Sociodemographic predictors of knowledge, mosquito bite patterns and protective behaviors concerning vector borne disease: The case of dengue fever in Chinese subtropical city, Hong Kong.

Geographic pattern of dengue fever is changing due to the global environmental and climate changes in the 21st century. Evidence of community's knowledge, mosquito bite patterns and protective behavior practices in non-endemic regions is limited. This study examined the knowledge of dengue, mosquito bite patterns, protective behavior practices and their associated factors in Hong Kong, a non-endemic subtropical city. A population-based random telephone survey (n = 590) was conducted three weeks after the government announcement of a local dengue outbreak in August 2018. Sociodemographic status, awareness, knowledge, protective measures, bite patterns of mosquito were collected. Results indicated high level of community awareness of the local outbreak (95.2%), symptom identification (84.0%) and adoption of at least one mosquito protective measures (nearly 80%). About 40% of respondents reported that they were bitten by mosquitoes during the study period, a high mosquito season in Hong Kong. Mosquito bites were prevalent near grassy area (63.4%), at home (42.6%) and at public transportation waiting spots (39.6%). Younger people (< 25 years old), female, those who lived on lower floors (≤the 6th) and near grassy area were at higher risk of mosquito bites at home. Respondents perceived higher threat of dengue to society were more likely to practice mosquito prevention. While residential factors affected their indoor prevention, other socio-demographic factors affected the outdoor prevention. Practicing prevention behaviors were associated with self-reported mosquito bite at home. Furthermore, the general prevention uptake rate unchanged after the announcement of local dengue outbreak. Although the uptake rate of protective measures during August was high, 40% participants reported they were bitten. Also public locations are more common area for bites, which suggested stronger mosquito prevention and control on public environments and more personal protective behaviors should be advocated.

Dietary sugar intake does not pose any risk of bone loss and non-traumatic fracture and is associated with a decrease in all-cause mortality among Chinese elderly: Finding from an 11-year longitudinal study of Mr. and Ms. OS Hong Kong.

BACKGROUND: The association of dietary sugar intake and skeletal health remains uncertain in the elderly. We aimed to investigate the association of sugar intake with the bone health and mortality of Chinese elderly. METHODS: An analysis was conducted through an 11-year longitudinal study (Mr. and Ms. OS Hong Kong). Four thousand Chinese elderly aged 65 and older were recruited from the local community between 2001 and 2003. Sugar intake was assessed at baseline by a validated 329-item Food Frequency Questionnaire and a local sugar database. The bone mineral density (BMD) was examined at baseline and the fourth year follow-up by a dual-energy X-ray absorptiometry. Data on the incidence of non-traumatic fractures (total, hip and osteoporotic sites) and all-cause mortality were collected. The multivariable logistic and Cox regression models were used to test the associations of sugar intake with bone health and all-cause mortality. RESULTS: No significant association was observed between sugar intakes and BMD changes in the fourth year's follow-up. During a total 34,483 person years' follow-up, we documented 433 non-traumatic fractures and 769 deaths. Although lack of significant association with the incidence of non-traumatic fractures, high added sugar intakes were significantly associated with a low risk of all-cause mortality among the elderly with a hazard ratio of 0.750 (95% CI: 0.590-0.954, P for trend = 0.007) in the highest quintile compared with that in the lowest quintile. CONCLUSION: The amount of sugar consumed by the Chinese elderly did not pose any risk of bone loss and fracture. Moreover, high sugar intake of the elderly was associated with a low rate of all-cause mortality.

[Study on the interaction under logistic regression modeling].

When study on epidemiological causation is carried out, logistic regression has been commonly used to estimate the independent effects of risk factors, as well as to examine possible interactions among individual risk factor by adding one or more product terms to the regression model. In logistic or Cox's regression model, the regression coefficient of the product term estimates the interaction on a multiplicative scale while statistical significance indicates the departure from multiplicativity. Rothman argues that when biologic interaction is examined, we need to focus on interaction as departure from additivity rather than departure from multiplicativity. He presents three indices to measure interaction on an additive scale or departure from additivity, using logarithmic models such as logistic or Cox's regression model. In this paper, we use data from a case-control study of female lung cancer in Hong Kong to calculate the regression coefficients and covariance matrix of logistic model in SPSS. We then introduce an Excel spreadsheet set up by Tomas Andersson to calculate the indices of interaction on an additive scale and the corresponding confidence intervals. The results can be used as reference by epidemiologists to assess the biologic interaction between factors. The proposed method is convenient and the Excel spreadsheet is available online for free.