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Showing papers by "Samuel Iddi published in 2023"


Journal ArticleDOI
TL;DR: In this article , the association between healthy housing and child morbidity across six countries in sub-Saharan Africa was assessed using Demographic and Health Survey (DHS) data for six countries where the most recent survey collected health outcome data on child diarrhoea, acute respiratory illness, and fever.
Abstract: The connection between healthy housing status and health is well established. The quality of housing plays a significant role in infectious and non-communicable as well as vector-borne diseases. The global burden of disease attributable to housing is considerable with millions of deaths arising from diarrheal and respiratory diseases annually. In sub-Saharan Africa (SSA), the quality of housing remains poor although improvements have been documented. There is a general dearth of comparative analysis across several countries in the sub-region. We assess in this study, the association between healthy housing and child morbidity across six countries in SSA.We use the Demographic and Health Survey (DHS) data for six countries where the most recent survey collected health outcome data on child diarrhoea, acute respiratory illness, and fever. The total sample size of 91,096 is used in the analysis (representing 15, 044 for Burkina Faso, 11, 732 for Cameroon, 5, 884 for Ghana, 20, 964 for Kenya, 33, 924 for Nigeria, and 3,548 for South Africa). The key exposure variable is healthy housing status. We control for various factors associated with the three childhood health outcomes. These include quality housing status, residency (rural/urban), age of the head of the household, mother's education, mother's BMI status, marital status, mother's age, and religious status. Others include the child's gender, age, whether the child is from multiple or single births, and breastfeeding status. Inferential analysis using survey-weighted logistic regression is employed.Our findings indicate that housing is an important determinant of the three outcomes investigated. Compared to unhealthier housing, healthy housing status was found to be associated with reduced odds of diarrhoea in Cameroon [Healthiest: aOR = 0.48, 95% CI, (0.32,0.71), healthier: aOR = 0.50, 95% CI,(0.35,0.70), Healthy: aOR = 0.60, 95% CI, (0.44,0.83), Unhealthy: aOR = 0.60, 95% CI, (0.44,0.81)], Kenya [Healthiest: aOR = 0.68, 95% CI, (0.52,0.87), Healtheir: aOR = 0.79, 95% CI, (0.63,0.98), Healthy: aOR = 0.76, 95% CI, (0.62,0.91)], South Africa[Healthy: aOR = 0.41, 95% CI, (0.18, 0.97)], and Nigeria [Healthiest: aOR = 0.48, 95% CI,(0.37,0.62), Healthier: aOR = 0.61, 95% CI,(0.50,0.74), Healthy: aOR = 0.71, 95%CI, (0.59,0.86), Unhealthy: aOR = 0.78, 95% CI, (0.67,0.91)], and reduced odds of Acute Respiratory Infection in Cameroon [Healthy: aOR = 0.72, 95% CI,(0.54,0.96)], Kenya [Healthiest: aOR = 0.66, 95% CI, (0.54,0.81), Healthier: aOR = 0.81, 95% CI, (0.69,0.95)], and Nigeria [Healthiest: aOR = 0.69, 95% CI, (0.56,0.85), Healthier: aOR = 0.72, 95% CI, (0.60,0.87), Healthy: aOR = 0.78, 95% CI, (0.66,0.92), Unhealthy: aOR = 0.80, 95% CI, (0.69,0.93)] while it was associated with increased odds in Burkina Faso [Healthiest: aOR = 2.45, 95% CI, (1.39,4.34), Healthy: aOR = 1.55, 95% CI, (1.09,2.20)] and South Africa [Healthy: aOR = 2.36 95% CI, (1.31, 4.25)]. In addition, healthy housing was significantly associated with reduced odds of fever among children in all countries except South Africa [Healthiest: aOR = 2.09, 95% CI, (1.02, 4.29)] where children living in the healthiest homes had more than double the odds of having fever. In addition, household-level factors such as the age of the household head, and place of residence were associated with the outcomes. Child-level factors such as breastfeeding status, age, and sex, and maternal-level factors such as education, age, marital status, body mass index (BMI), and religion were also associated with the outcomes.The dissimilarity of findings across similar covariates and the multiple relations between healthy housing and under 5 morbidity patterns show unequivocally the heterogeneity that exists across African countries and the need to account for different contexts in efforts to seek an understanding of the role of healthy housing in child morbidity and general health outcomes.

Journal ArticleDOI
TL;DR: In this paper , the effect of patient support group intervention on blood pressure management and the potential moderating effect of multimorbidity among low- and middle-income patients with hypertension in Kenya was evaluated.
Abstract: Introduction: Patient support group interventions have been widely used to manage chronic diseases in Kenya. However, the potential benefits of these groups on patient health outcomes, and how this is influenced by multimorbidity, have not been rigorously evaluated. Objective: We assessed the effect of a patient support group intervention on blood pressure (BP) management and the potential moderating effect of multimorbidity among low- and middle-income patients with hypertension in Kenya. Methods: We analysed data from a non-randomized, quasi-experimental study of 410 patients with hypertension on a home-based self-management program conducted from September 2019 to September 2020. The program included the formation and participation in patient support groups. Using a modified STEPS questionnaire, data were collected on BP, anthropometry and other measurements at enrolment and after 12 months of follow-up. Multimorbidity was defined as the simultaneous presence of hypertension and at least one or more related conditions with similar pathophysiology (concordant multimorbidity) or unrelated chronic conditions (discordant multimorbidity). Propensity score (PS) weighting was used to adjust for baseline differences among 243 patients who participated in the support groups and 167 who did not. We estimated the effects of patient support groups and moderating effects of multimorbidity on BP management using multivariable ordinary linear regression weighted by PS. Findings: Participation in support groups significantly reduced systolic BP by 5.4 mmHg compared to non-participation in the groups [β = –5.4; 95% CI –1.9 to –8.8]. However, among participants in the support group intervention, the mean systolic BP at follow-up assessment for those with concordant multimorbidity was 8.8 mmHg higher than those with no multimorbidity [β = 8.8; 95% CI 0.8 to 16.8]. Conclusion: Although patient support groups are potentially important adjuncts to home-based self-care, multimorbidity attenuates their effectiveness. There is a need to tailor patient support group interventions to match the needs of the people living with multimorbidity in low- and middle-income settings in Kenya.

Journal ArticleDOI
TL;DR: In this article , the authors compared structured diabetes self-management education to usual care, in adults with type 2 diabetes, in low-resource settings, and the intervention effect was assessed with linear mixed models.
Abstract: Abstract Background In high-resource settings, structured diabetes self-management education is associated with improved outcomes but the evidence from low-resource settings is limited and inconclusive. Aim To compare, structured diabetes self-management education to usual care, in adults with type 2 diabetes, in low-resource settings. Research design and methods. Design Single-blind randomised parallel comparator controlled multi-centre trial. Adults (> 18 years) with type 2 diabetes from two hospitals in urban Ghana were randomised 1:1 to usual care only, or usual care plus a structured diabetes self-management education program. Randomisation codes were computer-generated, and allotment concealed in opaque numbered envelopes. The intervention effect was assessed with linear mixed models. Main outcome: Change in HbA1c after 3-month follow-up. Primary analysis involved all participants. Clinicaltrial.gov identifier:NCT04780425, retrospectively registered on 03/03/2021. Results Recruitment: 22 nd until 29 th January 2021. We randomised 206 participants (69% female, median age 58 years [IQR: 49–64], baseline HbA1c median 64 mmol/mol [IQR: 45–88 mmol/mol],7.9%[IQR: 6.4–10.2]). Primary outcome data was available for 79 and 80 participants in the intervention and control groups, respectively. Reasons for loss to follow-up were death (n = 1), stroke(n = 1) and unreachable or unavailable (n = 47). A reduction in HbA1c was found in both groups; -9 mmol/mol [95% CI: -13 to -5 mmol/mol], -0·9% [95% CI: -1·2% to -0·51%] in the intervention group and -3 mmol/mol [95% CI -6 to 1 mmol/mol], -0·3% [95% CI: -0·6% to 0.0%] in the control group. The intervention effect was 1 mmol/mol [95%CI:-5 TO 8 p = 0.726]; 0.1% [95% CI: -0.5, 0.7], p = 0·724], adjusted for site, age, and duration of diabetes. No significant harms were observed. Conclusion In low-resource settings, diabetes self-management education might not be associated with glycaemic control. Clinician’s expectations from diabetes self-management education must therefore be guarded.