The study was performed to assess the prevalence and risk factors of epilepsy in a rural area where cysticercosis was endemic Dong Cuu commune, Gia Binh district, Bac Ninh province. Results: There were 38 cases of 6269 people living in the area suffering epilepsy. The prevalence of epilepsy was 6.1%. Among 38 patients with epilepsy, 25 cases were active epilepsy. The prevalence was highest in patients under 10 year and between 41 - 50 of aged. 71% of patients had generalized seisures, 13% had partial seisures and 15.8% of patients had unclassification seisures. 18/38 patients had risk factors indentified, of them 3 were due to Neurocysticercosis. 45% of patients did not receive any management and treatment. The prevalence of epilepsy in the area with cysticercosis as the same as other areas. However, Neurocysticercosis was considerable cause of epilepsy in the community.
Epilepsy ; Cysticercosis ; Epidemiologic Factors

Population attributable fraction (PAF) is an important public health parameter that is familiar to epidemiologists. The calculation of PAF is frequently based on the relative risk (RR) of a risk factor for a certain disease and the prevalence of exposure to the risk factor in the total population (Pe). We introduce here the method for making a nomogram linking PAF to RR and Pe. The nomogram will be very handy for public health professionals in estimating PAF quickly and accurately when information on RR and Pe is available.
Epidemiologic Methods ; Humans ; Risk Factors

Bias ; Confounding Factors (Epidemiology) ; Epidemiologic Methods ; Humans

1305 older persons living in communities were included in an epidemiological survey to investigate the risk factor for atherosclerosis. The results showed that prevalence of risk factors in the elderly was high: dyslipidemia (47.5%), hypertension (45.6%), smoking (26.9%), obesity (18.3%) and diabetes/IFG (12.1%). The prevalence of hypertension in rural area was higher than in urban area. Prevalence of dyslipidemia, diabetes/IFG and obesity in urban were higher than in rural area. There are not difference in prevalence of hypertension, diabetes/IFG and obesity between men and women.
Atherosclerosis ; Risk Factors ; Epidemiologic Studies ; aged

BACKGROUND: Vitiligo is an acquired disorder with destruction of melanocytes and clinically characterized by a progressive clinical course. OBJECTIVE: The significance of various epidemiological factors related to the progression of vitiligo were investigated. METHODS: A clinical study was done on 400 patients who had visited the Vitiligo Clinic of Severance Hospital. Questionaires regarding progression, sex, family history, clinical type, Koebner's isomorphic phenomenon, onset age, and duration of disease were recorded. RESULTS: There was significant progression of vitiligo in patients with family history, nonsegmental type, Koebner's isomorphic phenomenon and long duration. CONCLUSION: Some epidemiologic factors are relevant in predicting the progression of vitiligo.
Age of Onset ; Epidemiologic Factors ; Humans ; Melanocytes ; Vitiligo*

The overall details of causality frames in the objective world remain obscure, which poses difficulty for causality research. Based on the temporality of cause and effect, the objective world is divided into three time zones and two time points, in which the causal relationships of the variables are parsed by using Directed Acyclic Graphs (DAGs). Causal DAGs of the world (or causal web) is composed of two parts. One is basic or core to the whole DAGs, formed by the combination of any one variable originating from each time unit mentioned above. Cause effect is affected by the confounding only. The other is an internal DAGs within each time unit representing a parent-child or ancestor-descendant relationship, which exhibits a structure similar to the confounding. This paper summarizes the construction of causality frames for objective world research (causal DAGs), and clarify a structural basis for the control of the confounding in effect estimate.
Causality ; Computer Graphics ; Confounding Factors, Epidemiologic ; Data Interpretation, Statistical ; Epidemiologic Methods ; Humans

One of the commonly accepted merits of cohort studies (CSs) refers to the exposure precedes outcome superior to other observational designs. We use Directed Acyclic Graphs to construct a causal graph among research populations under CSs. We notice that the substitution of research population in place of a susceptible one can be used for effect estimation. Its correctness depends on the outcome-free status of the substituted population and the performance of both screening and diagnosis regarding the outcomes under study at baseline. The temporal precedence of exposure over outcome occurs theoretically, despite the opposite happens in realities. Correct effect estimate is affected by both the suitability of population substitution and the validities of outcome identification and exclusion.
Causality ; Cohort Studies ; Confounding Factors, Epidemiologic ; Epidemiologic Methods ; Mass Screening ; Research Design

Measurement bias (MB) has been described in causal structures but is still not entirely clear. In practice, the correctness of substitution estimate (SE) of effect is a prerequisite for causal inference, usually based on a bidirectionally non-differential misclassification between the measured exposure and the measured outcome. Based on a directed acyclic graph (DAG), this paper proposes a structure for the single-variable measure, where its MB is derived from the choice of an imperfect, "input/output device-like" measurement system. The MB of the SE is influenced both by the measurement system itself and by factors outside the measurement system: while the independence or dependence mechanism of the measurement system still ensures that the MB of the SE is bidirectionally non-differential; however, the misclassification can be bidirectionally non-differential, unidirectionally differential, or bidirectionally differential resulted from the factors outside the measurement system. In addition, reverse causality should be defined at the level of measurement, where measured exposures can influence measured outcomes and vice versa. Combined with temporal relationships, DAGs help elucidate MB's structures, mechanisms, and directionality.
Humans ; Confounding Factors, Epidemiologic ; Data Interpretation, Statistical ; Bias ; Causality

Controlling unmeasured confounders in non-randomized controlled studies is challenging. Negative control theory is based on the theoretical concept that the test result of negative controls must be negative. Setting appropriate negative control incorporates the specificity of association into population studies for the identification and control of unmeasured confounders. This paper explains the principles to control unmeasured confounders using negative control theory from a statistical perspective. A detailed introduction of derived methods based on negative control theory is also introduced, including adjusted standardized mortality ratio method, calibrating P-value method, generalized difference-in-difference model and double negative control method. The reasonable application of those derived methods is also comprehensively summarized based on representative case studies. Negative control is an important statistical design to identify, revise and control unmeasured confounders and a valuable method for comparative effectiveness research based on real-world data.
Humans ; Confounding Factors, Epidemiologic ; Research Design ; Comparative Effectiveness Research ; Bias

OBJECTIVETo evaluate the contribution of individual risk factor to a disease on someone with several risk factors.

METHODSA method based on epidemiological theory and Bayes' theorem was established to measure the contribution of individual risk factor, using the relative risk (RR) or odds ratio (OR) value obtained from population-based cohort studies or meta-analysis.

RESULTSThe proportional contribution for individual risk factor to disease in one person can be measured or estimated.

CONCLUSIONThis method can be applied to risk assessment in a patient with more than one risk factor, and the results also contribute to our etiological study and clinical decision-making strategy.

Bayes Theorem ; Data Interpretation, Statistical ; Disease ; etiology ; Epidemiologic Methods ; Epidemiologic Studies ; Humans ; Proportional Hazards Models ; Risk Assessment ; Risk Factors