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Lan Huong Dao

Publications and source records attributed to Lan Huong Dao.

2 recordsLinked to original sources

Cardiovascular disease mortality and its association with socioeconomic status: findings from a population-based cohort study in rural Vietnam, 1999-2003.

INTRODUCTION: Cardiovascular disease is an emerging epidemic in Vietnam, but because cause of death and other routine data are not widely available, it is difficult to characterize community-based disease patterns. Using 5-year data from an ongoing cause-specific mortality study conducted within a demographic surveillance system in Vietnam's Bavi district, this article estimates the rates of adult cardiovascular disease mortality in relation to the mortality rates of other noncommunicable diseases in rural northern Vietnam and examines the association of cardiovascular disease with certain demographic and socioeconomic factors. METHODS: All causes of death of adults aged 20 and older occurring from 1999 through 2003 (n = 1067) were determined by using an established demographic surveillance system and data collected by trained interviewers who asked caretakers or relatives of the deceased individuals about signs and symptoms of disease during quarterly household visits. Deaths were classified as cardiovascular disease, cancer, or other noncommunicable diseases. These records were linked to demographic and socioeconomic data. RESULTS: Of the 1067 adult deaths that were recorded, there was an overall noncommunicable disease mortality rate of 7.8 per 1000 person-years. Cardiovascular disease accounted for 33% of male and 31% of female deaths. Compared with cancer and other noncommunicable causes of death in a Cox proportional hazards model, higher cardiovascular disease mortality rates were observed among men, older age groups, and those without formal education. CONCLUSION: To date, cohort studies and population-based mortality data in Vietnam have been scarce; this study provides insights into the public health aspects of cardiovascular disease in transitional Vietnam. The rates of cardiovascular disease mortality in this rural Vietnamese community were high, suggesting the need for both primary prevention and secondary treatment initiatives. The demographic surveillance system is an important tool for characterizing such an epidemic.

Adult↗

Refining a probabilistic model for interpreting verbal autopsy data.

OBJECTIVE: To build on the previously reported development of a Bayesian probabilistic model for interpreting verbal autopsy (VA) data, attempting to improve the model's performance in determining cause of death and to reassess it. DESIGN: An expert group of clinicians, coming from a wide range geographically and in terms of specialization, was convened. Over a four-day period the content of the previous probabilistic model was reviewed in detail and adjusted as necessary to reflect the group consensus. The revised model was tested with the same 189 VA cases from Vietnam, assessed by two local clinicians, that were used to test the preliminary model. RESULTS: The revised model contained a total of 104 indicators that could be derived from VA data and 34 possible causes of death. When applied to the 189 Vietnamese cases, 142 (75.1%) achieved concordance between the model's output and the previous clinical consensus. The remaining 47 cases (24.9%) were presented to a further independent clinician for reassessment. As a result, consensus between clinical reassessment and the model's output was achieved in 28 cases (14.8%); clinical reassessment and the original clinical opinion agreed in 8 cases (4.2%), and in the remaining 11 cases (5.8%) clinical reassessment, the model, and the original clinical opinion all differed. Thus overall the model was considered to have performed well in 170 cases (89.9%). CONCLUSIONS: This approach to interpreting VA data continues to show promise. The next steps will be to evaluate it against other sources of VA data. The expert group approach to determining the required probability base seems to have been a productive one in improving the performance of the model.

Autopsy↗