Sex ratio at birth in Vietnam among six subnational regions during 1990–2050, estimation and probabilistic projection using a Bayesian hierarchical time series model

The sex ratio at birth (SRB, i.e., the ratio of male to female births) in Vietnam has been imbalanced since the 2000s. Previous studies have revealed a rapid increase in the SRB over the past 15 years and the presence of important variations across regions. More recent studies suggested that the nation’s SRB may have plateaued during the 2010s. Given the lack of exhaustive birth registration data in Vietnam, it is necessary to estimate and project levels and trends in the regional SRBs in Vietnam based on a reproducible statistical approach. We compiled an extensive database on regional Vietnam SRBs based on all publicly available surveys and censuses and used a Bayesian hierarchical time series mixture model to estimate and project SRB in Vietnam by region from 1980 to 2050. The Bayesian model incorporates the uncertainties from the observations and year-by-year natural fluctuation. It includes a binary parameter to detect the existence of sex ratio transitions among Vietnamese regions. Furthermore, we model the SRB imbalance using a trapezoid function to capture the increase, stagnation, and decrease of the sex ratio transition by Vietnamese regions. The model results show that four out of six Vietnamese regions, namely, Northern Midlands and Mountain Areas, Northern Central and Central Coastal Areas, Red River Delta, and South East, have existing sex imbalances at birth. The rise in SRB in the Red River Delta was the fastest, as it took only 12 years and was more pronounced, with the SRB reaching the local maximum of 1.146 with a 95% credible interval (1.129, 1.163) in 2013. The model projections suggest that the current decade will record a sustained decline in sex imbalances at birth, and the SRB should be back to the national SRB baseline level of 1.06 in all regions by the mid-2030s.

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Temporal change and its spatial variety on land surface temperature and land use changes in the Red River Delta, Vietnam, using MODIS time-series imagery

Environmental Monitoring and Assessment ◽

10.1007/s10661-015-4691-3 ◽

2015 ◽

Vol 187 (7) ◽

Cited By ~ 18

Author(s):

On Van Nguyen ◽

Kensuke Kawamura ◽

Dung Phan Trong ◽

Zhe Gong ◽

Endan Suwandana

Keyword(s):

Land Use ◽

Time Series ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Temporal Change ◽

Land Use Changes ◽

River Delta ◽

Red River ◽

Red River Delta

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Rice-planted area extraction by time series analysis of ENVISAT ASAR WS data using a phenology-based classification approach: A case study for Red River Delta, Vietnam

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-7-w3-77-2015 ◽

2015 ◽

Vol XL-7/W3 ◽

pp. 77-83 ◽

Cited By ~ 8

Author(s):

D. Nguyen ◽

W. Wagner ◽

V. Naeimi ◽

S. Cao

Keyword(s):

Time Series ◽

Supervised Classification ◽

Incidence Angle ◽

Rice Fields ◽

River Delta ◽

Rice Cultivation ◽

Red River ◽

Rice Crop ◽

Red River Delta ◽

Classification Approach

Recent studies have shown the potential of Synthetic Aperture Radars (SAR) for mapping of rice fields and some other vegetation types. For rice field classification, conventional classification techniques have been mostly used including manual threshold-based and supervised classification approaches. The challenge of the threshold-based approach is to find acceptable thresholds to be used for each individual SAR scene. Furthermore, the influence of local incidence angle on backscatter hinders using a single threshold for the entire scene. Similarly, the supervised classification approach requires different training samples for different output classes. In case of rice crop, supervised classification using temporal data requires different training datasets to perform classification procedure which might lead to inconsistent mapping results. In this study we present an automatic method to identify rice crop areas by extracting phonological parameters after performing an empirical regression-based normalization of the backscatter to a reference incidence angle. The method is evaluated in the Red River Delta (RRD), Vietnam using the time series of ENVISAT Advanced SAR (ASAR) Wide Swath (WS) mode data. The results of rice mapping algorithm compared to the reference data indicate the Completeness (User accuracy), Correctness (Producer accuracy) and Quality (Overall accuracies) of 88.8%, 92.5 % and 83.9 % respectively. The total area of the classified rice fields corresponds to the total rice cultivation areas given by the official statistics in Vietnam (R²  0.96). The results indicates that applying a phenology-based classification approach using backscatter time series in optimal incidence angle normalization can achieve high classification accuracies. In addition, the method is not only useful for large scale early mapping of rice fields in the Red River Delta using the current and future C-band Sentinal-1A&B backscatter data but also might be applied for other rice cultivation areas.

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Levels and trends in sex ratio at birth in provinces of Pakistan from 1980 to 2020 with scenario-based missing female birth projections to 2050: a Bayesian modeling approach

10.31235/osf.io/5n3y8 ◽

2021 ◽

Author(s):

Fengqing Chao ◽

Muhammad Asif Wazir ◽

Hernando Ombao

Keyword(s):

Sex Ratio ◽

Sex Discrimination ◽

Credible Interval ◽

Sex Ratio At Birth ◽

Bayesian Hierarchical ◽

Female Birth ◽

Child Mortality Rate ◽

Birth Records ◽

Male To Female ◽

Postnatal Stage

BACKGROUND: Pakistan has a strong preference for boys over girls; previous evidence on sex preference is primarily reported at the postnatal stage in which the child mortality rate is higher for females than males. Prenatal sex discrimination in Pakistan, reflected in the inflated sex ratio at birth (SRB; ratio of male to female births) has been barely mentioned before this study.OBJECTIVE: We estimate the SRB and missing female births in Pakistan provinces from 1980 to 2020 and identify provinces with imbalanced SRB. We provide scenario-based projections of missing female births in provinces without the existing SRB inflation.METHODS: An extensive SRB database of 832,091 birth records was compiled from all available surveys and censuses. To synthesize different data sources and provide annual estimates and their associated uncertainties of SRBs across provinces, we adopted a Bayesian hierarchical time series model.RESULTS: As per our model, Balochistan has had SRB imbalance since 1980. The maximum SRB was estimated as 1.121 (95% credible interval [1.066; 1.142]) in 1997. Assuming different start year of SRB inflation process in provinces without existing imbalance, the largest female birth deficit is projected to be 76.2 thousand in Punjab in 2033 when the SRB inflation starts in 2021.CONTRIBUTION: This is the first study on estimating the SRB from 1980 to 2020 and providing scenario-based projections of missing female births up to 2050 by Pakistan province. We identified the Balochistan province with imbalanced SRB and demonstrated important disparities in the occurrence and quantity of female birth deficits before 2050.

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Global estimation and scenario-based projections of sex ratio at birth and missing female births using a Bayesian hierarchical time series mixture model

The Annals of Applied Statistics ◽

10.1214/20-aoas1436 ◽

2021 ◽

Vol 15 (3) ◽

Author(s):

Fengqing Chao ◽

Patrick Gerland ◽

Alex R. Cook ◽

Leontine Alkema

Keyword(s):

Time Series ◽

Sex Ratio ◽

Mixture Model ◽

Sex Ratio At Birth ◽

Bayesian Hierarchical ◽

Global Estimation

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Climate Change and Land Use Change of Rural Households in The Red River Delta, Vietnam

Journal of Economics and Development ◽

10.33301/2013.15.02.05 ◽

2013 ◽

pp. 79-94

Author(s):

Ngoc Luu Bich

Keyword(s):

Climate Change ◽

Land Use ◽

Agricultural Land ◽

Rural Households ◽

River Delta ◽

Red River ◽

Red River Delta ◽

Sea Levels ◽

Main Production ◽

Farming Households

Climate change (CC) and its impacts on the socio-economy and the development of communities has become an issue causing very special concern. The rise in global temperatures, in sea levels, extreme weather phenomena, and salinization have occurred more and more and have directly influenced the livelihoods of rural households in the Red River Delta – one of the two regions projected to suffer strongly from climate change in Vietnam. For farming households in this region, the major and traditional livelihoods are based on main production materials as agricultural land, or aquacultural water surface Changes in the land use of rural households in the Red River Delta during recent times was influenced strongly by the Renovation policy in agriculture as well as the process of industrialization and modernization in the country. Climate change over the past 5 years (2005-2011) has started influencing household land use with the concrete manifestations being the reduction of the area cultivated and the changing of the purpose of land use.

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