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1.
Sante Publique ; 30(6): 887-896, 2018.
Article in French | MEDLINE | ID: mdl-30990277

ABSTRACT

CONTEXT: The WHO estimates that 100 million people are pushed into poverty by direct payments for medical services. This work explored the constraints and challenges for setting up health microinsurance in a developing country, the Democratic Republic of Congo (DRC). METHODS AND MATERIALS: This is a cross-sectional, analytical, quantitative, and household survey based on two-stage cluster sampling. Data entry was done using the EPI DATA software and analysis by the SPSS software. MAIN RESULTS: The average income per capita in DRC 119.35 USD per year. The total amount was USD 3.87 for a disease episode. The average cost paid for health care at the last episode of illness was 5.91 USD. Just over six out of ten households (64.43%) felt that health care was too expensive.Nearly nine out of ten households would be willing to subscribe to a microinsurance health plan, even though four out of ten households felt the premium was exorbitant (US $ 6.65 per person per year). The willingness to pay for the contribution to a voluntary health insurance scheme was $5.16 per household per year, or $0.71 per person. CONCLUSION: We have shown that universal coverage with an expanded package of offered services is not economically feasible in the health zone of Katako-Kombe, through the establishment of a quality health micro insurance, if it relies only on the contributions of its members.


Subject(s)
Delivery of Health Care/economics , Insurance Coverage/economics , Insurance, Health/economics , Cross-Sectional Studies , Democratic Republic of the Congo , Humans
2.
BMC Endocr Disord ; 16(1): 60, 2016 Nov 11.
Article in English | MEDLINE | ID: mdl-27835951

ABSTRACT

BACKGROUND: Factual data exploring the relationship between obesity and diabetes mellitus prevalence from rural areas of sub-Saharan Africa remain scattered and are unreliable. To address this scarceness, this work reports population study data describing the relationship between the obesity and the diabetes mellitus in the general population of the rural area of Katana (South Kivu in the Democratic Republic of the Congo). METHODS: A cohort of three thousand, nine hundred, and sixty-two (3962) adults (>15 years old) were followed between 2012 and 2015 (or 4105 person-years during the observation period), and data were collected using the locally adjusted World Health Organization's (WHO) STEPwise approach to Surveillance (STEPS) methodology. The hazard ratio for progression of obesity was calculated. The association between diabetes mellitus and obesity was analyzed with logistic regression. RESULTS: The diabetes mellitus prevalence was 2.8 % versus 3.5 % for obese participants and 7.2 % for those with metabolic syndrome, respectively. Within the diabetes group, 26.9 % had above-normal waist circumference and only 9.8 % were obese. During the median follow-up period of 2 years, the incidence of obesity was 535/100,000 person-years. During the follow-up, the prevalence of abdominal obesity significantly increased by 23 % (p <0.0001), whereas the increased prevalence of general obesity (7.8 %) was not significant (p = 0.53). Finally, diabetes mellitus was independently associated with age, waist circumference, and blood pressure but not body mass index. CONCLUSION: This study confirms an association between diabetes mellitus and abdominal obesity but not with general obesity. On the other hand, the rapid increase in abdominal obesity prevalence in this rural area population within the follow-up period calls for the urgent promoting of preventive lifestyle measures.


Subject(s)
Diabetes Mellitus/epidemiology , Obesity/complications , Rural Population , Adult , Age Factors , Blood Pressure , Body Mass Index , Cohort Studies , Democratic Republic of the Congo/epidemiology , Diabetes Complications/epidemiology , Female , Humans , Logistic Models , Male , Metabolic Syndrome/complications , Metabolic Syndrome/epidemiology , Middle Aged , Obesity/epidemiology , Prevalence , Proportional Hazards Models , Waist Circumference
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