Browsing by Author "Kaneko, S."

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Analysis of effects of meteorological factors on dengue incidence in Sri Lanka using time series data
(Public Library of Science, 2013) Goto, K.; Kumarendran, B.; Mettananda, S.; Gunasekara, D.; Fujii, Y.; Kaneko, S.
In tropical and subtropical regions of eastern and South-eastern Asia, dengue fever (DF) and dengue hemorrhagic fever (DHF) outbreaks occur frequently. Previous studies indicate an association between meteorological variables and dengue incidence using time series analyses. The impacts of meteorological changes can affect dengue outbreak. However, difficulties in collecting detailed time series data in developing countries have led to common use of monthly data in most previous studies. In addition, time series analyses are often limited to one area because of the difficulty in collecting meteorological and dengue incidence data in multiple areas. To gain better understanding, we examined the effects of meteorological factors on dengue incidence in three geographically distinct areas (Ratnapura, Colombo, and Anuradhapura) of Sri Lanka by time series analysis of weekly data. The weekly average maximum temperature and total rainfall and the total number of dengue cases from 2005 to 2011 (7 years) were used as time series data in this study. Subsequently, time series analyses were performed on the basis of ordinary least squares regression analysis followed by the vector autoregressive model (VAR). In conclusion, weekly average maximum temperatures and the weekly total rainfall did not significantly affect dengue incidence in three geographically different areas of Sri Lanka. However, the weekly total rainfall slightly influenced dengue incidence in the cities of Colombo and Anuradhapura. Copyright: 2013 Goto et al.
Correction: Double burden of maternal and child malnutrition and socioeconomic status in urban Sri Lanka.
(Public Library of Science, 2020) Shinsugi, C.; Gunasekara, D.; Gunawardena, N.K.; Subasinghe, W.; Miyoshi, M.; Kaneko, S.; Takimoto, H.
[This corrects the article DOI: 10.1371/journal.pone.0224222.]. Erratum for Double burden of maternal and child malnutrition and socioeconomic status in urban Sri Lanka. PLoS One.2019;14(10):e0224222.
Double burden of maternal and child malnutrition and socioeconomic status in urban Sri Lanka
(Public Library of Science, 2019) Shinsugi, C.; Gunasekara, D.; Gunawardena, N.K.; Subasinghe, W.; Miyoshi, M.; Kaneko, S.; Takimoto, H.
Child malnutrition and maternal obesity are serious public health issues in Sri Lanka. This study explores the associations between socioeconomic status and the double burden of malnutrition among school-aged children and within their household. A total of 543 primary school children aged 5-10 years (204 boys and 339 girls) in Gampaha District, Sri Lanka, were included in the analysis. The nutritional statuses of thinness, normal, overweight, and obesity for children and mothers were defined according to WHO growth references and body mass index. Maternal education, household equivalent income, and maternal employment were used as socioeconomic status indicators. The proportion of child thinness and overweight was 19.3% and 13.4%, respectively, and that of maternal overweight (body mass index ≥ 25 kg/m2) was 36.5%. A positive correlation was found between maternal body mass index and the child's body mass index for age z-score in older boys and younger girls. A multivariate stepwise logistic regression analysis showed that lower education of mothers posed a higher association with child thinness (adjusted odds ratio = 2.33, 95% confidence interval: 1.08-5.00). Mothers with overweight and obesity were less likely to have a child with thinness (adjusted odds ratio = 0.30, 95% confidence interval: 0.16-0.58). Maternal employment status and household equivalent income were not significantly, but marginally, associated with child overweight and obesity. Socioeconomic inequality combined with maternal nutritional status affected child malnutrition. These findings suggest that the underlying circumstances within households should be considered to improve child malnutrition. Erratum in: PLoS One. 2020;15(3):e0230785.