Socioeconomic correlates of trauma: An analysis of emergency ward patients in Yaoundé, Cameroon

Kacker, Seema; Bishai, David; Mballa, Georges Alain Etoundi; Monono, Martin Ekeke; Schneider, Eric B.; Ngamby, Marquise Kouo; Hyder, Adnan A.; Juillard, Catherine

doi:10.1016/j.injury.2015.12.011

Cited by 19 publications

(7 citation statements)

References 16 publications

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“…Compared to those in urban settings and of higher socio-economic status, women in rural settings, and those of lower socio-economic standing, tend to be more vulnerable to adverse physical, mental, obstetric and gynecological health outcomes [22,[43][44][45][46][47][48][49][50][51][52][53]. They often report poorer self-rated mental and physical health [43,52], have less access to necessary obstetric care [22,46,47,50], and have higher rates of trauma and mortality [23,24,46,[54][55][56][57][58][59]. Poor sexual functioning may further exacerbate these and other adverse health conditions in this subpopulation.…”

Section: Discussionmentioning

confidence: 99%

“I did not know it was a medical condition”: Predictors, severity and help seeking behaviors of women with female sexual dysfunction in the Volta region of Ghana

et al. 2020

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ObjectivesThe study's main objective was to describe the prevalence and severity of female sexual dysfunction (FSD) amongst a group of Ghanaian women in the outpatient setting of the predominantly rural Volta region of Ghana. Additionally we determine the predictors of FSD severity and care seeking behaviors of women with the condition. OPEN ACCESSCitation: Ibine B, Sefakor Ametepe L, Okere M, Anto-Ocrah M (2020) "I did not know it was a medical condition": Predictors, severity and help seeking behaviors of women with female sexual dysfunction in the Volta region of Ghana. PLoS ONE 15(1): e0226404. https://doi.org/10. ResultsFSD Prevalence: Out of 407 women approached, 300 (83.8%) agreed and consented to participate in the study. The prevalence of FSD was 48.3% (n = 145). Compared to those without FSD, over a third of the FSD women resided in rural settings (37.90% vs 20.60%; p = 0.001) and tended to be multiparous, with a significantly greater proportion having at least three children (31.70% vs 18.10%; p = 0.033).FSD Severity: Over a quarter of the sample (27.6%, n = 40) met the cut-off for moderate to severe FSD. In age-adjusted models, lubrication disorder was associated with 45 times the odds of moderate/severe FSD (age-adj. OR: 45.38, 95% CI: 8.37, 246.00; p<0.001), pain with 17times the odds (age-adj. OR: 17.18, 95% CI: 4.50, 65.50; p<0.001) and satisfaction almost 5times the odds (age-adj. OR: 4.69, 95% CI: 1.09, 20.2; p = 0.04). Compared to those with 1-3 children, nulliparous women had 3.5 times higher odds of moderate/severe sexual dysfunction as well (age-adj. OR:3.51, 95% CI:1.37,8.98; p = 0.009).FSD-related Health Seeking Behaviors: Statistically significant predictors of FSD-related care seeking included having FSD of pain disorder (age-adj. OR: 5.91, 95% CI:1.29, 27.15; p = 0.02), having �4 children (age-adj. OR: 6.29, 95%CI: 1.53, 25.76; p = 0.01). Of those who sought help, seven in 10 sought formal help from a healthcare provider, with General Practitioners preferred over Gynecologist. About one in 3 (31.3%) who did not seek help indicated that they did not know their sexual dysfunction was a medical condition, over a quarter (28.9%) "thought it was normal" to have FSD, and interestingly, 14.1% did not think a medical provider would be able to provide them with assistance.

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Section: Discussionmentioning

confidence: 99%

“I did not know it was a medical condition”: Predictors, severity and help seeking behaviors of women with female sexual dysfunction in the Volta region of Ghana

et al. 2020

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“…The DHS assessed the performance of the Wealth Index in distinguishing different economic groups based on variables known or suspected to be associated with economic status, including fertility rates, use of medical prenatal care, child mortality rates, rates of childhood stunting, and education levels [40]. Then, the DHS and subsequently many other research groups began to use the Wealth Index model in studies aimed at measuring health disparities which over time continued the validation process [35, 36, 37, 42]. Our work in Cameroon and our collaborators’ work in Ghana will continue this process for the EconomicClusters model.…”

Section: Discussionmentioning

confidence: 99%

Optimization and validation of the EconomicClusters model for facilitating global health disparities research: Examples from Cameroon and Ghana

2019

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Health disparities research in low- and middle-income countries (LMICs) is hampered by the difficulty of measuring economic status in low-resource settings. We previously developed the EconomicClusters k-medoids clustering-based algorithm for defining population-specific economic models based on few Demographic and Health Surveys (DHS) assets. The algorithm previously defined a twenty-group economic model for Cameroon. The aims of this study are to optimize the functionality of our EconomicClusters algorithm and app based on collaborator feedback from early use of this twenty-group economic model, to test the validity of the model as a metric of economic status, and to assess the utility of the model in another LMIC context. We condense the twenty Cameroonian economic groups into fewer, ordinally-ranked, groups using agglomerative hierarchical clustering based on mean cluster child height-for-age Z-score (HAZ), women’s literacy score, and proportion of children who are deceased. We develop an EconomicClusters model for Ghana consisting of five economic groups and rank these groups based on the same three variables. The proportion of variance in women’s literacy score accounted for by the EconomicClusters model was 5–12% less than the proportion of variance accounted for by the DHS Wealth Index model. The proportion of the variance in child HAZ and proportion of children who are deceased accounted for by the EconomicClusters model was similar to (0.4–2.5% less than) the proportion of variance accounted for by the DHS Wealth Index model. The EconomicClusters model requires asking only five questions, as opposed to greater than twenty Wealth Index questions. The EconomicClusters algorithm and app could facilitate health disparities research in any country with DHS data by generating ordinally-ranked, population-specific economic models that perform nearly as well as the Wealth Index in evaluating variability in health and social outcomes based on wealth status but that are more feasible to assess in time-constrained settings.

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“…The over-representation of patients from higher-SES urban households in our trauma registry data has been described previously, and is due in part to the urban or peri-urban location of the four pilot hospitals as well as differences in care seeking behaviour among the lower-SES household clusters. 38 Further research is warranted to better describe the burden of IPVRI among the rural population of Cameroon.…”

Section: Discussionmentioning

confidence: 99%

“…35 In response to the need to better characterise the burden of injury in the country, the Cameroon National Trauma Registry project was implemented in 2015 and collects data from all injured patients who receive care at one of the four pilot trauma registry hospitals. 36 37 Early trauma registry data from Cameroon demonstrated a number of demographic and socioeconomic correlates of injury, [38][39][40] and a resultant aim of the pilot trauma registry project was to identify and address inequities in the burden of injury in the country. To that end, we used data collected as a part of the Cameroon National Trauma Registry project to explore associations between IPVRI and education level, employment status, household SES cluster and alcohol use among a cross-sectional sample of injured patients seeking hospital-level care in Cameroon.…”

Section: Bmj Global Healthmentioning

confidence: 99%

Associations between social determinants of health and interpersonal violence-related injury in Cameroon: a cross-sectional study

et al. 2022

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IntroductionRisk factors for interpersonal violence-related injury (IPVRI) in low-income and middle-income countries (LMICs) remain poorly defined. We describe associations between IPVRI and select social determinants of health (SDH) in Cameroon.MethodsWe conducted a cross-sectional analysis of prospective trauma registry data collected from injured patients >15 years old between October 2017 and January 2020 at four Cameroonian hospitals. Our primary outcome was IPVRI, compared with unintentional injury. Explanatory SDH variables included education level, employment status, household socioeconomic status (SES) and alcohol use. The EconomicClusters model grouped patients into household SES clusters: rural, urban poor, urban middle-class (MC) homeowners, urban MC tenants and urban wealthy. Results were stratified by sex. Categorical variables were compared via Pearson’s χ2 statistic. Associations with IPVRI were estimated using adjusted odds ratios (aOR) with 95% confidence intervals (95%CI).ResultsAmong 7605 patients, 5488 (72.2%) were men. Unemployment was associated with increased odds of IPVRI for men (aOR 2.44 (95% CI 1.95 to 3.06), p<0.001) and women (aOR 2.53 (95% CI 1.35 to 4.72), p=0.004), as was alcohol use (men: aOR 2.33 (95% CI 1.91 to 2.83), p<0.001; women: aOR 3.71 (95% CI 2.41 to 5.72), p<0.001). Male patients from rural (aOR 1.45 (95% CI 1.04 to 2.03), p=0.028) or urban poor (aOR 2.08 (95% CI 1.27 to 3.41), p=0.004) compared with urban wealthy households had increased odds of IPVRI, as did female patients with primary-level/no formal (aOR 1.78 (95% CI 1.10 to 2.87), p=0.019) or secondary-level (aOR 1.54 (95% CI 1.03 to 2.32), p=0.037) compared with tertiary-level education.ConclusionLower educational attainment, unemployment, lower household SES and alcohol use are risk factors for IPVRI in Cameroon. Future research should explore LMIC-appropriate interventions to address SDH risk factors for IPVRI.

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Socioeconomic correlates of trauma: An analysis of emergency ward patients in Yaoundé, Cameroon

Cited by 19 publications

References 16 publications

“I did not know it was a medical condition”: Predictors, severity and help seeking behaviors of women with female sexual dysfunction in the Volta region of Ghana

“I did not know it was a medical condition”: Predictors, severity and help seeking behaviors of women with female sexual dysfunction in the Volta region of Ghana

Optimization and validation of the EconomicClusters model for facilitating global health disparities research: Examples from Cameroon and Ghana

Associations between social determinants of health and interpersonal violence-related injury in Cameroon: a cross-sectional study

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