Influence of distance between residence and health facilities on non-communicable diseases: An assessment over hypertension and diabetes in Bangladesh

Hypertension, diabetes, and hypercholesterolemia in Bangladesh: Evaluating role of physical activity from cross-sectional STEPS 2018 survey

Background and Aims

The objective of this study was to assess current condition of three noncommunicable diseases (NCDs)-diabetes, hypertension, and hypercholesterolemia and vulnerable cohorts among adults in Bangladesh.

Methods

The STEPwise Approach to the NCD Risk Factor Surveillance survey of 2018 was analyzed to evaluate the association between NCDs and sociodemographic factors, levels of physical activity, and behavioral measurements. Complex survey weight-adjusted logistic models were fitted.

Results

From 6875 samples, prevalence of diabetes, hypertension and hypercholesterolemia were 27.3%, 9.8%, and 30.2%, respectively. The prevalence of the three NCDs were higher among older respondents. Low occupational activity with obese-BMI status people was more prone to NCDs. Lower prevalence of hypercholesterolemia was observed in Rangpur, Rajshahi, and Mymensingh, whereas lesser diabetes in Khulna region. Likelihood of NCDs were higher among highly educated, urban residents with low physical activity. Lesser physical activity, and lack of weight maintenance were found to be key factors in higher rates of NCDs in Bangladesh.

Conclusion

Greater education and less strenuous profession led to a higher chance of NCDs. Overall, physical activity and maintenance of weight seem to be factors driving higher rates of NCDs in Bangladesh. As a preventive measure against NCDs, an active lifestyle is to be encouraged, particularly to the most vulnerable cohort.

Associations of the built environment with type 2 diabetes in Asia: a systematic review

OBJECTIVES

Our study aimed to systematically review the literature and synthesise findings on potential associations of built environment characteristics with type 2 diabetes (T2D) in Asia.

DESIGN

Systematic review of the literature.

DATA SOURCES

Online databases Medline, Embase and Global Health were used to identify peer-reviewed journal articles published from inception to 23 January 2023.

ELIGIBILITY CRITERIA

Eligible studies included cohort, cross-sectional and case-control studies that explored associations of built environment characteristics with T2D among adults 18 years and older in Asia.

DATA EXTRACTION AND SYNTHESIS

Covidence online was used to remove duplicates and perform title, abstract and full-text screening. Data extraction was carried out by two independent reviewers using the OVID database and data were imported into MS Excel. Out of 5208 identified studies, 28 studies were included in this systematic review. Due to heterogeneity in study design, built environment and outcome definitions, a semiqualitative analysis was conducted, which synthesised results using weighted z-scores.

RESULTS

Five broad categories of built environment characteristics were associated with T2D in Asia. These included urban green space, walkability, food environment, availability and accessibility of services such as recreational and healthcare facilities and air pollution. We found very strong evidence of a positive association of particulate matter (PM_2.5, PM₁₀), nitrogen dioxide and sulfur dioxide (p<0.001) with T2D risk.

CONCLUSION

Several built environment attributes were significantly related to T2D in Asia. When compared with Western countries, very few studies have been conducted in Asia. Further research is, therefore, warranted to establish the importance of the built environment on T2D. Such evidence is essential for public health and planning policies to (re)design neighbourhoods and help improve public health across Asian countries.

PROSPERO REGISTRATION NUMBER

CRD42020214852.

Undiagnosed status and associated factors of hypertension among adults living in rural of central, Ethiopia, 2020: Uncovering the hidden magnitude of hypertension

BACKGROUND

Hypertension is a major risk factor for cardiovascular (CVD) disease related deaths worldwide. It affects more than 20% of adults in Ethiopia, making it a major public health concern. Although it is important to uncover the hidden extent of hypertension, there is limited information on the proportion of undiagnosed hypertension in rural areas of the country.

OBJECTIVE

This study aimed to determine the magnitude of undiagnosed hypertension and associated factors among adults living in the rural Dano district, Central Ethiopia 2020.

METHODS AND MATERIALS

A quantitative, community-based cross-sectional study conducted from May to July 2020. A three-stage sampling technique was used to select a total of 605 study participants. A Validated tool was used to assess the participant's behavioral characteristics. Blood pressure was measured using digital blood pressure apparatus. The mean of three blood measurements was used to classify hypertension after intra-class correlation was tested. Standardized instruments were used to assess participants' health-seeking behavior and knowledge of the hypertensive disease. The proportion of undiagnosed hypertension was determined among patients with hypertension. The regression analyses were done to determine factors associated with undiagnosed hypertension. The adjusted odds ratio with 95% CI was estimated to measure the strength of the association. The level of statistical significance was set at a p-value < 0.05.

RESULTS

The prevalence of undiagnosed hypertension was 21.32% (CI: 19.95%, 25.8%). Living in a household with the low wealth index [(AOR: 3.5,95%CI: (1.6,6.4)], far distance to health facility, [(AOR: 0.155,95%CI: (0.11.0.67)], underweight, [AOR = 2.2.1,95%CI:(2.00,4.22)], use of smokeless tobacco products, [AOR = 3.2,95%Cl:(1.88,4.75)], and participants' knowledge of hypertension were independently associated with undiagnosed hypertension.

CONCLUSION

This study shows that undiagnosed hypertension is a major public health problem in the study area. Living in a household with a low wealth index, being far from a health facility, being underweight, using smokeless tobacco products, and having little knowledge about hypertension increase the likelihood of having undiagnosed Hypertension. Hypertension health information, particularly to smokes tobacco users, could improve the perceived susceptibility to hypertensive disease, and reduce the hidden extent of hypertension.

Rural–Urban Disparities in Realized Spatial Access to General Practitioners, Orthopedic Surgeons, and Physiotherapists among People with Osteoarthritis in Alberta, Canada

Rural Canadians have high health care needs due to high prevalence of osteoarthritis (OA) but lack access to care. Examining realized access to three types of providers (general practitioners (GPs), orthopedic surgeons (Ortho), and physiotherapists (PTs)) simultaneously helps identify gaps in access to needed OA care, inform accessibility assessment, and support health care resource allocation. Travel time from a patient’s postal code to the physician’s postal code was calculated using origin–destination network analysis. We applied descriptive statistics to summarize differences in travel time, hotspot analysis to explore geospatial patterns, and distance decay function to examine the travel pattern of health care utilization by urbanicity. The median travel time in Alberta was 11.6 min (IQR = 4.3–25.7) to GPs, 28.9 (IQR = 14.8–65.0) to Ortho, and 33.7 (IQR = 23.1–47.3) to PTs. We observed significant rural–urban disparities in realized access to GPs (2.9 and IQR = 0.0–92.1 in rural remote areas vs. 12.6 and IQR = 6.4–21.0 in metropolitan areas), Ortho (233.3 and IQR = 171.3–363.7 in rural remote areas vs. 21.3 and IQR = 14.0–29.3 in metropolitan areas), and PTs (62.4 and IQR = 0.0–232.1 in rural remote areas vs. 32.1 and IQR = 25.2–39.9 in metropolitan areas). We identified hotspots of realized access to all three types of providers in rural remote areas, where patients with OA tend to travel longer for health care. This study may provide insight on the choice of catchment size and the distance decay pattern of health care utilization for further studies on spatial accessibility.

Availability and Affordability of Primary Health Care Among Vulnerable Populations in Urban Kumasi Metropolis: Family Health Perspective

Purpose

Health-related expenditures pose a significant burden on vulnerable populations. This study assessed the availability and affordability of primary health care among disadvantaged populations in urban Kumasi Metropolis, Ghana.

Methods

This study was a descriptive cross-sectional study conducted among multi-level participants of vulnerable populations ≥18 years of age (n=710) constituting the older adults/aged, pregnant women, head porters, sex workers, and other vulnerable groups (people with disabilities and the homeless). Data were collected using a semistructured questionnaire. Poisson regression with robust variance was used to assess the association between vulnerability and access to health care.

Results

There were significant differences in the availability and adequacy of health care among the vulnerable groups studied. Distance to the source of care was >5 km for majority of the vulnerable groups and the average expenditure on a visit to the health facility was GH¢ 27.04 (∼US$ 5.55 as at January 2019). Challenges to health care among the vulnerable groups included monetary (37.9%), stigmatization (18.6%), and staff attitude (25.9%). Head porters and other vulnerable groups were less likely to view health care as affordable compared with older adults. The difference in the perception of health care affordability was, however, explained by sociodemographic characteristic and health care-related factors.

Conclusion

Despite the introduction of a National Health Insurance Scheme in Ghana, this study highlights challenges in health care access among vulnerable populations independent of the type of vulnerability. This suggests the need for stakeholders to adopt other innovative care strategies that may have broader applicability for all populations.

Tweedie Model for Predicting Factors Associated with Distance Traveled to Access Inpatient Services in Kenya

Aim. This study aims to examine which factors influence the distance traveled by patients for inpatient care in Kenya. Methods. We used data from the fourth round of the Kenya Household Health Expenditure and Utilization survey. Our dependent variable was the self-reported distance traveled by patients to access inpatient care at public health facilities. As the clustered data were correlated, we used the generalized estimating equations approach with an exchangeable correlation under a Tweedie distribution. To select the best-fit covariates for predicting distance, we adopted a variable selection technique using the $QI{C}_u$ and $R^2$ criteria, wherein the lowest (highest) value for the former (latter) is preferred. Results. Using data for 451 participants from 47 counties, we found that three-fifths were admitted between 1 and 5 days, two-thirds resided in rural areas, and 90% were satisfied with the facilities’ service. Wealth quintiles were evenly distributed across respondents. Most admissions (81%) comprised $<$ 15, $>$ 65, and 25–54 years. Many households were of medium size (4–6 members) and had low education level (48%), and nine-tenths had no access to insurance. While two-thirds reported employment-based income, the same number reported not having cash to pay for inpatient services; 6 out of 10 paid over 3000 KES. Thus, differences in employment, ability to pay, and household size influence the distance traveled to access government healthcare facilities in Kenya. Interpretation. Low-income individuals more likely have large households and live in rural areas and, thus, are forced to travel farther to access inpatient care. Unlike the unemployed, the employed may have better socioeconomic status and possibly live near inpatient healthcare facilities, thereby explaining their short distances to access these services. Policymakers must support equal access to inpatient services, prioritize rural areas, open job opportunities, and encourage smaller families.

The Effect of High-Density Built Environments on Elderly Individuals' Physical Health: A Cross-Sectional Study in Guangzhou, China

The built environment refers to the objective material environment built by humans in cities for living and production activities. Existing studies have proven that the built environment plays a significant role in human health, but little attention is paid to the elderly in this regard. At the same time, existing studies are mainly concentrated in Western developed countries, and there are few empirical studies in developing countries such as China. Based on POI (point of interest) data and 882 questionnaires collected from 20 neighborhoods in Guangzhou, we employ multilevel linear regression modeling, mediating effect modeling, to explore the path and mechanism of the impact of the built environment on elderly individuals' physical health, especially the mediating effects of physical and social interaction activity. The results show that the number of POIs, the distance to the nearest park and square, and the number of parks and squares are significantly positively correlated with the physical health of the elderly, while the number of bus and subway stations and the distance to the nearest station are significantly negatively correlated. Secondly, physical activity and social networks play a separate role in mediating the effect of the built environment on elderly individuals' physical health. The results enrich the research on the built environment and elderly individuals' health in the context of high-density cities in China and provide some reference basis for actively promoting spatial intervention and cultivating a healthy aging society.

Does where mothers live matter? Regional variations in factors influencing place of child delivery in Nigeria

Utilization of health care facilities for child delivery is associated with improved maternal and neonatal outcomes, but less than half of mothers use these for child delivery in Nigeria. This study investigated the factors associated with facility delivery in Nigeria, and their variation between the Northern and Southern parts of the country - two regions with distinct socio-cultural make-ups. The study included 33,924 mothers aged 15-49 who had given birth in the last 5 years preceding the 2018 Nigeria Demographic and Health Survey. Overall, higher age, being educated, being a Christian, being an urban resident, being exposed to mass media, making joint decisions with partner on health care, beginning antenatal visits in the first trimester and attending antenatal clinics frequently were found to be associated with improved use of a health care facility for child delivery. An average mother in Northern Nigeria had a 38% chance of having a facility-based delivery, whereas the likelihood in the South was 76%. When other factors were adjusted for, age and listening to the radio were significant predictors of facility-based delivery in the South but not in the North. In the North, Christians were more likely than Muslims to have a facility-based delivery, but the reverse was true in the South. Rural women in the South had a 16% greater chance of having a facility-based delivery than urban women in the North. The study results suggest that there is inequality in access to health care facilities in Nigeria, and the differences in the socio-cultural make-up of the two regions suggest that uniform intervention programmes may not yield similar results across the regions. The findings give credence to, and expand on, the Cosmopolitan-Success and Conservative-Failure Hypothesis.

Impacts of Anthropometric, Biochemical, Socio-demographic, and Dietary Habits Factors on the Health Status of Urban Corporate People in a Developing Country

This study focused on urban corporate people and applied multinomial logistic regression (MLR) to identify the impact of anthropometric, biochemical, socio-demographic and dietary habit factors on health status. Health status is categorized into four levels: healthy, caution, affected, and emergent. A cross-sectional study, based on convenience sampling method, was conducted to select 271 employees from 18 institutions under the Grameen Bank Complex, Dhaka, Bangladesh. Biochemical measurements such as blood uric acid are highly significant variables in the MLR model. When holding other factors as constants, with a one-unit increase in blood uric acid, a person is 11.02 times more likely to be "emergent" compared to "caution". The odds are also higher, at 1.82, for the blood uric acid to be "affected" compared "caution". The results of this study can help to prevent a large proportion of non-communicable diseases (NCDs) by reducing the most significant risk factor: blood uric acid. This study can contribute to the establishment of combined actions to improve disease management.

Hypertension prevalence and its trend in Bangladesh: evidence from a systematic review and meta-analysis

Background

Hypertension, itself being a major chronic condition, is one of the most significant risk factors for premature cardiovascular diseases and mortality. Hypertension is responsible for 13% of global deaths and three-quarters of the world’s hypertensive population reside in low- and middle-income countries. Bangladesh is one of those countries that experiencing an epidemiological transition from communicable to non-communicable diseases, a nutritional transition from a traditional diet to process and fast food, and an increase in a sedentary lifestyle, resulting in increased hypertension prevalence. We carried out a systematic review and meta-analysis to identify existing research on hypertension prevalence in Bangladesh, summarize findings and assess its temporal change.

Methods

We searched MEDLINE, EMBASE and PubMed and relevant references to identify studies on the prevalence of hypertension in Bangladesh. We used Random-effects meta-analysis to pool the prevalence estimates and performed subgroup analyses. We assessed heterogeneity, a trend in prevalence of hypertension and publication bias in selected studies.

Results

Our search initially identified 735 articles and after removing duplicates, reviewing titles and abstracts, and screening full texts, 53 studies were finally selected. The studies comprised 305,432 subjects and reported overall, gender-specific, geographical location specific and criteria specific prevalence of hypertension. We identified the range of hypertension prevalence is from 1.10% to 75.0% and the overall weighted pooled prevalence of hypertension is 20.0%. An extremely high heterogeneity (I² = 99.53%; Cochran Q-statistic p < 0.001) was observed in the prevalence of hypertension. Consequently, we performed subgroup analysis based on gender, age group and geographical location of the study participants, the cut-off level used to define hypertension, and the types of hypertension reported and presented our findings accordingly. An overall increasing trend of hypertension prevalence is also observed.

Conclusions

The prevalence of hypertension is high and rising in Bangladesh. Strategies targeting prevention are required to mitigate a further increase in the prevalence and reduce the morbidity and mortality associated with it.

Distance sampling for epidemiology: an interactive tool for estimating under-reporting of cases from clinic data

BACKGROUND

Distance sampling methods are widely used in ecology to estimate and map the abundance of animal and plant populations from spatial survey data. The key underlying concept in distance sampling is the detection function, the probability of detecting the occurrence of an event as a function of its distance from the observer, as well as other covariates that may influence detection. In epidemiology, the burden and distribution of infectious disease is often inferred from cases that are reported at clinics and hospitals. In areas with few public health facilities and low accessibility, the probability of detecting a case is also a function of the distance between an infected person and the "observer" (e.g. a health centre). While the problem of distance-related under-reporting is acknowledged in public health; there are few quantitative methods for assessing and correcting for this bias when mapping disease incidence. Here, we develop a modified version of distance sampling for prediction of infectious disease incidence by relaxing some of the framework's fundamental assumptions. We illustrate the utility of this approach using as our example malaria distribution in rural Burkina Faso, where there is a large population at risk but relatively low accessibility of health facilities.

RESULTS

The modified distance-sampling framework was used to predict the probability of reporting malaria infection at 8 rural clinics, based on road-travel distances from villages. The rate at which reporting probability dropped with distance varied between clinics, depending on road and clinic positions. The probability of case detection was estimated as 0.3-1 in the immediate vicinity of the clinic, dropping to 0.1-0.6 at a travel distance of 10 km, and effectively zero at distances > 30-40 km.

CONCLUSIONS

To enhance the method's strategic impact, we provide an interactive mapping tool (as a self-contained R Shiny app) that can be used by non-specialists to interrogate model outputs and visualize how the overall probability of under-reporting and the catchment area of each clinic is influenced by changing the number and spatial allocation of health centres.

Constructing a knowledge-based heterogeneous information graph for medical health status classification

Applying Pearson correlation and semantic relations in building a heterogeneous information graph (HIG) to develop a classification model has achieved a notable performance in improving the accuracy of predicting the status of health risks. In this study, the approach that was used, integrated knowledge of the medical domain as well as taking advantage of applying Pearson correlation and semantic relations in building a classification model for diagnosis. The research mined knowledge which was extracted from titles and abstracts of MEDLINE to discover how to assess the links between objects relating to medical concepts. A knowledge-base HIG model then was developed for the prediction of a patient's health status. The results of the experiment showed that the knowledge-base model was superior to the baseline model and has demonstrated that the knowledge-base could help improve the performance of the classification model. The contribution of this study has been to provide a framework for applying a knowledge-base in the classification model which helps these models achieve the best performance of predictions. This study has also contributed a model to medical practice to help practitioners become more confident in making final decisions in diagnosing illness. Moreover, this study affirmed that biomedical literature could assist in building a classification model. This contribution will be advantageous for future researchers in mining the knowledge-base to develop different kinds of classification models.

Achieving explanatory depth and spatial breadth in infectious disease modelling: Integrating active and passive case surveillance

Ideally, the data used for robust spatial prediction of disease distribution should be both high-resolution and spatially expansive. However, such in-depth and geographically broad data are rarely available in practice. Instead, researchers usually acquire either detailed epidemiological data with high resolution at a small number of active sampling sites, or more broad-ranging but less precise data from passive case surveillance. We propose a novel inferential framework, capable of simultaneously drawing insights from both passive and active data types. We developed a Bayesian latent point process approach, combining active data collection in a limited set of points, where in-depth covariates are measured, with passive case detection, where error-prone, large-scale disease data are accompanied only by coarse or remotely-sensed covariate layers. Using the example of malaria, we tested our method's efficiency under several hypothetical scenarios of reported incidence in different combinations of imperfect detection and spatial complexity of the environmental variables. We provide a simple solution to a widespread problem in spatial epidemiology, combining latent process modelling and spatially autoregressive modelling. By using active sampling and passive case detection in a complementary way, we achieved the best-of-both-worlds, in effect, a formal calibration of spatially extensive, error-prone data by localised, high-quality data.

Antenatal care and skilled birth attendance in Bangladesh are influenced by female education and family affordability: BDHS 2014

OBJECTIVES

Antenatal care (ANC) during pregnancy and skilled birth attendance (SBA) during delivery are important policy concerns to reduce maternal deaths. Bangladesh is one of the developing countries which has made remarkable progress in both services during the last couple of decades by improving the SBA service rate from 16% in 2004 to 42.1% in 2014. However, this rate remains below the targeted level (50%) of the Health Population and Nutrition Sector Development Program set by the Ministry of the Health and Family Welfare of Bangladesh. This article explored the sociodemographic factors associated with the ANC and SBA service attainment. Furthermore, the possible implication of using ANC on SBA was also investigated.

STUDY DESIGN

The study followed a cross-sectional design using the Bangladesh demographic and health survey 2014, with a sample of size 4603 women with at least one live birth 3 years preceding the survey.

METHODS

Following a bivariate analysis, linear mixed-effect models were used to assess the relationship between sociodemographic factors and the outcome indicators (ANC and SBA). Finally, the association between SBA and ANC was evaluated through another mixed-effect model.

RESULTS

Wealth index, participation in household decisions, and partner's and respondent's education were significant predictors of ANC; whereas, residence, age at first birth, wealth index, working status, participation in household decisions, and partner and respondent's education were significant for SBA. Female education and household affordability were the strongest predictors for both ANC and SBA. ANC showed significant association with SBA as women accessing essential ANC during delivery seemed to be 4 times more likely (95% confidence interval: 3.05-5.93) to avail SBA services.

CONCLUSIONS

Overall, four factors were significant: residence, wealth index, education, and ANC access. Women residing in urban areas, having higher financial solvency, completing higher education, and accessing ANC by skilled personnel were more likely to receive SBA at delivery than their counterparts. Accessibility to skilled care during pregnancy leads to increased professional care during delivery. Thus, policies to encourage women and heads of families to seek skilled care during pregnancy would be beneficial to reach the maternal healthcare targets of Bangladesh.