visits), and 88.1% received PNC within 48 hours. Most women had secondary or higher education (70.1%), and 59.1% were in the upper wealth category. Urban and rural residents were nearly equally distributed. Most children were singletons (95.7%), of average birth size (65.9%), and of first or second birth order (81.9%). Table 1 Characteristics of the Analytical Sample, CS-Delivered Women, KDHS 2022 (n = 536) Characteristic n % Weighted % Outcome Timely BF initiation (≤ 1 hour) 197 36.7 33.9 Delayed BF initiation (> 1 hour) 339 63.3 66.1 Health System Factors Facility type: Public 62 11.6 14.9 Facility type: Private/NGO/FBO 474 88.4 85.1 Facility level: Hospital 498 92.9 94.6 Facility level: Health centre/dispensary 38 7.1 5.4 ANC adequate (≥ 4 visits) 396 73.9 76.1 PNC within 48 hours 472 88.1 89.2 Socioeconomic Factors Education: No education 23 4.3 2.1 Education: Primary 137 25.6 25.4 Education: Secondary and above 376 70.1 72.5 Wealth: Lower quintiles 125 23.3 18.8 Wealth: Middle quintile 94 17.5 15.6 Wealth: Upper quintiles 317 59.1 65.7 Urban residence 252 47.0 49.6 Rural residence 284 53.0 50.4 Child-level Factors Birth size: Large/very large 109 20.3 21.9 Birth size: Average 353 65.9 — Birth size: Small/very small 69 12.9 — Multiple birth 23 4.3 3.9 Birth order: First 170 31.7 30.1 Birth order: Second–third 269 50.2 53.1 Birth order: Fourth or higher 97 18.1 16.8 Sex of child: Male 286 53.4 — BF = Breastfeeding; ANC = Antenatal Care; PNC = Postnatal Care. Weighted % derived from survey-weighted tabulations using v005/1,000,000. — = not calculated for this subgroup. Table 2 Bivariate Analysis: Association Between Explanatory Variables and Delayed Breastfeeding Initiation Among CS-Delivered Women, KDHS 2022 (n = 536) Variable Delayed BF Initiation UOR 95% CI p-value No n (%) Yes n (%) Health System Factors Facility type Public (ref.) 21 (33.9) 41 (66.1) 1.00 — — Private/NGO/FBO 176 (37.1) 298 (62.9) 0.83 0.43–1.59 0.569 Facility level Hospital (ref.) 183 (36.7) 315 (63.3) 1.00 — — Health centre/dispensary 14 (36.8) 24 (63.2) 0.97 0.44–2.16 0.950 ANC visits (adequacy) < 4 visits (ref.) 50 (35.7) 90 (64.3) 1.00 — — ≥ 4 visits 147 (37.1) 249 (62.9) 0.95 0.60–1.52 0.843 PNC within 48 hours No (ref.) 21 (32.8) 43 (67.2) 1.00 — — Yes 176 (37.3) 296 (62.7) 0.80 0.42–1.51 0.488 Socioeconomic Factors Maternal education No education (ref.) 9 (39.1) 14 (60.9) 1.00 — — Primary 61 (44.5) 76 (55.5) 0.77 0.26–2.23 0.626 Secondary and above 127 (33.8) 249 (66.2) 1.33 0.48–3.69 0.585 Household wealth Lower quintiles (ref.) 50 (40.0) 75 (60.0) 1.00 — — Middle quintile 40 (42.6) 54 (57.4) 0.88 0.46–1.68 0.705 Upper quintiles 107 (33.8) 210 (66.2) 1.40 0.83–2.34 0.204 Residence Rural (ref.) 112 (39.4) 172 (60.6) 1.00 — — Urban 85 (33.7) 167 (66.3) 1.37 0.89–2.11 0.158 Child-level Factors Birth size Normal/large (ref.) 163 (38.2) 264 (61.8) 1.00 — — Small/very small 34 (31.2) 75 (68.8) 1.51 0.87–2.61 0.141 Plurality Singleton (ref.) 192 (37.4) 321 (62.6) 1.00 — — Multiple birth 5 (21.7) 18 (78.3) 2.17 0.72–6.59 0.171 Birth order First (ref.) 64 (37.6) 106 (62.4) 1.00 — — Second–third 91 (33.8) 178 (66.2) 1.20 0.75–1.91 0.454 Fourth or higher 42 (43.3) 55 (56.7) 0.73 0.40–1.34 0.309 UOR = Unadjusted Odds Ratio; CI = Confidence Interval; ref. = reference category. UORs estimated using multilevel logistic regression (melogit) with women nested within community clusters. p-values from Wald chi2 tests. BF = Breastfeeding; ANC = Antenatal Care; PNC = Postnatal Care. Table 3 Multilevel Logistic Regression Models for Delayed Breastfeeding Initiation Among CS-Delivered Women, KDHS 2022 (n = 536) Variable Null Model Model 1 AOR (95% CI) Model 2 AOR (95% CI) Model 3 AOR (95% CI) p (Model 3) Health system factors Facility type (private ref.) — 0.83 (0.43–1.59) 0.83 (0.42–1.64) 0.79 (0.40–1.57) 0.507 Facility level (hospital ref.) — 1.00 (0.45–2.23) 1.08 (0.48–2.46) 1.13 (0.49–2.58) 0.774 ANC adequate — 0.95 (0.60–1.52) 0.91 (0.56–1.49) 0.83 (0.50–1.37) 0.461 PNC within 48h — 0.80 (0.42–1.54) 0.75 (0.38–1.47) 0.74 (0.37–1.48) 0.396 Socioeconomic factors Education (per category) — — 1.40 (0.93–2.11) 1.39 (0.90–2.15) 0.140 Wealth (per category) — — 1.06 (0.77–1.47) 1.06 (0.76–1.47) 0.732 Urban residence — — 1.26 (0.74–2.13) 1.25 (0.74–2.13) 0.408 Child-level factors Small birth size — — — 1.57 (0.89–2.75) 0.118 Multiple birth — — — 2.80 (0.85–9.30) 0.092 Birth order (per category) — — — 0.94 (0.68–1.31) 0.714 Random effects Cluster variance (τ²) 0.765 0.774 0.877 0.907 — ICC (%) 18.8% 19.0% 21.0% 21.6% — Model fit Log-likelihood −352.49 −350.97 −348.04 −345.37 — AIC — 713.9 714.1 714.7 — BIC — 739.7 752.6 766.2 — AOR = Adjusted Odds Ratio; CI = Confidence Interval; ICC = Intraclass Correlation Coefficient; AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion. All models estimated using melogit in Stata 17. †p < 0.10. Cluster variance and ICC reported from each respective model. Model 1 = health system factors only; Model 2 = health system + socioeconomic factors; Model 3 = full model. Source: KDHS 2022. 4.2 Prevalence of Delayed Breastfeeding Initiation Overall, 339 of 536 women (63.3%; weighted 66.1%) experienced delayed breastfeeding initiation. The mean time to first breastfeeding was 61.5 hours (SD = 57.4), ranging from immediate initiation to 504 hours. This high prevalence across all subgroups indicates that delay is normative rather than exceptional among CS-delivered women in Kenya. 4.3 Bivariate Associations Table 2 presents bivariate associations. No predictor reached statistical significance at p < 0.05 in bivariate analysis. Among health system factors, the proportions of delayed initiation were nearly identical across facility type, facility level, ANC adequacy, and PNC receipt. Among socioeconomic factors, a higher proportion of delayed initiators had secondary or above education (66.2% vs. 60.9% for no education) and were in the upper wealth category (66.2% vs. 60.0% for lower wealth), though neither was significant. Urban residence trended toward higher odds of delay (UOR = 1.37, 95% CI: 0.89–2.11, p = 0.158). Among child-level factors, multiple birth showed the largest unadjusted association (UOR = 2.17, 95% CI: 0.72–6.59, p = 0.171). 4.4 Multilevel Model Results Table 3 presents results across all four models. The null model ICC was 18.8% (τ² = 0.765), indicating that approximately one-fifth of the total variation in delayed initiation was attributable to community-level differences, confirming the appropriateness of the multilevel approach. In Model 1 (health system factors only), none of the four predictors reached significance. Private facility delivery was associated with lower odds of delay (AOR = 0.83, 95% CI: 0.43–1.59, p = 0.569), and PNC within 48 hours was also in the protective direction (AOR = 0.80, 95% CI: 0.42–1.54, p = 0.488), though neither was significant. The overall model Wald chi2 was 0.82 (p = 0.936). Model 2 added socioeconomic variables. Education showed a positive borderline association (AOR = 1.40, 95% CI: 0.93–2.11, p = 0.103), suggesting that higher education was associated with greater odds of delay, paradoxically. The likelihood ratio test comparing Model 2 with Model 1 was not significant (LR chi2 = 5.86, p = 0.119), and AIC marginally increased. In the full Model 3, multiple birth had the strongest association with delayed initiation (AOR = 2.80, 95% CI: 0.85–9.30, p = 0.092), approaching but not reaching significance. Small birth size trended positive (AOR = 1.57, 95% CI: 0.89–2.75, p = 0.118). Education retained a borderline positive association (AOR = 1.39, p = 0.140). The LR test comparing Model 3 to Model 2 was not significant (p = 0.148), and the BIC increased from 752.6 to 766.2, confirming that the simpler Model 1 was the most parsimonious fit. 5. Discussion This study examined health system and socioeconomic determinants of delayed breastfeeding initiation among CS-delivered women in Kenya using nationally representative data. The central finding — that 63.3% of this population experienced delayed initiation — places Kenya among the countries with the highest rates of delayed TIBF in the CS subgroup, comparable to rates of 55–70% reported from Ethiopia and Nigeria (Shifraw et al., 2018 ; Ogbo et al., 2019 ). This prevalence is substantially higher than national estimates for all delivery modes, underscoring the particular vulnerability of CS-delivered women to breastfeeding disruption. The null model ICC of 18.8% is both a methodological and substantive finding. Methodologically, it confirms that conventional logistic regression would have underestimated standard errors and potentially produced spuriously significant individual-level associations. Substantively, it means that nearly one-fifth of the variation in delayed initiation is attributable to community-level factors — where a woman lives or delivers may matter as much as who she is. Local breastfeeding norms, community peer support, the practices of specific maternity facilities, and the attitudes of healthcare workers may account for this clustering in ways that individual-level survey data cannot fully capture. The ICC increased slightly across models (from 18.8% in the null to 21.6% in Model 3), suggesting that none of the measured individual-level variables fully explained the community-level variance. The absence of statistically significant individual-level predictors requires careful interpretation rather than dismissal. The study was likely underpowered to detect moderate associations given n = 536 and the restricted variation in several key predictors: 92.9% of deliveries occurred in hospitals and 88.4% in private facilities, leaving very little facility-type variability to drive associations. This reflects the socioeconomic patterning of CS delivery in Kenya rather than a true null finding — CS is concentrated in a relatively homogeneous subgroup of wealthier, better-educated, facility-delivered women. The borderline positive association between higher education and delayed initiation (AOR = 1.39, p = 0.140) is consistent with the paradoxical pattern noted in sub-Saharan African literature. More educated women are more likely to have elective CS, more likely to be exposed to formula marketing, and may be less embedded in community breastfeeding support networks. They may also hold different postpartum care expectations that do not prioritize immediate breastfeeding. This finding adds to growing evidence that educational interventions alone are insufficient to improve TIBF among CS-delivered women (Mgongo et al., 2017 ; Ogbo et al., 2019 ). Multiple birth showed the strongest, albeit non-significant, association (AOR = 2.80, p = 0.092). The wide confidence interval (0.85–9.30) reflects the small number of multiple births (n = 23). Clinically, the magnitude is plausible: multiple births delivered by CS typically involve separation of infants from the mother for observation or neonatal intensive care, directly impeding early breastfeeding. These mothers constitute a particularly high-risk group warranting targeted postnatal lactation support. The lack of significant association between ANC adequacy, PNC within 48 hours, and delayed initiation may reflect the inability of the KDHS to capture the content and quality of these contacts. A woman may have attended four or more ANC visits without receiving meaningful breastfeeding counseling. Within the CS delivery context, immediate postoperative management practices may be more determinative than prenatal preparation, and these are not captured in household survey data. These findings have clear policy implications. Given the high prevalence and meaningful community-level clustering, facility-level interventions are likely to be more effective than individual-level education programs. Implementing and scaling the BFHI in Kenyan hospitals, with specific adaptations for CS deliveries, would directly address the primary mechanism of delay: postoperative separation and lack of lactation support. This includes facilitating skin-to-skin contact in the recovery room, training nursing staff in postoperative breastfeeding positioning, and establishing dedicated lactation counselor roles in maternity facilities. The study has several limitations. The cross-sectional design precludes causal inference, and breastfeeding timing data rely on maternal recall, which may be subject to telescoping bias. The KDHS does not distinguish between elective and emergency CS, does not capture facility-level practices or BFHI certification status, and the sample size of CS-delivered women limits statistical power. Future research using facility-based data, qualitative methods, and prospective designs is needed to further characterize the mechanisms driving delayed TIBF in this population. 6. Conclusion Delayed breastfeeding initiation affects nearly two-thirds of CS-delivered women in Kenya, making it a pervasive rather than exceptional problem in this population. The multilevel analysis revealed significant community-level clustering (ICC = 18.8%), indicating that contextual and facility-level factors are important drivers of this outcome even if they cannot be fully characterized using household survey data. No individual-level predictor reached statistical significance in the adjusted models, though multiple birth and higher maternal education showed borderline associations warranting further investigation. The findings call for a policy shift from a focus on individual maternal characteristics to the systemic conditions under which CS deliveries occur. Strengthening maternity facility protocols to support immediate postoperative breastfeeding, scaling BFHI implementation with CS-specific adaptations, and investing in postnatal lactation support services are the most actionable levers for reducing delayed TIBF among this growing and underserved population of Kenyan mothers. Declarations The ethics declaration This research was performed in accordance with the principles of the Declaration of Helsinki. The study used secondary data from the 2022 Kenya Demographic and Health Survey (KDHS), which is publicly available through the DHS Program website ( https://dhsprogram.com ). Ethical approval for the original KDHS data collection was obtained from the ICF Institutional Review Board (Project Number: 132989) and the Kenya Medical Research Institute (KEMRI) Scientific and Ethics Review Unit (Protocol Number: KEMRI/RES/7/3/1). All survey respondents provided written informed consent before participation, including consent for anonymized data to be used in future research. Since this analysis involved de-identified, publicly available data, it did not require further ethical clearance. Human Ethics and Consent to Participate All participants in the original surveys provided written informed consent before participation, including consent for anonymized data to be used in future research. As this study involved secondary analysis of fully anonymized, publicly available data, it was exempt from additional ethical review. Human Ethics and Consent to Participate declarations: not applicable for this secondary analysis Consent to Publish Consent to Publish declaration: not applicable. This manuscript does not contain any individual person's data in any form (including individual details, images, or videos) that would require consent for publication. All data presented are aggregated, anonymized, and publicly available from the Demographic and Health Surveys (DHS) Program Competing interests The authors declare that they have no competing interests. No financial or non-financial interests that could be construed as influencing the research or interpretation of the findings exist. Funding The authors received no financial support for the research, authorship, and/or publication of this article. This study was conducted using publicly available data from the Demographic and Health Surveys (DHS) Program, and all work was performed as part of the authors' academic affiliations without external funding. Author Contribution Charles, John: Conceptualization, Methodology, Software, Formal analysis, Data curation, Visualization, Writing – original draft. Mary, Charles: Conceptualization, Methodology, Investigation, Validation, Writing – review & editing, Project administration. Charles, erick: Resources, Validation, Writing – review & editing, Supervision. All authors have read and approved the final manuscript Data Availability The datasets generated and/or analyzed during the current study are available in the Demographic and Health Surveys (DHS) Program repository and the Kenya National Bureau of Statistics. [https://statistics.knbs.or.ke/nada/index.php/catalog/128](https:/statistics.knbs.or.ke/nada/index.php/catalog/128) .Alternatively, the official DHS Program website for the Kenya 2022 KDHS dataset is: [https://www.dhsprogram.com/data/available-datasets.cfm](https:/www.dhsprogram.com/data/available-datasets.cfm) Access to the data requires free registration and approval of a research proposal by The DHS Program, in accordance with the data use agreements with the Government of Kenya. The data are publicly available for legitimate research purposes. The authors confirm that they did not have any special access privileges to these data References Agho KE, Dibley MJ, Odiase JI, Ogujii SM. Determinants of exclusive breastfeeding in Nigeria. BMC Pregnancy Childbirth. 2011;11:2. https://doi.org/10.1186/1471-2393-11-2 . Ballard O, Morrow AL. Human milk composition: Nutrients and bioactive factors. Pediatr Clin North Am. 2013;60(1):49–74. https://doi.org/10.1016/j.pcl.2012.10.002 . Debes AK, Kohli A, Walker N, Edmond K, Mullany LC. Time to initiation of breastfeeding and neonatal mortality and morbidity: A systematic review. BMC Public Health. 2013;13(Suppl 3):S19. https://doi.org/10.1186/1471-2458-13-S3-S19 . Edmond KM, Zandoh C, Quigley MA, Amenga-Etego S, Owusu-Agyei S, Kirkwood BR. Delayed breastfeeding initiation increases risk of neonatal mortality. Pediatrics. 2006;117(3):e380–6. https://doi.org/10.1542/peds.2005-1496 . Goldstein H. Multilevel Statistical Models. 4th ed. Wiley; 2011. https://doi.org/10.1002/9780470973394 . Hobbs AJ, Mannion CA, McDonald SW, Brockway M, Tough SC. The impact of caesarean section on breastfeeding initiation, duration and difficulties in the first four months postpartum. BMC Pregnancy Childbirth. 2016;16:90. https://doi.org/10.1186/s12884-016-0876-1 . Kamunya R, Ndinda C, Muthoni E. Factors associated with timely initiation of breastfeeding in Kenya: Analysis of the 2014 Kenya Demographic and Health Survey. Afr J Food Agric Nutr Dev. 2021;21(3):17654–73. https://doi.org/10.18697/ajfand.98.20044 . Kenya National Bureau of Statistics [KNBS]. (2023). Kenya Demographic and Health Survey 2022. KNBS. https://www.knbs.or.ke/reports/kdhs-2022/ Kujabi ML, Petersen TG, Hutchinson JN, Byberg S. Factors associated with caesarean section in sub-Saharan Africa: A systematic review. Acta Obstet Gynecol Scand. 2021;100(4):590–604. https://doi.org/10.1111/aogs.14064 . Mgongo M, Hussein TH, Stray-Pedersen B, Vangen S, Msuya SE, Wandel M. Prevalence and predictors of exclusive breastfeeding among women in Kilimanjaro region, Northern Tanzania. Int Breastfeed J. 2017;12:2. https://doi.org/10.1186/s13006-016-0091-3 . Ogbo FA, Dhami MV, Awosemo AO, Olusanya BO, Page A. Regional prevalence and determinants of exclusive breastfeeding in India. Int Breastfeed J. 2019;14:20. https://doi.org/10.1186/s13006-019-0214-0 . Perez-Escamilla R, Martinez JL, Segura-Perez S. Impact of the Baby-Friendly Hospital Initiative on breastfeeding and child health outcomes: A systematic review. Maternal Child Nutr. 2016;12(3):402–17. https://doi.org/10.1111/mcn.12294 . Prior E, Santhakumaran S, Gale C, Philipps LH, Modi N, Hyde MJ. Breastfeeding after cesarean delivery: A systematic review and meta-analysis. Am J Clin Nutr. 2012;95(5):1113–35. https://doi.org/10.3945/ajcn.111.030254 . Rollins NC, Bhandari N, Hajeebhoy N, Horton S, Lauer JM, Martines JC, Piwoz EG, Richter LM, Victora CG. Why invest, and what it will take to improve breastfeeding practices? Lancet. 2016;387(10017):491–504. https://doi.org/10.1016/S0140-6736(15)01044-2 . Rowe-Murray HJ, Fisher JRW. Baby friendly hospital practices: Cesarean section is a persistent barrier to early initiation of breastfeeding. Birth. 2002;29(2):124–31. https://doi.org/10.1046/j.1523-536X.2002.00172.x . Shifraw T, Worku A, Berhane Y. Factors associated with exclusive breastfeeding practices of urban women in Addis Ababa public health centers, Ethiopia. Int Breastfeed J. 2018;10:22. https://doi.org/10.1186/s13006-015-0048-4 . UNICEF. (2021). Breastfeeding: A mother's gift for every child. UNICEF. https://www.unicef.org/media/55601/file/UNICEF_Breastfeeding_A_Mothers_Gift_for_Every_Child.pdf Victora CG, Bahl R, Barros AJD, Franca GVA, Horton S, Krasevec J, Murch S, Sankar MJ, Walker N, Rollins NC. Breastfeeding in the 21st century: Epidemiology, mechanisms, and lifelong effect. Lancet. 2016;387(10017):475–90. https://doi.org/10.1016/S0140-6736(15)01024-7 . World Health Organization. (2016). WHO recommendations on antenatal care for a positive pregnancy experience. WHO. https://www.who.int/publications/i/item/9789241549912 World Health Organization. (2023). Breastfeeding: Key facts. WHO. https://www.who.int/news-room/fact-sheets/detail/breastfeeding World Health Organization & United Nations Children's Fund. (2009). Baby-friendly hospital initiative: Revised, updated and expanded for integrated care. WHO. https://www.who.int/publications/i/item/9789241594967 World Health Organization & United Nations Children's Fund. (2021). Indicators for assessing infant and young child feeding practices. WHO. https://www.who.int/publications/i/item/9789240025257 Zanardo V, Svegliado G, Cavallin F, Giustardi A, Cosmi E, Litta P, Trevisanuto D. Elective cesarean delivery: Does it have a negative effect on breastfeeding? Birth. 2010;37(4):275–9. https://doi.org/10.1111/j.1523-536X.2010.00421.x . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 24 Apr, 2026 Reviewers agreed at journal 24 Apr, 2026 Reviewers agreed at journal 05 Apr, 2026 Reviewers invited by journal 05 Apr, 2026 Editor assigned by journal 27 Mar, 2026 Submission checks completed at journal 27 Mar, 2026 First submitted to journal 21 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9186315","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":618023237,"identity":"e6c8135c-8427-40a2-a1e5-1259f6f456b8","order_by":0,"name":"Charles Wanjiku","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIiWNgGAWjYDACCSB+AGEmHGxgkJADsQ48IKQlAaHFwhisJYFILQyMDQwViQ0MSCLYAP/s5mcfEirqEvtnNzw8OLNNIn1+2OGHQFvs5HQbcFhy55jxjIQzhxNn3DmQcHBjm0TuxttpBkAtycZmB7BrMZBIMGZIbDuQ23AjIeHgQ5CW2QkgLQcSt+HUkv6ZIfFfXe58qJZ0w9npHwhoyQHa0sCcuwGkBeiwBHnpHPy2SNzIKWZIOHa4fiNIy4xzEoYbpHMKDiQY4PYL/4z0zQwfauqM5W7kJH/sKauTl5+dvvnDhwo7OVxakABPAsSpYJUGBJWDADvEVPkGolSPglEwCkbBCAIAXf5tXjVvo50AAAAASUVORK5CYII=","orcid":"","institution":"Kenyatta University","correspondingAuthor":true,"prefix":"","firstName":"Charles","middleName":"","lastName":"Wanjiku","suffix":""}],"badges":[],"createdAt":"2026-03-21 14:08:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9186315/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9186315/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106959059,"identity":"c11c4134-3b6e-4247-a003-c410d0fd0de4","added_by":"auto","created_at":"2026-04-15 08:44:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1163860,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9186315/v1/bd315327-93d2-4bdd-9b96-b18cf876b345.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Health System and Socioeconomic Determinants of Delayed Initiation of Breastfeeding Among Cesarean Deliveries in Kenya: Analysis of the 2022 Kenya Demographic and Health Survey","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBreastfeeding is among the most effective and low-cost interventions available for reducing neonatal and infant mortality. The World Health Organization (WHO) recommends that all newborns be put to the breast within one hour of birth, a practice referred to as timely initiation of breastfeeding (TIBF). Early initiation facilitates the transfer of colostrum \u0026mdash; a nutrient-dense secretion rich in immunoglobulins, lactoferrin, and growth factors \u0026mdash; that establishes passive immunity, stimulates gastrointestinal maturation, and supports the mother-infant bond critical to continued exclusive breastfeeding (WHO, 2023; Ballard \u0026amp; Morrow, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Globally, failure to initiate breastfeeding within the first hour is associated with a significant increase in the risk of neonatal death, diarrheal disease, acute respiratory illness, and suboptimal cognitive development (Victora et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Edmond et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn sub-Saharan Africa, estimated rates of TIBF range from 50% to 75%, with considerable heterogeneity by country, delivery setting, and socioeconomic subgroup (UNICEF, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Among women who deliver by cesarean section (CS), these barriers are compounded by several physiological and procedural factors: delayed onset of lactogenesis secondary to surgical stress, routine separation of mother and infant during postoperative recovery, restricted mobility and postoperative pain, and the frequent absence of structured breastfeeding support protocols in maternity facilities (Hobbs et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Prior et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Rowe-Murray \u0026amp; Fisher, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCS rates in Kenya have risen markedly, from 6.5% in 2008\u0026ndash;2009 to 14.6% in 2022 (KNBS, 2023). This upward trend mirrors patterns across low- and middle-income countries, where the medicalization of childbirth has not been matched by equivalent investment in postnatal breastfeeding support. CS deliveries in Kenya are concentrated among wealthier, more educated, and urban women, raising questions about whether the socioeconomic predictors of CS also shape breastfeeding outcomes within this population (Kujabi et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExisting Kenyan literature on breastfeeding determinants has predominantly analyzed the general population, giving limited attention to CS-delivered women as a distinct subgroup whose determinants may differ substantially from the broader population. Furthermore, most prior studies apply conventional logistic regression to survey data, ignoring the hierarchical structure created by clustering of women within communities and health facilities. This produces downwardly biased standard errors and may inflate the statistical significance of individual-level predictors (Goldstein, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study addresses these gaps by analyzing health system and socioeconomic determinants of delayed TIBF specifically among CS-delivered women in Kenya using the 2022 KDHS, the most recent nationally representative dataset available. Multilevel logistic regression is employed to properly account for community-level clustering.\u003c/p\u003e \u003cp\u003eThe specific objectives were to: (i) estimate the prevalence of delayed TIBF among CS-delivered women; (ii) examine associations between health system factors \u0026mdash; facility type, facility level, ANC adequacy, and PNC within 48 hours \u0026mdash; and delayed TIBF; (iii) examine associations between socioeconomic factors \u0026mdash; maternal education, household wealth, and urban-rural residence \u0026mdash; and delayed TIBF; and (iv) quantify community-level clustering in delayed TIBF using the intraclass correlation coefficient (ICC).\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Global Significance of Timely Breastfeeding Initiation\u003c/h2\u003e \u003cp\u003eThe evidence linking early breastfeeding with neonatal survival is robust. In a landmark Ghanaian cohort study, Edmond et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) demonstrated that initiating breastfeeding within one hour of birth was associated with a 22% reduction in neonatal mortality compared to initiation at one to 23 hours, rising to 45% when compared with initiation after 24 hours. Subsequent analyses from South Asia and sub-Saharan Africa have broadly replicated these findings even after controlling for birth setting and maternal socioeconomic characteristics (Debes et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The biological mechanism is well established: colostrum contains secretory immunoglobulin A, lactoferrin, lysozymes, and growth factors that establish intestinal barrier function and confer passive humoral immunity before the neonate's own immune system matures (Ballard \u0026amp; Morrow, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGlobally, TIBF is one of eight core indicators for monitoring infant and young child feeding practices recommended by WHO and UNICEF (WHO/UNICEF, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The latest estimates indicate that only 44% of newborns worldwide are breastfed within the first hour of birth, with particularly low rates in facility-delivered births where institutional protocols frequently disrupt early skin-to-skin contact (UNICEF, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Victora et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Cesarean Section and Breastfeeding: Mechanisms and Evidence\u003c/h2\u003e \u003cp\u003eCS delivery is consistently associated with delayed breastfeeding initiation across diverse settings. A systematic review by Hobbs et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) identified 21 studies predominantly from high-income countries, finding that CS-delivered women were significantly less likely to initiate breastfeeding early compared to those who delivered vaginally. The pathways are multiple and interact. Regional or general anesthesia may cause maternal sedation and neonatal neurobehavioral depression, delaying rooting and suckling reflexes (Zanardo et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Postoperative pain, restricted maternal mobility, and intravenous lines physically impede the positioning required for early breastfeeding. Standard institutional practices frequently separate the mother and neonate during postoperative monitoring, interrupting the sensitive early period for skin-to-skin contact and breastfeeding (Rowe-Murray \u0026amp; Fisher, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEvidence from low- and middle-income countries is consistent with these findings. Shifraw et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) in Ethiopia found CS delivery was among the strongest predictors of delayed TIBF (AOR\u0026thinsp;=\u0026thinsp;3.2). Similar findings have been reported from Nigeria and Tanzania, where facility-level constraints including staff shortages and absent lactation counselors compound the physiological barriers (Ogbo et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Agho et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In Kenya, analysis of KDHS 2014 data confirmed that CS-delivered women were significantly less likely to initiate within one hour, though formal examination of predictors within the CS subgroup was not conducted (Kamunya et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A key limitation of much of this literature is the failure to distinguish elective from emergency CS, which may differ in their effects on immediate postoperative maternal-infant contact \u0026mdash; a gap that persists in the present study as well.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Health System Factors and Breastfeeding Outcomes\u003c/h2\u003e \u003cp\u003eThe health system context shapes TIBF through structural factors \u0026mdash; the availability of breastfeeding-friendly protocols \u0026mdash; and through the practices of individual providers. The Baby-Friendly Hospital Initiative (BFHI), launched by WHO and UNICEF in 1991, provides a framework for hospitals to support TIBF through ten steps that include immediate skin-to-skin contact, early breastfeeding support, and restriction of formula supplementation (WHO/UNICEF, 2009). Evidence from multiple LMICs suggests BFHI implementation is associated with higher rates of early initiation, though implementation fidelity is often incomplete in resource-constrained settings (Perez-Escamilla et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Kenya, the landscape of maternity facilities ranges from government district hospitals to private clinics and faith-based mission hospitals. Private facility delivery is associated with higher CS rates but not necessarily better breastfeeding support, partly because private facilities serve wealthier clients whose expectations of care may not prioritize early breastfeeding (Kujabi et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). ANC provides an opportunity for breastfeeding education and preparation prior to delivery, and PNC within 48 hours is the most proximate contact during which TIBF support can be reinforced. However, evidence on these associations specifically within the CS subgroup remains sparse, and the content quality of these contacts is not captured in household survey data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Socioeconomic Determinants of Breastfeeding Initiation\u003c/h2\u003e \u003cp\u003eThe relationship between socioeconomic status and TIBF is paradoxical in the African context. Unlike in high-income countries, wealthier and more educated women in sub-Saharan Africa are sometimes less likely to initiate breastfeeding promptly, partly because they are more likely to deliver by CS, have access to infant formula, and be exposed to breast milk substitute marketing (Victora et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Rollins et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Mgongo et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) in Tanzania found higher maternal education independently associated with delayed TIBF after controlling for delivery mode, attributing this to the greater likelihood of facility delivery among educated women and lower priority given to immediate breastfeeding in these settings. Household wealth has shown a similar inverse association with TIBF in several KDHS-based analyses (Kamunya et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Urban residence adds further ambiguity: urban women are more likely to have facility deliveries and access to trained staff, but are also more exposed to formula marketing and may face time pressures associated with employment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Methodological Gaps\u003c/h2\u003e \u003cp\u003eA recurring limitation in the breastfeeding literature is the use of single-level regression for outcomes that are clustered within communities and facilities. Mothers sharing a community share contextual exposures \u0026mdash; local norms, facility practices, community support structures \u0026mdash; that create within-cluster correlation in outcomes. Ignoring this underestimates standard errors, inflates significance, and obscures the contribution of contextual factors (Goldstein, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Recent studies applying multilevel models to breastfeeding in Nigeria and Ethiopia found ICC values of 5\u0026ndash;25%, indicating meaningful clustering (Ogbo et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Shifraw et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). None, however, restricted analysis to CS-delivered women as a distinct subgroup, where facility-level factors are likely to be more dominant. The present study addresses this gap directly.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Methods","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Data Source and Study Design\u003c/h2\u003e \u003cp\u003eThis study used data from the 2022 Kenya Demographic and Health Survey (KDHS 2022), a nationally representative cross-sectional household survey conducted by the Kenya National Bureau of Statistics (KNBS) with technical support from ICF International. The KDHS employs a stratified two-stage cluster sampling design, with enumeration areas as primary sampling units and households as secondary sampling units. Data were collected from women aged 15\u0026ndash;49 years on reproductive health, child health, nutrition, and health service utilization. Full methodological details are available in the survey report (KNBS, 2023).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Study Population and Sample Selection\u003c/h2\u003e \u003cp\u003eThe target population was women who had delivered by CS in the two years preceding the survey, had a live birth, and had complete breastfeeding timing data. Child age in months was calculated as the difference between the date of interview (v008) and date of birth (b3). CS delivery was identified using variable m17 (coded 1\u0026thinsp;=\u0026thinsp;cesarean). Breastfeeding timing was captured by variable m34, which records time to first breastfeeding using a combined hour-day scheme (0\u0026ndash;199\u0026thinsp;=\u0026thinsp;hours; 200\u0026ndash;299\u0026thinsp;=\u0026thinsp;days). Cases coded 994 (never breastfed), children who had died at interview (b5\u0026thinsp;=\u0026thinsp;0), and cases with missing values on delivery mode or breastfeeding timing were excluded. The final analytical sample comprised 536 mother-child pairs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Outcome Variable\u003c/h2\u003e \u003cp\u003e The outcome was delayed breastfeeding initiation, defined as first breastfeeding more than one hour after birth, consistent with WHO guidelines. A binary variable was constructed: 1\u0026thinsp;=\u0026thinsp;delayed (\u0026gt;\u0026thinsp;1 hour), 0\u0026thinsp;=\u0026thinsp;timely (\u0026le;\u0026thinsp;1 hour). Hour values were extracted for m34 codes 0\u0026ndash;199; day-coded values (200\u0026ndash;299) were converted to hours by multiplying (m34\u0026thinsp;\u0026minus;\u0026thinsp;200) \u0026times; 24. Among the 536 women, 339 (63.3%) experienced delayed initiation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Explanatory Variables\u003c/h2\u003e \u003cp\u003eHealth system variables included facility type (public vs. private/NGO/FBO), facility level (hospital vs. health centre or dispensary), ANC adequacy (\u0026ge;\u0026thinsp;4 vs. \u0026lt; 4 visits, consistent with the WHO focused ANC threshold applicable at the time of these births), and PNC within 48 hours (derived from variable m63).\u003c/p\u003e \u003cp\u003eSocioeconomic variables included maternal education (no education; primary; secondary and above), household wealth index (collapsed from five DHS quintiles into three groups: lower, middle, upper), and urban-rural residence.\u003c/p\u003e \u003cp\u003eChild-level covariates included birth size as reported by the mother (large/very large; average; small/very small), plurality (singleton vs. multiple), and birth order (first; second-third; fourth or higher).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Statistical Analysis\u003c/h2\u003e \u003cp\u003eSurvey-weighted proportions were calculated for all variables using the svyset command in Stata 17. Cross-tabulations with the Pearson chi-square design-based test examined bivariate associations. Unadjusted odds ratios (UOR) with 95% confidence intervals were estimated for each predictor using separate bivariate multilevel logistic regression models (melogit), with women nested within community clusters (v001) to account for clustering.\u003c/p\u003e \u003cp\u003eMultivariable analysis proceeded in three stages. A null multilevel model with no predictors estimated the baseline ICC using the formula ICC\u0026thinsp;=\u0026thinsp;τ\u0026sup2; / (τ\u0026sup2; + π\u0026sup2;/3), where π\u0026sup2;/3\u0026thinsp;=\u0026thinsp;3.29. Model 1 added health system predictors; Model 2 additionally included socioeconomic variables; Model 3 further included child-level covariates. Likelihood ratio tests compared nested models. Model fit was assessed using AIC and BIC. Survey weights (v005/1,000,000) were applied to descriptive analyses. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; borderline findings (0.05\u0026thinsp;\u0026le;\u0026thinsp;p\u0026thinsp;\u0026lt;\u0026thinsp;0.10) are also reported. All analyses were conducted in Stata/IC 17.0.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Ethical Considerations\u003c/h2\u003e \u003cp\u003e The 2022 KDHS was approved by the Kenya Medical Research Institute Ethics Review Committee and ICF's Institutional Review Board. All participants provided informed consent. The present analysis used anonymized, publicly available secondary data and required no additional ethical clearance.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Sample Characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents characteristics of the 536 CS-delivered women in the analytical sample. The mean child age was 11.7 months (SD\u0026thinsp;=\u0026thinsp;6.9), consistent with the restriction to births in the preceding 24 months. The vast majority of deliveries occurred in hospitals (92.9%), and in private or faith-based/NGO facilities (88.4%). Nearly three-quarters (73.9%) had adequate ANC (\u0026ge;\u0026thinsp;4 visits), and 88.1% received PNC within 48 hours. Most women had secondary or higher education (70.1%), and 59.1% were in the upper wealth category. Urban and rural residents were nearly equally distributed. Most children were singletons (95.7%), of average birth size (65.9%), and of first or second birth order (81.9%).\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\u003eCharacteristics of the Analytical Sample, CS-Delivered Women, KDHS 2022 (n\u0026thinsp;=\u0026thinsp;536)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWeighted %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTimely BF initiation (\u0026le;\u0026thinsp;1 hour)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelayed BF initiation (\u0026gt;\u0026thinsp;1 hour)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth System Factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility type: Public\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility type: Private/NGO/FBO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility level: Hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility level: Health centre/dispensary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANC adequate (\u0026ge;\u0026thinsp;4 visits)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNC within 48 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocioeconomic Factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation: No education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation: Primary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation: Secondary and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth: Lower quintiles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth: Middle quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth: Upper quintiles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild-level Factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth size: Large/very large\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth size: Average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth size: Small/very small\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth order: First\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth order: Second\u0026ndash;third\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth order: Fourth or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex of child: Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eBF\u0026thinsp;=\u0026thinsp;Breastfeeding; ANC\u0026thinsp;=\u0026thinsp;Antenatal Care; PNC\u0026thinsp;=\u0026thinsp;Postnatal Care. Weighted % derived from survey-weighted tabulations using v005/1,000,000. \u0026mdash; = not calculated for this subgroup.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate Analysis: Association Between Explanatory Variables and Delayed Breastfeeding Initiation Among CS-Delivered Women, KDHS 2022 (n\u0026thinsp;=\u0026thinsp;536)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDelayed BF Initiation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eHealth System Factors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility type\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (66.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate/NGO/FBO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e176 (37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298 (62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.43\u0026ndash;1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility level\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e183 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e315 (63.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth centre/dispensary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.44\u0026ndash;2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.950\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANC visits (adequacy)\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 4 visits (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 (64.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 4 visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147 (37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e249 (62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.60\u0026ndash;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNC within 48 hours\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (67.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\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\u003e176 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e296 (62.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u0026ndash;1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocioeconomic Factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal education\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (39.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (60.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (44.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u0026ndash;2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.626\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127 (33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e249 (66.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.48\u0026ndash;3.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.585\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold wealth\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower quintiles (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (40.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (42.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (57.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.46\u0026ndash;1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper quintiles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107 (33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210 (66.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u0026ndash;2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112 (39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e172 (60.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167 (66.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u0026ndash;2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild-level Factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth size\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal/large (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163 (38.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e264 (61.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall/very small\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87\u0026ndash;2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlurality\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingleton (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192 (37.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e321 (62.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (78.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.72\u0026ndash;6.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth order\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 (37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (62.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond\u0026ndash;third\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e178 (66.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.75\u0026ndash;1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFourth or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (56.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.40\u0026ndash;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eUOR\u0026thinsp;=\u0026thinsp;Unadjusted Odds Ratio; CI\u0026thinsp;=\u0026thinsp;Confidence Interval; ref. = reference category. UORs estimated using multilevel logistic regression (melogit) with women nested within community clusters. p-values from Wald chi2 tests. BF\u0026thinsp;=\u0026thinsp;Breastfeeding; ANC\u0026thinsp;=\u0026thinsp;Antenatal Care; PNC\u0026thinsp;=\u0026thinsp;Postnatal Care.\u003c/em\u003e \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\u003eMultilevel Logistic Regression Models for Delayed Breastfeeding Initiation Among CS-Delivered Women, KDHS 2022 (n\u0026thinsp;=\u0026thinsp;536)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNull Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 1 AOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 2 AOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 3 AOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep (Model 3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth system factors\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility type (private ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83 (0.43\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83 (0.42\u0026ndash;1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.79 (0.40\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility level (hospital ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 (0.45\u0026ndash;2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.08 (0.48\u0026ndash;2.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.13 (0.49\u0026ndash;2.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANC adequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95 (0.60\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.56\u0026ndash;1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.83 (0.50\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.461\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNC within 48h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80 (0.42\u0026ndash;1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75 (0.38\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.74 (0.37\u0026ndash;1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocioeconomic factors\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation (per category)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40 (0.93\u0026ndash;2.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.39 (0.90\u0026ndash;2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth (per category)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06 (0.77\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.06 (0.76\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26 (0.74\u0026ndash;2.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.25 (0.74\u0026ndash;2.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.408\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild-level factors\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall birth size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.57 (0.89\u0026ndash;2.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.80 (0.85\u0026ndash;9.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth order (per category)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94 (0.68\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRandom effects\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster variance (τ\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICC (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel fit\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog-likelihood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;352.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;350.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;348.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;345.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e713.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e714.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e714.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e739.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e752.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e766.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eAOR\u0026thinsp;=\u0026thinsp;Adjusted Odds Ratio; CI\u0026thinsp;=\u0026thinsp;Confidence Interval; ICC\u0026thinsp;=\u0026thinsp;Intraclass Correlation Coefficient; AIC\u0026thinsp;=\u0026thinsp;Akaike Information Criterion; BIC\u0026thinsp;=\u0026thinsp;Bayesian Information Criterion. All models estimated using melogit in Stata 17. \u0026dagger;p\u0026thinsp;\u0026lt;\u0026thinsp;0.10. Cluster variance and ICC reported from each respective model. Model 1\u0026thinsp;=\u0026thinsp;health system factors only; Model 2\u0026thinsp;=\u0026thinsp;health system\u0026thinsp;+\u0026thinsp;socioeconomic factors; Model 3\u0026thinsp;=\u0026thinsp;full model. Source: KDHS 2022.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Prevalence of Delayed Breastfeeding Initiation\u003c/h2\u003e \u003cp\u003eOverall, 339 of 536 women (63.3%; weighted 66.1%) experienced delayed breastfeeding initiation. The mean time to first breastfeeding was 61.5 hours (SD\u0026thinsp;=\u0026thinsp;57.4), ranging from immediate initiation to 504 hours. This high prevalence across all subgroups indicates that delay is normative rather than exceptional among CS-delivered women in Kenya.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Bivariate Associations\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents bivariate associations. No predictor reached statistical significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in bivariate analysis. Among health system factors, the proportions of delayed initiation were nearly identical across facility type, facility level, ANC adequacy, and PNC receipt. Among socioeconomic factors, a higher proportion of delayed initiators had secondary or above education (66.2% vs. 60.9% for no education) and were in the upper wealth category (66.2% vs. 60.0% for lower wealth), though neither was significant. Urban residence trended toward higher odds of delay (UOR\u0026thinsp;=\u0026thinsp;1.37, 95% CI: 0.89\u0026ndash;2.11, p\u0026thinsp;=\u0026thinsp;0.158). Among child-level factors, multiple birth showed the largest unadjusted association (UOR\u0026thinsp;=\u0026thinsp;2.17, 95% CI: 0.72\u0026ndash;6.59, p\u0026thinsp;=\u0026thinsp;0.171).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Multilevel Model Results\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents results across all four models. The null model ICC was 18.8% (τ\u0026sup2; = 0.765), indicating that approximately one-fifth of the total variation in delayed initiation was attributable to community-level differences, confirming the appropriateness of the multilevel approach.\u003c/p\u003e \u003cp\u003eIn Model 1 (health system factors only), none of the four predictors reached significance. Private facility delivery was associated with lower odds of delay (AOR\u0026thinsp;=\u0026thinsp;0.83, 95% CI: 0.43\u0026ndash;1.59, p\u0026thinsp;=\u0026thinsp;0.569), and PNC within 48 hours was also in the protective direction (AOR\u0026thinsp;=\u0026thinsp;0.80, 95% CI: 0.42\u0026ndash;1.54, p\u0026thinsp;=\u0026thinsp;0.488), though neither was significant. The overall model Wald chi2 was 0.82 (p\u0026thinsp;=\u0026thinsp;0.936).\u003c/p\u003e \u003cp\u003eModel 2 added socioeconomic variables. Education showed a positive borderline association (AOR\u0026thinsp;=\u0026thinsp;1.40, 95% CI: 0.93\u0026ndash;2.11, p\u0026thinsp;=\u0026thinsp;0.103), suggesting that higher education was associated with greater odds of delay, paradoxically. The likelihood ratio test comparing Model 2 with Model 1 was not significant (LR chi2\u0026thinsp;=\u0026thinsp;5.86, p\u0026thinsp;=\u0026thinsp;0.119), and AIC marginally increased.\u003c/p\u003e \u003cp\u003eIn the full Model 3, multiple birth had the strongest association with delayed initiation (AOR\u0026thinsp;=\u0026thinsp;2.80, 95% CI: 0.85\u0026ndash;9.30, p\u0026thinsp;=\u0026thinsp;0.092), approaching but not reaching significance. Small birth size trended positive (AOR\u0026thinsp;=\u0026thinsp;1.57, 95% CI: 0.89\u0026ndash;2.75, p\u0026thinsp;=\u0026thinsp;0.118). Education retained a borderline positive association (AOR\u0026thinsp;=\u0026thinsp;1.39, p\u0026thinsp;=\u0026thinsp;0.140). The LR test comparing Model 3 to Model 2 was not significant (p\u0026thinsp;=\u0026thinsp;0.148), and the BIC increased from 752.6 to 766.2, confirming that the simpler Model 1 was the most parsimonious fit.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThis study examined health system and socioeconomic determinants of delayed breastfeeding initiation among CS-delivered women in Kenya using nationally representative data. The central finding \u0026mdash; that 63.3% of this population experienced delayed initiation \u0026mdash; places Kenya among the countries with the highest rates of delayed TIBF in the CS subgroup, comparable to rates of 55\u0026ndash;70% reported from Ethiopia and Nigeria (Shifraw et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ogbo et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This prevalence is substantially higher than national estimates for all delivery modes, underscoring the particular vulnerability of CS-delivered women to breastfeeding disruption.\u003c/p\u003e \u003cp\u003eThe null model ICC of 18.8% is both a methodological and substantive finding. Methodologically, it confirms that conventional logistic regression would have underestimated standard errors and potentially produced spuriously significant individual-level associations. Substantively, it means that nearly one-fifth of the variation in delayed initiation is attributable to community-level factors \u0026mdash; where a woman lives or delivers may matter as much as who she is. Local breastfeeding norms, community peer support, the practices of specific maternity facilities, and the attitudes of healthcare workers may account for this clustering in ways that individual-level survey data cannot fully capture. The ICC increased slightly across models (from 18.8% in the null to 21.6% in Model 3), suggesting that none of the measured individual-level variables fully explained the community-level variance.\u003c/p\u003e \u003cp\u003eThe absence of statistically significant individual-level predictors requires careful interpretation rather than dismissal. The study was likely underpowered to detect moderate associations given n\u0026thinsp;=\u0026thinsp;536 and the restricted variation in several key predictors: 92.9% of deliveries occurred in hospitals and 88.4% in private facilities, leaving very little facility-type variability to drive associations. This reflects the socioeconomic patterning of CS delivery in Kenya rather than a true null finding \u0026mdash; CS is concentrated in a relatively homogeneous subgroup of wealthier, better-educated, facility-delivered women.\u003c/p\u003e \u003cp\u003eThe borderline positive association between higher education and delayed initiation (AOR\u0026thinsp;=\u0026thinsp;1.39, p\u0026thinsp;=\u0026thinsp;0.140) is consistent with the paradoxical pattern noted in sub-Saharan African literature. More educated women are more likely to have elective CS, more likely to be exposed to formula marketing, and may be less embedded in community breastfeeding support networks. They may also hold different postpartum care expectations that do not prioritize immediate breastfeeding. This finding adds to growing evidence that educational interventions alone are insufficient to improve TIBF among CS-delivered women (Mgongo et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ogbo et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMultiple birth showed the strongest, albeit non-significant, association (AOR\u0026thinsp;=\u0026thinsp;2.80, p\u0026thinsp;=\u0026thinsp;0.092). The wide confidence interval (0.85\u0026ndash;9.30) reflects the small number of multiple births (n\u0026thinsp;=\u0026thinsp;23). Clinically, the magnitude is plausible: multiple births delivered by CS typically involve separation of infants from the mother for observation or neonatal intensive care, directly impeding early breastfeeding. These mothers constitute a particularly high-risk group warranting targeted postnatal lactation support.\u003c/p\u003e \u003cp\u003eThe lack of significant association between ANC adequacy, PNC within 48 hours, and delayed initiation may reflect the inability of the KDHS to capture the content and quality of these contacts. A woman may have attended four or more ANC visits without receiving meaningful breastfeeding counseling. Within the CS delivery context, immediate postoperative management practices may be more determinative than prenatal preparation, and these are not captured in household survey data.\u003c/p\u003e \u003cp\u003eThese findings have clear policy implications. Given the high prevalence and meaningful community-level clustering, facility-level interventions are likely to be more effective than individual-level education programs. Implementing and scaling the BFHI in Kenyan hospitals, with specific adaptations for CS deliveries, would directly address the primary mechanism of delay: postoperative separation and lack of lactation support. This includes facilitating skin-to-skin contact in the recovery room, training nursing staff in postoperative breastfeeding positioning, and establishing dedicated lactation counselor roles in maternity facilities.\u003c/p\u003e \u003cp\u003eThe study has several limitations. The cross-sectional design precludes causal inference, and breastfeeding timing data rely on maternal recall, which may be subject to telescoping bias. The KDHS does not distinguish between elective and emergency CS, does not capture facility-level practices or BFHI certification status, and the sample size of CS-delivered women limits statistical power. Future research using facility-based data, qualitative methods, and prospective designs is needed to further characterize the mechanisms driving delayed TIBF in this population.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eDelayed breastfeeding initiation affects nearly two-thirds of CS-delivered women in Kenya, making it a pervasive rather than exceptional problem in this population. The multilevel analysis revealed significant community-level clustering (ICC\u0026thinsp;=\u0026thinsp;18.8%), indicating that contextual and facility-level factors are important drivers of this outcome even if they cannot be fully characterized using household survey data. No individual-level predictor reached statistical significance in the adjusted models, though multiple birth and higher maternal education showed borderline associations warranting further investigation.\u003c/p\u003e \u003cp\u003eThe findings call for a policy shift from a focus on individual maternal characteristics to the systemic conditions under which CS deliveries occur. Strengthening maternity facility protocols to support immediate postoperative breastfeeding, scaling BFHI implementation with CS-specific adaptations, and investing in postnatal lactation support services are the most actionable levers for reducing delayed TIBF among this growing and underserved population of Kenyan mothers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cb\u003eThe ethics declaration\u003c/b\u003e \u003c/p\u003e \u003cp\u003e This research was performed in accordance with the principles of the Declaration of Helsinki. The study used secondary data from the 2022 Kenya Demographic and Health Survey (KDHS), which is publicly available through the DHS Program website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dhsprogram.com\u003c/span\u003e\u003cspan address=\"https://dhsprogram.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Ethical approval for the original KDHS data collection was obtained from the ICF Institutional Review Board (Project Number: 132989) and the Kenya Medical Research Institute (KEMRI) Scientific and Ethics Review Unit (Protocol Number: KEMRI/RES/7/3/1). All survey respondents provided written informed consent before participation, including consent for anonymized data to be used in future research. Since this analysis involved de-identified, publicly available data, it did not require further ethical clearance.\u003c/p\u003e\u003cp\u003e \u003ch2\u003eHuman Ethics and Consent to Participate\u003c/h2\u003e \u003cp\u003e All participants in the original surveys provided written informed consent before participation, including consent for anonymized data to be used in future research. As this study involved secondary analysis of fully anonymized, publicly available data, it was exempt from additional ethical review. Human Ethics and Consent to Participate declarations: not applicable for this secondary analysis\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent to Publish\u003c/h2\u003e \u003cp\u003eConsent to Publish declaration: not applicable. This manuscript does not contain any individual person's data in any form (including individual details, images, or videos) that would require consent for publication. All data presented are aggregated, anonymized, and publicly available from the Demographic and Health Surveys (DHS) Program\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests. No financial or non-financial interests that could be construed as influencing the research or interpretation of the findings exist.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors received no financial support for the research, authorship, and/or publication of this article. This study was conducted using publicly available data from the Demographic and Health Surveys (DHS) Program, and all work was performed as part of the authors' academic affiliations without external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eCharles, John: Conceptualization, Methodology, Software, Formal analysis, Data curation, Visualization, Writing \u0026ndash; original draft. Mary, Charles: Conceptualization, Methodology, Investigation, Validation, Writing \u0026ndash; review \u0026amp; editing, Project administration. Charles, erick: Resources, Validation, Writing \u0026ndash; review \u0026amp; editing, Supervision. All authors have read and approved the final manuscript\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are available in the Demographic and Health Surveys (DHS) Program repository and the Kenya National Bureau of Statistics. [https://statistics.knbs.or.ke/nada/index.php/catalog/128](https:/statistics.knbs.or.ke/nada/index.php/catalog/128) .Alternatively, the official DHS Program website for the Kenya 2022 KDHS dataset is: [https://www.dhsprogram.com/data/available-datasets.cfm](https:/www.dhsprogram.com/data/available-datasets.cfm) Access to the data requires free registration and approval of a research proposal by The DHS Program, in accordance with the data use agreements with the Government of Kenya. The data are publicly available for legitimate research purposes. The authors confirm that they did not have any special access privileges to these data\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgho KE, Dibley MJ, Odiase JI, Ogujii SM. Determinants of exclusive breastfeeding in Nigeria. BMC Pregnancy Childbirth. 2011;11:2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2393-11-2\u003c/span\u003e\u003cspan address=\"10.1186/1471-2393-11-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBallard O, Morrow AL. Human milk composition: Nutrients and bioactive factors. Pediatr Clin North Am. 2013;60(1):49\u0026ndash;74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pcl.2012.10.002\u003c/span\u003e\u003cspan address=\"10.1016/j.pcl.2012.10.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDebes AK, Kohli A, Walker N, Edmond K, Mullany LC. Time to initiation of breastfeeding and neonatal mortality and morbidity: A systematic review. BMC Public Health. 2013;13(Suppl 3):S19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2458-13-S3-S19\u003c/span\u003e\u003cspan address=\"10.1186/1471-2458-13-S3-S19\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEdmond KM, Zandoh C, Quigley MA, Amenga-Etego S, Owusu-Agyei S, Kirkwood BR. Delayed breastfeeding initiation increases risk of neonatal mortality. Pediatrics. 2006;117(3):e380\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1542/peds.2005-1496\u003c/span\u003e\u003cspan address=\"10.1542/peds.2005-1496\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoldstein H. Multilevel Statistical Models. 4th ed. Wiley; 2011. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/9780470973394\u003c/span\u003e\u003cspan address=\"10.1002/9780470973394\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHobbs AJ, Mannion CA, McDonald SW, Brockway M, Tough SC. The impact of caesarean section on breastfeeding initiation, duration and difficulties in the first four months postpartum. BMC Pregnancy Childbirth. 2016;16:90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12884-016-0876-1\u003c/span\u003e\u003cspan address=\"10.1186/s12884-016-0876-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamunya R, Ndinda C, Muthoni E. Factors associated with timely initiation of breastfeeding in Kenya: Analysis of the 2014 Kenya Demographic and Health Survey. Afr J Food Agric Nutr Dev. 2021;21(3):17654\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.18697/ajfand.98.20044\u003c/span\u003e\u003cspan address=\"10.18697/ajfand.98.20044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKenya National Bureau of Statistics [KNBS]. (2023). Kenya Demographic and Health Survey 2022. KNBS. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.knbs.or.ke/reports/kdhs-2022/\u003c/span\u003e\u003cspan address=\"https://www.knbs.or.ke/reports/kdhs-2022/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKujabi ML, Petersen TG, Hutchinson JN, Byberg S. Factors associated with caesarean section in sub-Saharan Africa: A systematic review. Acta Obstet Gynecol Scand. 2021;100(4):590\u0026ndash;604. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/aogs.14064\u003c/span\u003e\u003cspan address=\"10.1111/aogs.14064\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMgongo M, Hussein TH, Stray-Pedersen B, Vangen S, Msuya SE, Wandel M. Prevalence and predictors of exclusive breastfeeding among women in Kilimanjaro region, Northern Tanzania. Int Breastfeed J. 2017;12:2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13006-016-0091-3\u003c/span\u003e\u003cspan address=\"10.1186/s13006-016-0091-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOgbo FA, Dhami MV, Awosemo AO, Olusanya BO, Page A. Regional prevalence and determinants of exclusive breastfeeding in India. Int Breastfeed J. 2019;14:20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13006-019-0214-0\u003c/span\u003e\u003cspan address=\"10.1186/s13006-019-0214-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerez-Escamilla R, Martinez JL, Segura-Perez S. Impact of the Baby-Friendly Hospital Initiative on breastfeeding and child health outcomes: A systematic review. Maternal Child Nutr. 2016;12(3):402\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mcn.12294\u003c/span\u003e\u003cspan address=\"10.1111/mcn.12294\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrior E, Santhakumaran S, Gale C, Philipps LH, Modi N, Hyde MJ. Breastfeeding after cesarean delivery: A systematic review and meta-analysis. Am J Clin Nutr. 2012;95(5):1113\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3945/ajcn.111.030254\u003c/span\u003e\u003cspan address=\"10.3945/ajcn.111.030254\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRollins NC, Bhandari N, Hajeebhoy N, Horton S, Lauer JM, Martines JC, Piwoz EG, Richter LM, Victora CG. Why invest, and what it will take to improve breastfeeding practices? Lancet. 2016;387(10017):491\u0026ndash;504. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(15)01044-2\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(15)01044-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRowe-Murray HJ, Fisher JRW. Baby friendly hospital practices: Cesarean section is a persistent barrier to early initiation of breastfeeding. Birth. 2002;29(2):124\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1046/j.1523-536X.2002.00172.x\u003c/span\u003e\u003cspan address=\"10.1046/j.1523-536X.2002.00172.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShifraw T, Worku A, Berhane Y. Factors associated with exclusive breastfeeding practices of urban women in Addis Ababa public health centers, Ethiopia. Int Breastfeed J. 2018;10:22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13006-015-0048-4\u003c/span\u003e\u003cspan address=\"10.1186/s13006-015-0048-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUNICEF. (2021). Breastfeeding: A mother's gift for every child. UNICEF. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.unicef.org/media/55601/file/UNICEF_Breastfeeding_A_Mothers_Gift_for_Every_Child.pdf\u003c/span\u003e\u003cspan address=\"https://www.unicef.org/media/55601/file/UNICEF_Breastfeeding_A_Mothers_Gift_for_Every_Child.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVictora CG, Bahl R, Barros AJD, Franca GVA, Horton S, Krasevec J, Murch S, Sankar MJ, Walker N, Rollins NC. Breastfeeding in the 21st century: Epidemiology, mechanisms, and lifelong effect. Lancet. 2016;387(10017):475\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(15)01024-7\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(15)01024-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. (2016). WHO recommendations on antenatal care for a positive pregnancy experience. WHO. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789241549912\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789241549912\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. (2023). Breastfeeding: Key facts. WHO. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/breastfeeding\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/breastfeeding\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization \u0026amp; United Nations Children's Fund. (2009). Baby-friendly hospital initiative: Revised, updated and expanded for integrated care. WHO. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789241594967\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789241594967\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization \u0026amp; United Nations Children's Fund. (2021). Indicators for assessing infant and young child feeding practices. WHO. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240025257\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789240025257\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZanardo V, Svegliado G, Cavallin F, Giustardi A, Cosmi E, Litta P, Trevisanuto D. Elective cesarean delivery: Does it have a negative effect on breastfeeding? Birth. 2010;37(4):275\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1523-536X.2010.00421.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1523-536X.2010.00421.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"international-breastfeeding-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ibfj","sideBox":"Learn more about [International Breastfeeding Journal](http://internationalbreastfeedingjournal.biomedcentral.com/)","snPcode":"13006","submissionUrl":"https://submission.nature.com/new-submission/13006/3","title":"International Breastfeeding Journal","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"breastfeeding initiation, cesarean section, multilevel analysis, postnatal care","lastPublishedDoi":"10.21203/rs.3.rs-9186315/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9186315/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTimely initiation of breastfeeding within one hour of birth reduces neonatal mortality and supports optimal child development. Women who deliver by cesarean section (CS) face disproportionate barriers to early breastfeeding, yet the determinants of these delays remain poorly characterized in Kenya.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo examine health system and socioeconomic determinants of delayed breastfeeding initiation among CS-delivered women in Kenya using nationally representative data from the 2022 Kenya Demographic and Health Survey (KDHS 2022).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe analytical sample comprised 536 women who delivered by CS in the two years preceding the survey, had a live birth, and had valid breastfeeding timing data. Delayed initiation was defined as first breastfeeding occurring more than one hour after birth. Multilevel logistic regression models were used to account for community-level clustering. Predictors included facility type, facility level, antenatal care (ANC) adequacy, postnatal care (PNC) within 48 hours, maternal education, household wealth, urban-rural residence, birth size, plurality, and birth order.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong CS-delivered women, 63.3% experienced delayed breastfeeding initiation (weighted: 66.1%). The intraclass correlation coefficient from the null multilevel model was 18.8%, confirming significant community-level clustering. In the fully adjusted model, no predictor reached statistical significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Multiple birth showed the strongest borderline association (AOR\u0026thinsp;=\u0026thinsp;2.80; 95% CI: 0.85\u0026ndash;9.30; p\u0026thinsp;=\u0026thinsp;0.092). Higher education trended toward increased odds of delay (AOR\u0026thinsp;=\u0026thinsp;1.39; 95% CI: 0.90\u0026ndash;2.15; p\u0026thinsp;=\u0026thinsp;0.140). Model fit did not improve significantly with addition of socioeconomic or child-level variables.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eDelayed breastfeeding initiation is highly prevalent among CS-delivered women in Kenya. Meaningful community-level clustering suggests that facility practices and contextual factors are important drivers. Targeted postnatal breastfeeding support protocols for CS mothers, including Baby-Friendly Hospital Initiative adaptations, are urgently needed.\u003c/p\u003e","manuscriptTitle":"Health System and Socioeconomic Determinants of Delayed Initiation of Breastfeeding Among Cesarean Deliveries in Kenya: Analysis of the 2022 Kenya Demographic and Health Survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-10 20:52:44","doi":"10.21203/rs.3.rs-9186315/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"22673938299755142725399060059131441352","date":"2026-04-25T02:41:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"149283473471762461715928934830236150051","date":"2026-04-24T19:23:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"263313472404744177758469829435861398014","date":"2026-04-06T01:51:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-06T01:48:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-27T11:40:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-27T11:39:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Breastfeeding Journal","date":"2026-03-21T14:03:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-breastfeeding-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ibfj","sideBox":"Learn more about [International Breastfeeding Journal](http://internationalbreastfeedingjournal.biomedcentral.com/)","snPcode":"13006","submissionUrl":"https://submission.nature.com/new-submission/13006/3","title":"International Breastfeeding Journal","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7a48aae2-1eb8-4687-a5c6-9cffe3c08953","owner":[],"postedDate":"April 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-10T20:52:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-10 20:52:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9186315","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9186315","identity":"rs-9186315","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}