Maternal Factors in Predicting Low Birth Weight Babies

This study examines the association between maternal factors and low birth weight among newborns at a tertiary hospital in Malaysia. This was a cross-sectional study where mothers were followed through from first booking till delivery. There were 666 mothers who delivered from May 2007 to March 2008. Infants’ birth weight were compared with maternal age, pre-pregnancy BMI, fathers BMI, parity, ethnicity, per capita monthly income, and maternal blood pressure during pregnancy. A multiple logistic regressions was used to determine the relationship of maternal factors and low birth weight, while the ROC curve was constructed to assess the sensitivity and specificity of the predictive model. Among the significant risk factors of low birth weight were older age (35 years and above), low pre-pregnancy BMI (<20 kg/m2), parity of 4 and above, Indian origin, economically under privileged, and low and high blood pressure. Blood pressure during pregnancy was an important risk factor for LBW, by using this parameter alone the risk of LBW could be predicted with a sensitivity rate of 70% and a specificity rate of 70%. The sensitivity and specificity was further improved to 80% and 75% percent respectively when other factors like maternal factors such as maternal age, pre-pregnancy BMI, ethnicity, and per capita monthly income were included in the analysis.

A review of maternal mortality in Malaysia

There has been a significant decline in maternal mortality from 540 per 100,000 live births in I957 to 28 per 100,000 in 2010. This decline is due to several factors. Firstly the introduction of the rural health infrastructure which is mainly constructing health centres and midwife clinics for the rural population. This provided the accessibility and availability of primary health care and specially, antenatal care for the women. This also helped to increase the antenatal coverage for the women to 98% in 2010 and it increased the average number of antenatal visits per women from 6 in 1980 to 12 visits in 2010 for pregnant women. Along with the introduction of health centres, another main feature was the introduction of specific programmes to address the needs of the women and children. In the 1950s the introduction of Maternal and Child Health (MCH) programme was an important step. Later in the late 1970s there was the introduction of the High Risk Approach in MCH care and Safe Motherhood in the 1980s. In 1990, an important step was the introduction of the Confidential Enquiry into Maternal Deaths (CEMD). Another significant factor in the reduction is the identification of high risk mothers and this is being done by the introduction of the colour coding system in the health centres. Other factors include the increase in the number of safe deliveries by skilled personnel and the reduction in the number of deliveries by the Traditional Birth Attendants (TBAs). The reduction in fertility rate from 6.3 in 1960 to 3.3 in 2010 has been another important factor. To achieve the 2015 Millennium Development Goals (MDG) to further reduce maternal deaths by 50%, more needs to be done especially to identify maternal deaths that are missed by omission or misclassification and also to capture the late maternal deaths.

Economic Impact of Dyspepsia in Rural and Urban Malaysia: A Population-Based Study

BACKGROUND/AIMS: The economic impact of dyspepsia in regions with a diverse healthcare system remains uncertain. This study aimed to estimate the costs of dyspepsia in a rural and urban population in Malaysia. METHODS: Economic evaluation was performed based on the cost-of-illness method. Resource utilization and quality of life data over a specific time frame, were collected to determine direct, indirect and intangible costs related to dyspepsia. RESULTS: The prevalences of dyspepsia in the rural (n = 2,000) and urban (n = 2,039) populations were 14.6% and 24.3% respectively. Differences in socioeconomic status and healthcare utilisation between both populations were considerable. The cost of dyspepsia per 1,000 population per year was estimated at USD14,816.10 and USD59,282.20 in the rural and urban populations respectively. The cost per quality adjusted life year for dyspepsia in rural and urban adults was USD16.30 and USD69.75, respectively. CONCLUSIONS: The economic impact of dyspepsia is greater in an urban compared to a rural setting. Differences in socioeconomic status and healthcare utilisation between populations are thought to contribute to this difference.