BACKGROUND AND OBJECTIVE

Access to healthcare remains a challenge in most areas in the Philippines. Fifty-three percent (53%) of the Philippine population do not have access to a rural health unit (RHU) within a 30-minute travel t ime. As a response, the Department of Health (DOH) needs to construct an additional 2400 RHUs by 2025. This paper uses the Philippine Health Facility Development Plan 2020-2040 (PHFDP) as a reference to present a solution for locating sites for RHU placement in under-served areas using neural networks to meet the 30-minute travel time by maximizing population accessibility.

RHU accessibility was measured using geographic attributes as inputs to a back propagation neural network (BPNN) and a recurrent neural network (RNN): (1) land coverage and hazard data, representing geographical limitations; (2) population density and distribution, indicating demand for healthcare services; and (3) infrastructure-related features, such as road networks, points of interest, and the locations of existing RHUs, which influence healthcare accessibility. The models were trained to identify underserved areas and were implemented on a nationwide scale, excluding NCR, to locate candidate areas to increase population access to the new RHUs. The models were validated using a healthcare facility accessibility index (HCFAI) to assess RHU coverage improvement.

The BPNN showed stronger generalization across regions, achieving 79.1% average accuracy in distinguishing low from high accessible areas on Region 1 and identifying 1668 out of 3305 locations in the region as candidate sites. The RNN, better capturing unique regional characteristics, required separate training: 77.2% average accuracy on Region 1, identifying 1593 candidate sites. Our findings suggest expanding the use of land improves population access to healthcare facilities. Both models found more than the needed number of RHUs by 2040. The BPNN was more consistent than RNN to improve a region’s overall accessibility by increasing the HCFAI. The BPNN can increase population access to an RHU from 2.5-98.5% from its original population with access to an RHU.

The study demonstrates the usage of geographic attributes and neural networks to improve healthcare accessibility. The BPNN and RNN are adequate algorithms to find under-served areas and candidate sites for RHU construction to maximize population accessibility. The HCFAI metric validates the locations to highlight which neural network maximizes more of the region’s populat ion. The study contributes to ongoing efforts to improve healthcare infrastructure and accessibility, offering datadriven recommendations for RHU locations.

Introduction: Effective vaccination campaigns have been instrumental in reducing COVID-19 transmission and severe disease outcomes. Despite efforts to improve vaccine accessibility, vaccine literacy and confidence remain important determinants of vaccine uptake. Rural and geographically isolated communities often experience barriers to healthcare access that may affect vaccination coverage. This study aimed to assess COVID-19 vaccination coverage, vaccine literacy, and vaccine confidence among residents of selected Geographically Isolated and Disadvantaged Areas (GIDAs) in Floridablanca, Pampanga. Methods: A descriptive cross-sectional study was conducted among 211 residents of Barangays San Ramon and Nabuclod. Data were collected through face-to-face interviews using a translated and pretested questionnaire on vaccine literacy and vaccine confidence. Vaccination records obtained from the Rural Health Unit were reviewed to determine COVID-19 vaccination coverage. Descriptive statistics, including frequencies and percentages, were used to summarize the data. Results: The majority of respondents demonstrated an average level of vaccine literacy (75.8%), while 17.5% exhibited high vaccine literacy. Most respondents also demonstrated positive to very positive vaccine confidence (71.6%). Among the eligible population, 80.5% had completed the primary COVID-19 vaccination series, whereas 19.5% remained unvaccinated. Among those who completed the primary series, only 24.2% had received at least one booster dose. Conclusion Residents of the selected GIDAs generally demonstrated average vaccine literacy, positive vaccine confidence, and relatively high primary COVID-19 vaccination coverage. However, low booster uptake and the persistence of unvaccinated individuals highlight the need for sustained health education, improved healthcare accessibility, and targeted community-based interventions. These findings underscore the importance of strengthening vaccine literacy and confidence to support future immunization programs in geographically isolated communities.
COVID-19 ; Rural Health ; Vaccination coverage

BACKGROUND: Congenital heart disease (CHD) is a leading cause of birth defect-related mortality. However, more recent CHD mortality data for China are lacking. Additionally, limited studies have evaluated sex, rural-urban, and region-specific disparities of CHD mortality in China. METHODS: We designed a population-based study using data from the Dataset of National Mortality Surveillance in China between 2008 and 2021. We calculated age-adjusted CHD mortality using the sixth census data of China in 2010 as the standard population. We assessed the temporal trends in CHD mortality by age, sex, area, and region from 2008 to 2021 using the joinpoint regression model. RESULTS: From 2008 to 2021, 33,534 deaths were attributed to CHD. The period witnessed a two-fold decrease in the age-adjusted CHD mortality from 1.61 to 0.76 per 100,000 persons (average annual percent change [AAPC] = -5.90%). Females tended to have lower age-adjusted CHD mortality than males, but with a similar decline rate from 2008 to 2021 (females: AAPC = -6.15%; males: AAPC = -5.84%). Similar AAPC values were observed among people living in urban (AAPC = -6.64%) and rural (AAPC = -6.12%) areas. Eastern regions experienced a more pronounced decrease in the age-adjusted CHD mortality (AAPC = -7.86%) than central (AAPC = -5.83%) and western regions (AAPC = -3.71%) between 2008 and 2021. Approximately half of the deaths (46.19%) due to CHD occurred during infancy. The CHD mortality rates in 2021 were lower than those in 2008 for people aged 0-39 years, with the largest decrease observed among children aged 1-4 years (AAPC = -8.26%), followed by infants (AAPC = -7.01%). CONCLUSIONS CHD mortality in China has dramatically decreased from 2008 to 2021. The slower decrease in CHD mortality in the central and western regions than in the eastern regions suggested that public health policymakers should pay more attention to health resources and health education for central and western regions.
Humans ; Heart Defects, Congenital/mortality* ; Male ; Female ; China/epidemiology* ; Infant ; Child, Preschool ; Adult ; Child ; Adolescent ; Infant, Newborn ; Middle Aged ; Young Adult ; Aged ; Rural Population

BACKGROUND: The urban-rural disparities in overweight and obesity among children and adolescents are narrowing, and there is a need for long-term and updated data to explain this inequality, understand the underlying mechanisms, and identify priority groups for interventions. METHODS: We analyzed data from seven rounds of the Chinese National Survey on Students Constitution and Health (CNSSCH) conducted from 1985 to 2019, focusing on school-age children and adolescents aged 7-18 years. Joinpoint regression was used to identify inflection points (indicating a change in the trend) in the prevalence of overweight and obesity during the study period, stratified by urban/rural areas and sex. Annual percent change (APC), average annual percent change (AAPC), and 95% confidence interval (CI) were used to describe changes in the prevalence of overweight and obesity. Polynomial regression models were used to predict the prevalence of overweight and obesity among children and adolescents in 2025 and 2030, considering urban/rural areas, sex, and age groups. RESULTS: The prevalence of overweight and obesity in urban boys and girls showed an inflection point of 2000, with AAPC values of 10.09% (95% CI: 7.33-12.92%, t = 7.414, P <0.001) and 8.67% (95% CI: 6.10-11.30%, t = 6.809, P <0.001), respectively. The APC for urban boys decreased from 18.31% (95% CI: 4.72-33.67%, t = 5.926, P = 0.027) to 4.01% (95% CI: 1.33-6.75%, t = 6.486, P = 0.023), while the APC for urban girls decreased from 13.88% (95% CI: 1.82-27.38%, t = 4.994, P = 0.038) to 4.72% (95% CI: 1.43-8.12%, t = 6.215, P = 0.025). However, no inflection points were observed in the best-fit models for rural boys and girls during the period 1985-2019. The prevalence of overweight and obesity for both urban and rural boys is expected to converge at 35.76% by approximately 2027. A similar pattern is observed for urban and rural girls, with a prevalence of overweight and obesity reaching 20.86% in 2025. CONCLUSIONS The prevalence of overweight and obesity among Chinese children and adolescents has been steadily increasing from 1985 to 2019. A complete reversal in urban-rural prevalence is expected by 2027, with a higher prevalence of overweight and obesity in rural areas. Urgent action is needed to address health inequities and increase investments, particularly policies targeting rural children and adolescents.
Humans ; Child ; Adolescent ; Female ; Male ; Rural Population/statistics & numerical data* ; Overweight/epidemiology* ; Prevalence ; China/epidemiology* ; Pediatric Obesity/epidemiology* ; Obesity/epidemiology* ; Urban Population

BACKGROUND: Death burden of stroke is severe with over one-third rural residents in China, but there is still a lack of specific national and high-quality reports on the urban-rural differences in stroke burden, especially for subtypes. We aimed to update the understanding of urban-rural differences in stroke deaths. METHODS: This is a descriptive observational study. Data from the national mortality surveillance system, which covers 323.8 million with 605 disease surveillance points (DSPs) across all 31 provinces, municipalities, and autonomous regions in China. All deaths from stroke as the underlying cause from 2015 to 2020 according to DSPs. Crude mortality rate and age-standardized mortality rate (ASMR) were estimated through DSPs. Average annual percentage change was used to explain the change in mortality rate. RESULTS: From 2015 to 2020, the majority of deaths from all stroke subtypes occurred in rural areas. There were significant differences between the changes of urban and rural ASMRs. On the whole, the changes in urban areas were evidently better, and the ASMR differences were basically expanding. Stroke ASMR in urban China decreased by 15.5%. The rural ASMR of ischemic stroke increased by 12.9%. The rural and urban ASMRs of intracerebral hemorrhage decreased by 24.9% and 27.4%, and those of subarachnoid hemorrhage decreased by 29.5% and 40.4%, respectively. The highest ASMRs of all stroke subtypes and the increasing trend of ischemic stroke ASMR make rural males the focus of stroke management. CONCLUSIONS The death burden of stroke varies greatly between urban and rural China. Rural residents face unique challenges.
Humans ; China/epidemiology* ; Stroke/mortality* ; Rural Population/statistics & numerical data* ; Male ; Female ; Urban Population/statistics & numerical data* ; Middle Aged ; Aged ; Aged, 80 and over ; Adult

INTRODUCTION: Visual impairment and obesity remain the major public health issues among school-age students in rural areas of China. Obesity is an underlying risk of vision problems. This study aimed to assess the association between visual impairment and body mass index (BMI) among school-age students in rural northwest China. METHODS: This study included 39,385 students from the 4 th to 9 th grade in rural northwest China. From 2018 to 2020, students underwent an assessment of visual acuity (VA) and completed a questionnaire on family demographics, and height and weight measurements. Multiple logistic regression analyses were used to analyse the data. RESULTS: The association between visual impairment and BMI groups was significant in the study population ( P = 0.002) and in different groups (at the different educational, provincial and national levels) ( P < 0.001, separately). Multiple logistic regression analyses revealed a positive relationship between visual impairment and obesity in the study population, including those attending primary school, Han students and the residents of Ningxia autonomous region. CONCLUSION The association between visual impairment and obesity was significant among school-age students in rural northwest China. There should be implementation of policies to address the problem about visual impairment and obesity among school-age students in rural areas.
Humans ; China/epidemiology* ; Body Mass Index ; Male ; Female ; Rural Population ; Vision Disorders/complications* ; Child ; Adolescent ; Students ; Surveys and Questionnaires ; Logistic Models ; Obesity/complications* ; Visual Acuity ; Cross-Sectional Studies

OBJECTIVES: The prevalence of overweight and obesity among children and adolescents continues to rise, becoming one of the most serious global public health issues of the 21st century. Given the differing growth and development environments between urban and rural children, associated risk factors also vary. This study aims to explore the distribution characteristics and influencing factors of overweight and obesity among urban and rural primary and secondary school students in Hunan Province, providing scientific evidence for targeted interventions. METHODS: A stratified, randomized cluster sampling method was used to select participants. A total of 197 084 students from primary and secondary schools across 14 prefectures in Hunan Province underwent physical examinations and questionnaire surveys. Population and spatial distribution characteristics of overweight and obesity were analyzed. Spatial distribution maps and spatial autocorrelation analyses were conducted using ArcGIS. Multivariate Logistic regression was used to identify influencing factors for overweight and obesity. RESULTS: The overall overweight and obesity rates among students in Hunan Province were 14.7% and 10.9%, respectively. Both rates were higher in urban areas than in rural counties (16.0% vs 13.9% for overweight; 12.1% vs 10.2% for obesity). Among both urban and rural students, boys had higher rates of overweight and obesity than girls. Higher-grade students had a higher overweight rate but a lower obesity rate than lower-grade students. In urban areas, the overweight and obesity rates of Han Chinese primary and secondary school students are lower than those of ethnic minority students (both P<0.05). In rural areas, the obesity rate of Han primary and secondary school students is lower than that of ethnic students (P<0.05). Across cities and prefectures, urban overweight and obesity rates ranged from 14.7% to 18.7% and 8.4% to 20.6% respectively, while rural rates ranged from 10.9% to 17.2% and 6.6% to 13.7% respectively. Spatial autocorrelation analysis revealed high-value clusters of overweight/obesity in urban areas of Changde and Zhangjiajie, and in rural areas of Loudi, Huaihua, and Shaoyang. Multivariate Logistic regression showed that gender, school stage, ethnicity, frequency of fresh vegetable intake, and sleep duration were associated with overweight and/or obesity in both urban and rural students. In urban students, frequency of fried food and fresh fruit intake, breakfast habits, physical activity on weekdays and holidays, and screen time on computers were also significant. In rural students, TV viewing time and sedentary duration were additional relevant factors. CONCLUSIONS The situation of overweight and obesity among primary and secondary school students in Hunan Province remains concerning. Greater attention should be paid to regions with high-value clusters of overweight/obesity, and targeted interventions should be developed based on urban-rural differences in influencing factors.
Humans ; China/epidemiology* ; Adolescent ; Male ; Female ; Rural Population/statistics & numerical data* ; Child ; Overweight/epidemiology* ; Students/statistics & numerical data* ; Urban Population/statistics & numerical data* ; Risk Factors ; Prevalence ; Obesity/epidemiology* ; Surveys and Questionnaires ; Pediatric Obesity/epidemiology* ; Schools

OBJECTIVES: The detection rate of scoliosis among school-aged children has been rising annually, varying by region, and has become a major public health concern affecting both physical and mental health. Its onset is multifactorial, and early screening combined with targeted interventions can alter disease progression. This study aims to investigate the prevalence and influencing factors of scoliosis among primary and secondary school students in Hunan Province, providing scientific evidence for targeted prevention strategies. METHODS: A stratified, randomized cluster sampling method was used to select 281 401 students from 14 prefecture-level cities in Hunan Province for scoliosis screening, physical examination, and questionnaire survey. The chi-square test was used for group comparisons, and trend chi-square test analyzed differences in screening positive rate by age. A multilevel regression model was applied to identify influencing factors, and ArcGIS was used to visualize spatial distribution patterns of scoliosis. RESULTS: The overall screening positive rate for scoliosis among Hunan students was 1.61%. Urban areas had a significantly higher rate than rural counties (2.81% vs 0.98%; P<0.01). The rate was equal between boys and girls (1.61% each). Underweight students had a higher rate than those with normal weight, overweight, or obesity (P<0.01). Stratified by age, urban students aged 6-18 years consistently showed higher positive rates than rural peers (P<0.001). No significant gender differences were observed at most ages (all P>0.05), except at age 11, where the females had a higher rate (1.28% vs 1.02%; P=0.048). After age 11, underweight students exhibited significantly higher positive rates than those with normal or higher BMI(all P<0.05). Across all groups, urban/rural, male/female, underweight/normal/overweight/obese, the scoliosis rate increased with age. By region, the screening positive rate ranged from 0.38% to 3.36%, with the top three being Chenzhou (3.36%), Xiangtan (2.78%), and Hengyang (2.71%), while the lowest was Xiangxi Tujia and Miao Autonomous Prefecture (0.38%). Multilevel regression analysis revealed that age (OR=1.160, 95% CI 1.135 to 1.186) and urban residence (OR=2.497, 95% CI 1.946 to 3.205) were positively associated with scoliosis risk (both P<0.01). Conversely, female gender (OR=0.931, 95% CI 0.874 to 0.993), normal nutritional status (OR=0.751, 95% CI 0.671 to 0.840), overweight (OR=0.513, 95% CI 0.447 to 0.590), obesity (OR=0.418, 95% CI 0.358 to 0.489), and engaging in ≥ 60 minutes of moderate-to-vigorous physical activity 2 to 4 days (OR=0.928, 95% CI 0.865 to 0.996) or 5 to 7 days per week (OR=0.912, 95% CI 0.833 to 0.998) were negatively associated with scoliosis risk (all P<0.05). CONCLUSIONS The prevalence of scoliosis among primary and secondary school students in Hunan Province is relatively high and is significantly associated with age, gender, urban-rural status, nutritional condition, and physical activity frequency. Targeted interventions and enhanced monitoring in high-risk regions and populations are essential to prevent and control scoliosis.
Humans ; Scoliosis/epidemiology* ; Male ; Female ; Adolescent ; China/epidemiology* ; Prevalence ; Child ; Students/statistics & numerical data* ; Rural Population/statistics & numerical data* ; Urban Population/statistics & numerical data* ; Surveys and Questionnaires ; Risk Factors ; Thinness/epidemiology*

OBJECTIVES: Older adults in rural areas with multiple chronic conditions (MCC) generally exhibit poorer medication adherence than the general elderly population. Considering individual heterogeneity helps to design precise subgroup-based interventions. This study aims to identify latent profile types of medication adherence mechanisms among rural older adults with MCC based on the capability-opportunity-motivation-behavior (COM-B) model, and to explore factors influencing medication adherence. METHODS: A multistage sampling method was used to recruit 349 rural older adults with MCC from 10 administrative villages in Jianghua County, Yongzhou City, Hunan Province, between July and September, 2024. Participants were surveyed using a general information questionnaire, the Health Literacy Scale for Chronic Patients, the Beliefs about Medicines Questionnaire-Specific, the Multidimensional Scale of Perceived Social Support, and the Morisky Medication Adherence Scale. Latent profile analysis based on the COM-B model was conducted to identify subgroups of medication adherence mechanisms. Univariate and Logistic regression analyses were used to identify influencing factors associated with different latent profiles and adherence levels. RESULTS: Among the participants, 33.5% demonstrated good medication adherence. The 5 most prevalent chronic diseases were hypertension (86.5%), diabetes (36.7%), arthritis or rheumatism (34.4%), stroke (21.8%), and heart disease (17.5%). Overall, rural older adults with MCC exhibited relatively good medication capability, opportunity, and motivation. Their medication adherence mechanisms were classified into 3 latent profiles: "family-support restrained type" (5.2%), "family-support driven type" (52.1%), and "comprehensive advantage type" (42.7%). Significant differences were observed among the three profiles in terms of education level, marital status, living arrangement, and per capita monthly household income (all P<0.05). Multivariate Logistic regression revealed that higher education level was a protective factor for belonging to the "comprehensive advantage type" rather than the "family-support driven type" [OR=0.277, 95% CI (PL) 0.126 to 0.614, P=0.002]. Furthermore, significant differences in education level, self-rated health status, and latent profile type were found between participants with good and poor adherence (P<0.05). Binary Logistic regression indicated that with each one-level increase in self-rated health status, the risk of poor adherence increased by 293.9% [OR=3.939, 95% CI (PL) 1.610 to 9.636, P=0.003]. Compared with the "family-support restrained type", individuals classified as the "comprehensive advantage type" had a 96.8% [OR=0.032, 95% CI (PL) 0.008 to 0.123, P<0.001] lower risk of poor medication adherence. CONCLUSIONS The mechanisms underlying medication adherence among rural older adults with MCC show clear heterogeneity. Primary healthcare providers should focus on the "family-support restrained type" subgroup, strengthen social support networks, and implement targeted interventions to improve medication adherence.
Humans ; Aged ; Rural Population ; Male ; Female ; China ; Medication Adherence/psychology* ; Surveys and Questionnaires ; Chronic Disease/drug therapy* ; Multiple Chronic Conditions/drug therapy* ; Social Support ; Motivation ; Middle Aged ; Health Literacy ; Aged, 80 and over

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*