Sampling Design Research Articles

Change detection due to ISPAAD Programme using geospatial techniques: A case study of Dinogeng Agricultural Extension Area of Kgatleng District, Botswan

Dinogeng Agricultural Extension Area (DAEA), located in the south eastern part of Botswana has witnessed tremendous land use changes due to the Integrated Support Programme for Arable Agriculture Development (ISPAAD). For over a decade, crop cultivation has been relatively small both in size and population. But today, Dinogeng is one of the fastest growing agricultural areas. Therefore, it is paramount to detect the nature and magnitude of land use changes for planning purpose. Remotely Sensed data from Landsat 5 and Landsat 8 were utilized for the purpose of Land Use Land Cover (LULC) change detection. Geographical Information Systems (GIS) and Remote Sensing (RS) were used to produce LULC maps for 2006 and 2020 for assessing the severity of land degradation. In a 14-year span (2006-2020), LULC of DAEA changed markedly. Cultivated land and bare areas increased by 19.4 and 18.3 % whereas shrub land and forest areas decreased by 36.9 and 0.7 %, respectively. Supervised classification algorithms and stratified random sampling design were adopted for the accuracy assessment. The classification process produced good results with overall accuracies of 93% and 94% for the 2006 and 2020 maps, respectively. The findings could be useful to guide the development of functional land use plan for DAEA.

Effects of spatial versus seasonal sources of environmental variability in springs: a case study of microcrustaceans (Ostracoda, Harpacticoida) in a calcareous helocrene

The cold temperate helocrenes are usually attributed to high biodiversity because of environmental heterogeneity. Their temporal stability of environmental conditions reduces seasonal changes in assemblage composition. However, the within-site patterns and processes have been only rarely studied in springs, thus our knowledge remains limited. In this study, we investigated a microcrustacean assemblage of a helocrenic calcareous spring at a high spatial resolution. We tested differences among visually distinct mesohabitats, and related the assemblage composition variation to environmental variables and seasonal changes by a repeated sampling in spring, summer and autumn. At this single site, we recorded 26 species of ostracods and harpacticoids, accounting for almost 50% of the whole known regional species pool. Species richness and composition varied significantly between the mesohabitats, the latter mainly due to differences in environmental variables (mainly water depth and temperature). The occurrence of cold-adapted species was restricted to the spring source, but species inhabiting other mesohabitats had clearly broader ecological niches. Despite significant temporal changes in water temperature, microcrustaceans showed almost negligible seasonal changes in species composition, suggesting that their microdistribution remains stable throughout the year. Our findings have important implications for sampling design of large-scale ecological studies and spring conservation.

Integrating deep reinforcement learning and improved artificial potential field method for safe path planning for mobile robots

PurposeThis paper aims to address the safety concerns of path-planning algorithms in dynamic obstacle warehouse environments. It proposes a method that uses improved artificial potential fields (IAPF) as expert knowledge for an improved deep deterministic policy gradient (IDDPG) and designs a hierarchical strategy for robots through obstacle detection methods.Design/methodology/approachThe IAPF algorithm is used as the expert experience of reinforcement learning (RL) to reduce the useless exploration in the early stage of RL training. A strategy-switching mechanism is introduced during training to adapt to various scenarios and overcome challenges related to sparse rewards. Sensor inputs, including light detection and ranging data, are integrated to detect obstacles around waypoints, guiding the robot toward the target point.FindingsSimulation experiments demonstrate that the integrated use of IDDPG and the IAPF method significantly enhances the safety and training efficiency of path planning for mobile robots.Originality/valueThis method enhances safety by applying safety domain judgment rules to improve APF’s security and designing an obstacle detection method for better danger anticipation. It also boosts training efficiency through using IAPF as expert experience for DDPG and the classification storage and sampling design for the RL experience pool. Additionally, adjustments to the actor network’s update frequency expedite convergence.

Boosting Perceptions of the Benefits of Complication Prevention in Reproductive Age Diabetes Mellitus Patients via Self-Talk Affirmation Intervention

Diabetes mellitus is a chronic disease that lasts a long time and requires high adherence and self-discipline to carry out comprehensive self-care management to control blood glucose levels and prevent further complications. The practice of self-management requires knowledge or literacy and a positive mindset that is supported by good self-confidence for DM sufferers to be able to do it. Several studies have only examined aspects of physical intervention, such as providing physical activity (DM gymnastics) and education on medication adherence, but there are still few interventions that provide mindset strengthening in the form of self-talk affirmations in order to form a positive perspective on the perception of the benefits of preventing DM complications in sufferers. The study's objective was to ascertain whether using self-talk affirmations would improve DM patients' perceptions of the benefits of preventing complications in Pekalongan Regency, Central Java, Indonesia. 158 individuals with DM participated in this study using a cross-sectional quantitative research approach and a pre-post test sample design. A questionnaire was utilized for data collection, and a Paired T-test for data analysis, which assessed patients' perceptions of the benefits of preventing DM complications either before and after receiving affirmative self-talk therapies. Patients' perceptions of the benefits of preventing DM complications are influenced by the results of self-talk and self-affirmation interventions; there is a difference in the mean score of perceived benefits before and after the intervention. For patients with DM who are of working age, self-talk affirmations might be included to a list of self-management interventions.

Exposure to bovine livestock and latent tuberculosis infection in children: Investigating the zoonotic tuberculosis potential in a large urban and peri-urban area of Cameroon.

Bovine tuberculosis (bTB), a neglected zoonotic disease, is endemic in cattle in many Sub-saharan African countries, yet its contribution to tuberculosis (TB) burden is understudied. Rapid urbanisation and increase in demand for animal proteins, including dairy products, increases the risk of spill over. This study compared the latent tuberculosis infection (LTBI) risk in children, a proxy-measure for recent TB infection, in children living in high cattle density areas to children from the general population in Cameroon. Cross-sectional study in the Centre Region of Cameroon in 2021, recruiting 160 children aged 2-15 years, stratified by exposure to livestock, people treated for pulmonary TB (PTB) and the general community. Veinous blood was tested for LTBI using QuantiFERON-TB Gold-Plus. Prevalence were calculated and the association to exposure and other risk factors investigated using logistic regression models. The crude LTBI prevalence were 8.2% in the general population, 7.3% in those exposed to cattle and 61% in pulmonary TB household contacts. After adjusting for confounding and sampling design, exposure to cattle and exposure to pulmonary TB were associated with higher risk of LTBI than the general population (respectively odds ratio (OR): 3.56, 95%CI: 0.34 to 37.03; and OR: 10.36, 95%CI: 3.13 to 34.21). Children frequently consuming cow milk had higher risk of LTBI (OR: 3.35; 95%CI 0.18 to 60.94). Despite limited statistical power, this study suggests that children exposed to cattle in a setting endemic for bTB had higher risk of LTBI, providing indirect evidence that Mycobacterium bovis may contribute to TB burden.

Approaches in Adult Glioblastoma Treatment: A Systematic Review of Emerging Therapies.

Glioblastoma (GB) is the most common and aggressive primary brain tumor in adults, characterized by complex genetic changes and a poor prognosis. Current standard therapies, including surgery, chemotherapy, and radiotherapy, have limited effectiveness. Emerging therapeutic strategies aim to address the high recurrence rate and improve outcomes by targeting glioblastoma stem cells (GSCs), the blood-brain barrier, and utilizing advanced drug delivery systems. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. An electronic search was conducted across several databases, including PubMed, Embase, Scopus, Web of Science, and Cochrane, covering studies published from January 2019 to May 2024. The inclusion criteria encompassed primary research studies in English focusing on emerging therapies for treating GB in adults. Eligible studies included experimental and observational studies. Only peer-reviewed journal articles were considered. Exclusion criteria included non-human studies, pediatric studies, non-peer-reviewed articles, systematic reviews, case reports, conference abstracts, and editorials. The search identified 755 articles and, finally, 24 of them met the inclusion criteria. The key findings highlight various promising therapies. Despite advances in treatment approaches, the complexity and heterogeneity of GB necessitate ongoing research to optimize these innovative strategies. The study has limitations that should be considered. The inclusion of only English-language articles may introduce language bias, and the focus on peer-reviewed articles could exclude valuable data from non-peer-reviewed sources. Heterogeneity among studies, particularly in sample sizes and designs, complicates comparison and synthesis, while the reliance on preclinical models limits generalizability to clinical practice. Nonetheless, this review provides a comprehensive overview of the emerging therapies that hold promise for improving patient outcomes in GB treatment.

A near-linear transect sampling method for validation of SMAP surface soil moisture in non-complex terrains

ABSTRACT The global validation for SMAP (Soil Moisture Active Passive) Level-4 surface soil moisture using well-established core validation sites does not comprehensively account for all landscapes on earth’s surface due to the diverse nature of their intrinsic characteristics. Due to the inhibitive cost of implementing a standard validation site, this study presents an alternative sampling approach suitable for localized validation of SMAP data in non-complex terrains. It involves clustering a large heterogeneous study area to smaller units of non-complex terrains where landscape-defining characteristics are largely homogeneous, thus permitting the computation of areal soil moisture as a simple arithmetic mean of near-linear point measurements. This allows optimization of limited resources (a hand-held moisture sensor with site-specific calibrations) to balance the need for spatial representativeness of samples in the sampling unit and the need for temporal proximity of sampled measurements to the aggregation time of the satellite product being validated. For ease of movement, transect sampling is implemented along access roads that run across the sampling units to allow sufficient measurement replications within a reasonably short time. Validations with four different landscapes in Kenya show a good agreement between in situ measurements and SMAP with R2 of 0.76, 0.72, 0.80, and 0.82, and biases of −0.0246, +0.0113, 0.0004, and + 0.0035 m3 m−3, respectively for Mawego, Kuresoi, Sotik and Kapsuser sites. These results only marginally differ from those obtained with a spatially distributed sampling method, indicating the potential of the proposed sampling design for time and cost effectiveness in validations at non-complex terrains. An analysis of the temporal variability of SMAP soil moisture in the watershed is also presented, with an assessment of its significance in the selection of sampling sites for validation. Particularly, the concept of temporal stability of soil moisture as a basis for clustering validation sites is evaluated.

HIV prevalence and associated factors among adolescent boys and young men in South Africa: 2017 nationally representative household-based population survey

IntroductionThere is growing recognition that adolescent boys and young men (ABYM) have been left behind in the HIV response and are under-represented in HIV services, leading to poor outcomes across...

Impact of mass media campaigns on knowledge of malaria prevention measures among pregnant mothers in Uganda: a propensity score-matched analysis

BackgroundUganda grapples with a considerable malaria burden, reporting prevalence rates of over 33% in some regions. To address this, the Uganda Ministry of Health employs audiovisual platforms for disseminating malaria prevention messages. However, the impact of these messages on pregnant women’s knowledge of malaria prevention remains insufficiently explored. This paper therefore emphasizes the influence of audiovisual messages on the knowledge of malaria prevention measures among pregnant women in Uganda.MethodsSecondary data obtained from the Uganda Malaria Indicator Survey (MIS) 2018–2019 was used for this analysis. Women aged 15–49 were included in the study. A total of 8868 women were selected using a two-stage sample design. The two stages of selection included clusters and households. Women who were currently pregnant were included in the study, resulting in a weighted sample of 721 women. Propensity score-matched analysis was used to evaluate the impact of access to malaria messages on knowledge of prevention measures.ResultsThe study revealed that 39% [95% CI 34.0–44.2] of pregnant women were exposed to malaria messages before the survey. Those exposed had a 17.2% higher knowledge [ATT = 0.172; 95% CI 0.035–0.310] of using mosquito nets for prevention compared to those unexposed. Among women exposed, radios accounted for most form of access to mass media campaigns [64.8, 95% CI 57.0–71.8] followed by interpersonal communication [45.0, 95% CI 37.6–52.6], community health workers [38.8, 95% CI 29.6–48.8], community events [21.4, 95% CI 15.8–28.3], and social mobilization [18.3, 95% CI 12.7–25.8].ConclusionResults highlight the importance of radios in spreading important malaria prevention messages to pregnant women. Being exposed to these messages is linked to increased awareness and knowledge about the proper use of insecticide-treated bed nets (ITNs) for preventing malaria. This finding underscores the importance of evaluating different channels for mass media campaigns to ensure the effective delivery of information about malaria prevention to the intended audiences.

Heart failure related fatigue: An exploratory analysis of serum osmolality from the national health and nutrition examination survey

BackgroundFatigue is a prominent symptom of heart failure (HF). However, underlying mechanisms remain poorly understood. Fluid volume status has been suggested as a physiologic mechanism of HF-related fatigue. Serum osmolality may fluctuate with changes in volume status associated with neurohormonal dysregulation. The relationship of fatigue to serum osmolality has not been assessed in adults with HF. ObjectivesDescribe the relationship between serum osmolality and fatigue in adults with HF. MethodsWe analyzed two waves of cross-sectional data from the National Health and Nutrition Examination Survey (2015–2016 and 2017–2018). Adults who self-reported having HF without select co-morbid conditions known to contribute to fatigue were included. Data were weighted to provide US national estimates, and complex sample design used for analyses. Sequential logistic regression was used to isolate the effect of serum osmolality on the odds of having fatigue. ResultsData from the sample represented 1.4 million Americans with HF (58.5 % male; median age 68 years), of whom 1,001,589 (67.9 %) reported fatigue. Participants with fatigue had lower serum osmolality compared to those without fatigue (t = -3.04, p = .009). Higher serum osmolality was associated with 8.8 % lower odds of experiencing fatigue when controlling for sex and body mass index (OR = 0.912, p = .007, CI 0.857 - 0.972). ConclusionsHF-related fatigue is associated with lower serum osmolality. Low serum osmolality may indicate excess volume and the presence of a heightened neurohormonal response, both of which may influence fatigue. Alternatively, serum osmolality may directly affect other physiologic changes that may contribute to fatigue.

Revealing the impact of spatial bias in survey design for habitat mapping: A tale of two sampling designs

Submerged aquatic vegetation, referring to benthic macroalgae and plants that obligately grow underwater, are critical components of marine ecosystems and are frequently found to provide preferential recruitment habitats. The mapping and monitoring of aquatic vegetation through remote sensing and machine learning is becoming an important aspect of managing coastal environments at scale. Accurate mapping and monitoring require robust sampling and occurrence data to assess predictive error and quantify submerged vegetation extents. The form of ground truthing survey design (preferential, random, grid-based or spatially balanced) could significantly influence predictive model outcomes and the overall accuracy of mapping and monitoring. Here, we test and contrast mapping aquatic vegetation extent ground-truthed using two different sampling designs: we used both preferential and spatially balanced sampling designs across four coastal sites along the midwest of Australia. We validate the map outcomes using spatial cross-validation and demonstrate that spatially balanced ground truthing significantly outperforms preferential sampling designs regarding modelled extent and map accuracy. In our comparison, we found that, on average, preferential designs overestimated vegetation extent by 25 percent compared to balanced designs and achieved an average kappa statistic, F1 score and Area under the Curve of 0.48, 0.615 and 0.517, respectively; whereas balanced designs achieved a kappa statistic, F1 score and AUC of 0.84, 0.85 and 0.83 respectively. We strongly recommend that sampling designs for remote sensing-derived habitat models be spatially balanced where habitat extent is proposed as a metric for monitoring.

Achieving SOC Conservation without Land-Use Changes between Agriculture and Forests

Global land-use changes impact soil’s ability to perform essential functions. This study investigates whether soil organic carbon (SOC) can be conserved without altering land use in traditional farming systems and degraded natural forests, focusing on ‘disturbed’ agricultural soils and ‘undisturbed’ forest soils. We also examine the influence of dominant crops on SOC within the top 30 cm of soil in data-deficient regions of Nepal. Using a multi-stage cluster sampling design, we tested 12 regression models to identify the best relationships among variables such as SOC, soil bulk density (BD), pH, dominant crops, climate, topography, and management practices. Our analysis revealed similar SOC levels in both disturbed and undisturbed soils, indicating significant degradation in forested areas, whereas traditional farming systems could support SOC and preserve farm-based indigenous knowledge alongside food security. Further, SOC stocks varied significantly (p < 0.05) across different cropping systems, suggesting that managing dominant crops could be a strategy to optimize SOC, with these crops serving as indicators. Additionally, our results show that the weak linear correlation between SOC and BD in regularly disturbed soils, such as farmlands, where anthropogenic activities frequently alter soil bulk density, may be misleading when estimating bulk density-dependent SOC. This finding suggests the need for further research into varying degrees of anthropogenic disturbance in soil to confirm these results. While the site-specific nature of the findings warrants caution with respect to generalization, they provide valuable insights for carbon monitoring, climate actions, ecosystem health, and land-use management in similar traditional farming systems and degraded forests, particularly in data-poor regions.

Cannabis Use and Associated Risk Behavior Factors among High School Students in Mississippi: Youth Risk Behavior Surveillance System 2021.

Cannabis is the most used illicit drug among youths in the United States. The objectives of this study were to identify the association between cannabis use and other risk behaviors, including suicidality, among high school students. This is a cross-sectional study using the 2021 Mississippi Youth Risk Behavior Surveillance System (YRBS). The 2021 YRBS data sets were combined for this study. The crude odds ratio (OR) and adjusted odds ratio (AOR) with a 95% confidence interval were generated using the survey packages in R to account for weights and the complex sampling design of the YRBS data. Univariate analysis identified seven risky behaviors that were significantly associated with current cannabis use, including carrying weapons on school campuses, suicidal attempts, electronic vapor use, current smoking, current drinking, sexual behaviors, and unsupervised children. In multivariable analysis, after adjusting for gender, race, students' grades, and other risky behaviors, statistically significant variables for cannabis use included current use of electronic vapor, current smoking, current drinking, and sexual behaviors. Cannabis use is evenly burdened between males and females and between all race categories among Mississippi high school students. The identified associations seem to indicate that electronic vapor, tobacco products, and alcohol use could be the forerunners for drug use and should be treated accordingly in drug use prevention programs.

Longitudinal propagation of aquatic disturbances following the largest wildfire recorded in New Mexico, USA

Wildfire disturbance propagation along fluvial networks remains poorly understood. We use incident, atmospheric, and water-quality data from the largest wildfire in New Mexico’s history to quantify how this gigafire affected surface runoff processes and mobilized wildfire disturbances into fluvial networks after burning 1382 km2. Surface runoff post-fire increased compared to pre-fire conditions, and precipitation events that are frequently observed in the affected watershed (<2-year recurrence) and fell during the post-fire first rainy season resulted in uncorrelated, less frequently observed runoff events (10-year recurrence). Besides these shifts in runoff generation, the magnitude and fluctuation of daily water quality parameters and relevant ecosystem processes also shifted over multiple months, even at sites located >160 km downstream of the burn perimeter. Our findings emphasize the need to incorporate spatially resolved longitudinal sampling designs into wildfire water quality research and highlight the spatiotemporal co-dependency among atmospheric, terrestrial, and aquatic processes in defining the net outcome of wildfire disturbance propagation along impacted fluvial networks.

Efficient sampling designs to assess biodiversity spatial autocorrelation: should we go fractal?

Efficient sampling designs to assess biodiversity spatial autocorrelation: should we go fractal?

Do gravel highways affect water quality and invertebrate communities in Arctic lakes?

ABSTRACT Gravel roads are a common feature in developed areas of Canada’s Arctic. These roads can be a source of calcareous dust that drifts to roadside lakes, causing significant changes in conductivity, calcium, and pH levels. In this study, we examined if road proximity was associated with differences in water quality and invertebrate communities in lakes along the Dempster and Inuvik-Tuktoyaktuk Highways in the Northwest Territories, Canada. We collected biological and water quality data from 18 lakes selected using a stratified random sampling design, with distance from the road (0–300 m, 300–600 m, and >600 m) and region of study (boreal forest, tundra) as the two factors. We hypothesized that lakes closer to the road would exhibit differences in water quality and invertebrate communities associated with road dust pollution and other stressors caused by roads. We found no clear differences in water quality or invertebrate communities among lakes based on distance from the highways. In addition, while there were differences between regions, these did not appear to be related to the effects of the roadways. Our results suggest that variability in lake morphometry and water quality in this region might be more important than the influence of roads.

Teacher-centered analysis with TIMSS and PIRLS data: weighting approaches, accuracy, and precision

This paper extends existing work on teacher weighting in student-centered surveys by looking into aspects of practical implementation of deriving and using weights for teacher-centered analysis in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS). The formal conditions to compute teacher-centered weights are detailed, including mathematical equations. We provide a proposal on how to define the targeted populations as well as how to collect data that is needed to derive teacher-centered weights, yet currently unavailable. We also tackle the issue of teacher nonresponse by proposing a respective adjustment factor, as well as mentioning the challenge of multiple selection probabilities when teachers teach in multiple schools. The core part of the paper focuses on studying the level of accuracy that can be expected when estimating teacher population characteristics. We use TIMSS 2019 data and simulate likely scenarios regarding the variance in weights. The results show that (i) the different weighting scenarios lead to relatively similar estimates; however, the differences between the scenarios are sufficient to justify the recommendation to use correctly derived teacher weights; (ii) differences between estimated standard errors based on complex sampling and corresponding estimates based on simple random sampling are sufficiently consistent to support use of a procedure to estimate standard errors that accounts for both sample weights and the complex sampling design; (iii) sample sizes and variance in weights significantly limit estimate precision, so that total population estimates with sufficient precision are available in the majority of countries but subpopulation features are generally not sufficiently precise. To provide a critical evaluation of our results, we recommend implementation of the proposed method in one or more countries. This recommended study will permit examination of logistical considerations in implementation of required changes in data acquisition and will provide data to replicate the analysis with teacher-centered weights.

Strategic alliances and competitive advantage of commercial banks in Kenya

Commercial banks in Kenya operate in quite dynamic financial market environment and continue to experience stiff competition in the provision of financial services. The liberation of the financial markets has resulted into an upsurge in the number of institutions providing financial products and services, threatening the future of Kenyan commercial banks. This study aimed at determining the effect of strategic alliances on competitive advantage of commercial banks in Kenya. The objectives were to determine effect of joint ventures, equity alliances, and joint research and development on the competitiveness of Kenyan banks. The following theories informed this research; Resource Based View theory, competitive theory, and resource dependence theory. Causal research design was adopted where all the 42 Kenyan commercial banks formed the target population. Census survey sampling design was applied and semi-structured questionnaire used. Reliability and validity results were used to improve the research instrument prior to the actual data collection. Data was analyzed using descriptive and inferential statistics. Study found that joint venture (?=0.435, p=0.000) equity alliances (?=0.227, p=0.018), and joint research and development (?=0.0.612, p=0.000) had positive significant effects on competitive advantage. With a coefficient of determination (R-square) of 68.9% and overall p-value of 0.000, the study concluded strategic alliances have a statistical significant effect on competitive advantage. The study recommends that managements of commercial banks should fast-truck implementation of such alliances to for improved competitiveness.

Evaluating Binary Outcome Classifiers Estimated from Survey Data.

Surveys are commonly used to facilitate research in epidemiology, health, and the social and behavioral sciences. Often, these surveys are not simple random samples, and respondents are given weights reflecting their probability of selection into the survey. We show that using survey weights can be beneficial for evaluating the quality of predictive models when splitting data into training and test sets. In particular, we characterize model assessment statistics, such as sensitivity and specificity, as finite population quantities and compute survey-weighted estimates of these quantities with test data comprising a random subset of the original data. Using simulations with data from the National Survey on Drug Use and Health and the National Comorbidity Survey, we show that unweighted metrics estimated with sample test data can misrepresent population performance, but weighted metrics appropriately adjust for the complex sampling design. We also show that this conclusion holds for models trained using upsampling for mitigating class imbalance. The results suggest that weighted metrics should be used when evaluating performance on test data derived from complex surveys.

Prevalence of hypertension in pregnancy and its associated sociodemographic factors among mothers aged 15–49 years old in Malaysia

BackgroundHypertensive disorders of pregnancy (HDP) pose a substantial public health concern, ranking among the primary contributors to maternal and perinatal morbidity and mortality, impacting around 5–10% of pregnancies. This study aimed to determine the prevalence of HDP and its associated factors among mothers aged 15–49 who recently gave birth within the last two years, throughout Malaysia, informing effective public health and primary care interventions.MethodsThis study was a part of the national survey on maternal and child health (MCH) also known as the National Health and Morbidity Survey (NHMS) 2022: MCH. This was a cross-sectional study using two stage stratified random sampling design. Data of mothers aged 15–49 years old who recently gave birth within the last two years were selected in this study. This survey utilised a set of structured validated questionnaires administered via face-to-face interviews (using a mobile device). Multiple logistic regression analysis was employed to identify the associated factors for hypertension.ResultsAmong 6 335 participants recruited for this study with an estimated population of 782, 550, the prevalence of HDP among Malaysian mothers aged 15–49 years old who recently gave birth within the last two years was 6.5% (95% CI: 5.76, 7.37). Multiple logistic regression showed that maternal age and ethnicity were significantly associated with hypertension. Advanced maternal age had higher odds of hypertension, with an aOR of 2.18 (95% CI = 1.75, 2.71). In addition, Other Bumiputera had higher odds of hypertension (aOR = 2.71, 95% CI = 1.25, 5.87).ConclusionThis study reveals the prevalence of HDP among Malaysian women with children under 2 years old, emphasizing advanced maternal age (above 35) and ethnicity as notable risk factors. It improves understanding of the epidemiology of HDP in Malaysia, offering valuable insights for the development of effective public health strategies and clinical interventions that can help with the control of HDP.