Abstract

TPS 742: Adverse birth outcomes 1, Exhibition Hall, Ground floor, August 27, 2019, 3:00 PM - 4:30 PM Climate has been reported to affect birthweight and few studies have been conducted in the Pacific region where influence of climate change can be reflected to health status directly. This study aimed to investigate the association between climate variability including El Niño Southern Oscillation (ENSO) and birthweight in Tuvalu, a Polynesian atoll island country located beneath the tropical Pacific Ocean. Data of all newborns born in Tuvalu between January 1980 and August 2018 were obtained from Ministry of Health (n = 7,528). Oceanic Niño Index (ONI) which is used for operational definitions of ENSO events and sea surface temperature measurement including NINO3, NINO3.4, and NINO4 together with local temperature and precipitation were used as climate variables. The average ONI and sea surface temperatures during full gestational period and each trimester of pregnancy were calculated for each newborn. Generalized additive model (GAM) was used to analyze the relationship between the average ONI and sea surface temperatures during each period of pregnancy and birthweight. Logistic regression model was also used to analyze the relationship between the average ONI and sea surface temperatures and low birthweight (LBW) birth defined as less than 2,500 grams according to the criteria of World Health Organization. Both models were adjusted for sex, birth islands, mother’s age group, marital status, and GDP per capita in the year of birth. GAM analyses demonstrated a negative relationship between birthweight and ONI. However, above a certain temperature, NINO4 and birthweight showed a positive relationship. The odds ratios of LBW birth were 0.93 (95% confidence interval (CI), 0.79-1.11), 1.05 (95% CI, 0.90-1.23), 0.93 (95% CI, 0.80-1.08), and 0.86 (95% CI, 0.73-1.01) for a unit increase of average ONI during full gestational period and each trimester of pregnancy. In conclusion, birthweight of Tuvalu was partly affected by climate variability.

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