Measuring urban expansion pattern using spatial matrices in Khulna City, Bangladesh

Khulna, the third-largest metropolitan area in Bangladesh, has become a potential site for the polycentric urbanization for multiple mega-projects. Measurement of urban expansion is essential for regulating haphazard growth and achieving effective management. This study aims to quantify and compare the urban expansion pattern of Khulna City Corporation (KCC) and surrounding areas' development hotspots. Landsat remote sensing images of 1990, 2000, 2010 and 2020 were used to perform supervised classification using Geographic Information System (GIS). To quantify urban expansion, we compute Annual Urban Expansion Rate, Urban Expansion Intensity Index, and Urban Expansion Differentiation Index. Although annual urban expansion in the study area was slow during the first two decades, it accelerated to 6.76% during the last decade. 48% of the total built-up areas have grown during 2010-2020 alone. Even though KCC experienced continuous urban growth over a thirty-year period, after 2010, the rate of urban expansion in peripheral areas exceeded that of KCC. Transboundary and intra-regional transportation and economic corridor development, establishment of economically potential zones (EPZ), urban to rural migration, availability of rich agriculture hinterland, low land price and several direct transportation links between the core and periphery are the major influencing factors of peri-urbanization.

A comparison of practices, distributions and determinants of birth attendance in two divisions with highest and lowest skilled delivery attendance in Bangladesh

BACKGROUND

Delivery by skilled birth attendants (SBAs) is strongly recommended to reduce maternal and neonatal mortality. The percentage of births attended by SBAs is low in Bangladesh (42% in 2014), though this rate varies widely by divisions, with the highest 58% in Khulna and only 27% in Sylhet. Comparing and critically analyzing the practices, distributions and determinants of delivery attendance in two divisions with the highest and lowest SBA attendance could help to understand the differences and to employ the findings of the high-performing division to the low-performing division.

METHODS

The 7th Bangladesh Demographic and Health Survey (BDHS 2014) data were analyzed. After reporting the types of delivery attendants, logistic regression analyses were applied to calculate the odds ratios of determinants of deliveries attended by SBAs.

RESULTS

SBAs attended 225 (58.6%) and 128 (27.4%) deliveries in Khulna and Sylhet, respectively. Khulna had higher birth attendance by qualified doctors (42.5%, n = 163) than Sylhet (15.8%, n = 74). Sylhet had higher attendance by traditional attendants (60.8%, n = 285) than Khulna (33.7%, n = 129). In both regions, attendance by community skilled birth attendants (CSBAs) was very low (< 1%). Khulna had higher percentages of women with higher education level, husbands' higher education, antenatal care (ANC) visits by SBAs, and higher wealth quintiles than Sylhet. In multivariable analyses, higher education level (adjusted odds ratio (AOR): 8.4; 95% confidence interval (CI): 1.9-36.7), ANC visits (AOR: 3.6; 95% CI: 2.0-6.5), family planning workers' visit (AOR: 3.0; 95% CI: 1.6-5.4), and belonging to richer (AOR: 2.6; 95% CI: 1.4-5.1) or richest (AOR: 3.8; 95% CI: 1.9-7.6) household wealth quintiles had significant positive associations with deliveries by SBAs in Sylhet. Similarly, ANC visits (AOR: 2.5; 95% CI: 1.4-4.6) and higher wealth quintile (AOR: 4.7; 95% CI: 1.9-11.5) were positive predictors in Khulna.

CONCLUSIONS

The higher proportion of educated women and their husbands, wealth status and ANC visits were associated with higher SBA utilization in Khulna compared to Sylhet. Improvement of socioeconomic status, increasing birth attendant awareness programs, providing ANC services, and family-planning workers' visits could increase the proportion of SBA-attended deliveries in Sylhet Division. CSBA program should be re-evaluated for both divisions.

Monitoring of metal pollution in waterways across Bangladesh and ecological and public health implications of pollution

Using innovative artificial mussels technology for the first time, this study detected eight heavy metals (Cd, Cu, Fe, Mn, Ni, Pb, U, Zn) on a regular basis in waterways across Bangladesh (Chittagong, Dhaka and Khulna). Three heavy metals, viz. Co, Cr and Hg were always below the instrumental detection levels in all the sites during the study period. Through this study, seven metal pollution "hot spots" have been identified, of which, five "hot spots" (Cu, Fe, Mn, Ni, Pb) were located in the Buriganga River, close to the capital Dhaka. Based on this study, the Buriganga River can be classified as the most polluted waterway in Bangladesh compared to waterways monitored in Khulna and Chittagong. Direct effluents discharged from tanneries, textiles are, most likely, reasons for elevated concentrations of heavy metals in the Buriganga River. In other areas (Khulna), agriculture and fish farming effluents may have caused higher Cu, U and Zn in the Bhairab and Rupsa Rivers, whereas untreated industrial discharge and ship breaking activities can be linked to elevated Cd in the coastal sites (Chittagong). Metal pollution may cause significant impacts on water quality (irrigation, drinking), aquatic biodiversity (lethal and sub-lethal effects), food contamination/food security (bioaccumulation of metals in crops and seafood), human health (diseases) and livelihoods of people associated with wetlands.