Journal of Global Health最新文献

Background: Studies on the relationship between personal history of irradiation and breast cancer have been reported for a long time. Still, epidemiological studies have not been conclusive, and the causal relationship is unclear. To address this issue, we employed Mendelian randomisation (MR) analysis to examine the association between individual radiation exposure history and breast cancer.

Methods: We used a series of quality control methods to select single nucleotide polymorphism (SNP) closely related to exposure. Meanwhile, several analysis methods were used to analyse the sample data to make the conclusion more reliable. To evaluate the horizontal pleiotropy, heterogeneity and stability of SNPs for breast cancer, the MR-Egger intercept test, Cochran's Q test and 'leave one' sensitivity analysis were used. Finally, the outlier variation determined by the Mendelian Randomisation Pleiotropy RESidual Sum and Outlier test is gradually eliminated to reduce the influence of heterogeneity and horizontal pleiotropy.

Results: After implementing rigorous quality control procedures, we carefully chose 102 qualified instrumental variables closely associated with the selected exposure for sensitivity analysis. This was conducted to evaluate the heterogeneity, level multiplicity, and stability of SNPs in the context of personal radiation history and its correlation with breast cancer. The results of the inverse variance weighted method analysis revealed a positive correlation between personal radiation and a heightened risk of breast cancer (odds ratio (OR) = 1.52; 95% confidence interval (CI) = 1.30-1.77). We also validated on another data set; the results were similar (OR = 1.51; 95% CI = 1.27-1.81). Furthermore, the findings from the sensitivity analysis were consistent. At the genetic level, our research demonstrated that personal radiation exposure is associated with an elevated risk of breast cancer.

Conclusions: Using genetic data provides evidence and strengthens the causal link that personal radiation causes breast cancer.

Background: Acute respiratory infection (ARI) poses a significant public health challenge worldwide, particularly among older adults. Understanding the cost of ARI management is important for optimising intervention strategy. We aimed to estimate the management cost of ARI in older adults in China.

Methods: We searched three English databases (MEDLINE, Embase, and Web of Science) and four Chinese databases (Chinese National Knowledge Infrastructure, Wanfang, SinoMed, and VIP) to identify studies published between 1 January 1995 and 27 February 2023 on the cost of ARI management in older adults in China. We pooled up age group and category-specific costs across individual studies by calculating median and interquartile range (IQR). All cost results were converted and inflated to USD in 2021.

Results: We included 99 studies, of which 50 were determined as high quality. In those aged >60 years, the median total cost of ARI, including direct medical, direct non-medical, and indirect cost, was USD 3263 (IQR = 2676-3786) in the inpatient setting and USD 104 (IQR = 80-129) in the outpatient setting. For both inpatient and outpatient settings, direct medical costs accounted for most of the costs (69.3% and 54.8%, respectively). There was an increasing trend over age in the median direct medical cost in the inpatient setting, ranging from USD 1517 (IQR = 1114-2017) in those aged ≥50 years to USD 3493 (IQR = 2608-4378) in those aged ≥80 years.

Conclusions: Our study fills the knowledge gap on the cost of ARI and suggests that the overall cost of ARI is substantial among older adults in China. Cost data stratified by region, pathogen, and presence of comorbidities are warranted to help further identify subpopulations with higher ARI management costs.

Registration: PROSPERO CRD42023485669.

Background: Globally, every year, 20 million neonates are born with weights below 2500 g and are considered low birth weight (LBW). About 90% of these births occur in low- and middle-income countries. Information regarding the geographical variation, socioeconomic inequalities of LBW neonates, and the relationship between maternal inadequate dietary diversity and LBW is limited in rural areas of Bangladesh. We aimed to explore the geographical disparities and socioeconomic inequalities in the prevalence of LBW and its association with inadequate maternal dietary diversity.

Methods: We extracted data from a large-scale evaluation programme conducted as a part of the maternal infant and young child nutrition phase two in Bangladesh, implemented by BRAC. We used the concentration index (CIX) to measure the socioeconomic inequalities of LBW. We performed a cluster-adjusted multiple logistic regression analysis to determine the association between LBW and maternal dietary diversity.

Results: A total of 4651 children aged <5 years with their mother's information were included. The overall prevalence of LBW was 13.5%. About 16% of mothers living in the poorest wealth quintile gave birth to LBW babies, whereas 10% of mothers living in the richest households gave birth to LBW babies. The CIX exhibited LBW babies were more prevalent among the socioeconomically worst-off (poorest) group (CIX = -0.08), indicating mothers of the poorest households are vulnerable to giving birth to normal-weight babies. An adjusted multiple logistic regression model indicated that mothers with inadequate dietary diversity had higher odds (adjusted odds ratio (AOR) = 1.27; 95% confidence interval (CI) = 1.04, 1.54) of giving birth to LBW babies. Notably, in the interaction of mothers' age and dietary diversity, we found that adolescent mothers (aged ≤ 19 years) with inadequate dietary diversity had 2.56 times (AOR = 2.56; 95% CI = 1.14, 5.76) higher odds of giving birth to LBW babies compared to adult mothers (aged >19 years) who consumed diversified foods.

Conclusions: Intervention strategies for reducing LBW prevalence should target the poorest households. Also, interventions for improving the dietary diversity of adolescent pregnant mothers are expected to reduce the number of LBW babies from the rural areas of Bangladesh.

Background: Incidence of early-onset cancers at multiple organ sites has increased worldwide in recent decades. We investigated whether such increasing trends could be explained by trends in obesity.

Methods: We obtained incidence data for 21 common cancers among 25-49-year-olds during 2000-2012 in 42 countries from the Cancer Incidence in Five Continents database. Nine cancers we examined have been classified as obesity-related by the International Agency for Research on Cancer. Estimates of overweight and obesity prevalence came from the Non-communicable Disease Risk Factor Collaboration. Using country-level data, we examined whether changes in the prevalence of overweight and obesity combined were correlated with changes in cancer incidence, after accounting for various time lags (0-15 years) between exposure and cancer diagnosis. To test the validity of our approach, we conducted negative control analyses (using non-obesity-related cancers as the outcome variable, and per-capita gross national income as the exposure variable), and sensitivity and supplemental analyses using alternative data streams or processing.

Results: We found increased incidence for six of nine obesity-related and seven of twelve non-obesity-related cancers in 25-49-year-olds. These increases were more predominant in Western countries (particularly Australia, the USA, Canada, Norway, the Netherlands, and Lithuania). For four obesity-related cancers displaying increased incidence (colon, rectum, pancreas, kidney), changes in cancer incidence were positively correlated with changes in overweight and obesity prevalence. When accounting for a 15-year lag, the estimated correlation was 0.27 (95% confidence interval (CI) = -0.04, 0.53; P = 0.090) for colon cancer, 0.33 (95% CI = 0.02, 0.58; P = 0.036) for rectal cancer, 0.39 (95% CI = 0.08, 0.64; P = 0.018) for pancreatic cancer, and 0.22 (95% CI = -0.10, 0.50; P = 0.173) for kidney cancer. Similar correlations were found in the sensitivity and supplemental analyses. We did not find similar correlations with excess body weight for the non-obesity-related early-onset cancers, nor correlations with per-capita gross national income for any cancer types, in the negative control analyses.

Conclusions: Worldwide increases in early-onset colon, rectal, pancreatic, and kidney cancers may have been partly driven by increases in excess body weight. The increases in other early-onset cancers, however, were likely driven by other factors deserving of further investigation.

Background: In this study, we aimed to explore the impact of exacerbation history on future exacerbation and mortality with different inhaled drugs in chronic obstructive pulmonary disease (COPD) patients based on a Global Initiative Chronic Obstructive Lung Disease (GOLD) A and B classifications.

Methods: This observational study was based on the cohort study Real World Research of Diagnosis and Treatment of COPD (RealDTC). We collected data from COPD patients in China from 1 July 2017 to 31 December 2022. Patients were followed up until December 2023 or death. Further, we separated GOLD A and B patients into GOLD A0 and B0, who had no exacerbation during the previous year, and GOLD A1 and B1, who had only one exacerbation during the previous year. Study outcomes included moderate-to-severe exacerbation, hospitalisation, frequent exacerbation in the first year and all-cause mortality during total follow-up.

Results: Of the 8318 eligible patients, GOLD E group of patients suffered from a greater risk of exacerbation in the first year and death than patients in the GOLD A and B groups. GOLD A1 group had a higher risk of moderate-to-severe exacerbation (hazard ratio (HR) = 2.087; 95% confidence interval (CI) = 1.419-3.068), hospitalisation (HR = 1.704; 95% CI = 1.010-2.705) and frequent exacerbation (HR = 1.983; 95% CI = 1.046-3.709) compared to GOLD A0. GOLD B1 group had a risk of moderate-to-severe exacerbation (HR = 1.321; 95% CI = 1.105-1.679) and mortality (HR = 1.362; 95% CI = 1.026-1.963) that exceeded the risk in GOLD B0 group. The treatment outcome of different inhaled drugs had no statistical differences in GOLD A0 group. In GOLD A1 group, only inhaled corticosteroids (ICS), in addition to long-acting β-2 agonist (LABA) and long-acting muscarinic antagonist (LAMA), reduced the risk of moderate-to-severe exacerbation in the first year compared to only LAMA. As for the GOLD B0 group, LABA and LAMA decreased the odds of moderate-to-severe exacerbation, hospitalisation, frequent exacerbation and mortality compared to only LAMA. ICS, LABA, and LAMA in GOLD B0 also down-regulated the risk of frequent exacerbation, compared to only LAMA. In addition, GOLD B1 patients treated with LABA and LAMA or ICS, LABA, and LAMA had a lower risk of moderate-to-severe exacerbation and hospitalisation. Meanwhile, ICS, LABA, and LAMA also reduced the risk of frequent exacerbation and mortality, compared to only LAMA in the multivariate Cox analysis.

Conclusions: Compared to the GOLD A or B group without exacerbation history, GOLD A patients with exacerbation history had a higher risk of future exacerbation, and GOLD B patients with exacerbation history had a higher risk of future exacerbation and mortality and benefited more from triple inhaler therapy.

Background: The rapid expansion of the cut flower industry in Africa has led to pervasive use and potential exposure of pesticides, raising concerns for local communities. Whether the risks associated with pesticide applications are localised or have broader implications remains unclear.

Methods: We measured biomarkers of real and perceived pesticide exposure in two Kenyan communities: Naivasha, where the cut flower industry is present, and Mogotio, where the cut flower industry is absent. We measured real exposure by the percentage of acetylcholinesterase (AChE) inhibition and perceived exposure by assessing hair cortisol levels, a biomarker of stress. Additionally, we conducted a demographic survey to evaluate the health and socioeconomic status of participants, as well as their perceptions of pesticide risks associated with the cut flower industry.

Results: Perceived pesticide exposure was more common in Naivasha (n = 36, 56%) compared to Mogotio (n = 0, 0%), according to community surveys. However, Mogotio residents had significantly higher mean hair cortisol levels (mean (x̄) = 790 ng/g, standard deviation (SD) = 233) and percentage of AChE inhibition (x̄ = 28.5%, SD = 7.3) compared to Naivasha residents, who had lower mean hair cortisol levels (x̄ = 548 ng/g, SD = 187) and percentage of AChE inhibition (x̄ = 14.5%, SD = 10.1). Location (proximity to cut flower farms) and gender were significant factors influencing pesticide exposure, with individuals living outside the cut flower industrial complexes being at higher risk. Women in both communities were the most vulnerable demographic, showing significantly higher mean hair cortisol levels (x̄ = 646 ng/g, SD = 267.4) and percentage of AChE inhibition (x̄ = 22.5%, SD = 12.4) compared to men hair cortisol levels (x̄ = 558.2 ng/g, SD = 208.2) and percentage of AChE inhibition (x̄ = 10.4%, SD = 13.1).

Conclusions: A heightened awareness of the potential risks of pesticide exposure was widespread within cut flower industrial complexes. This may have led to a reduction in exposure of both workers and non-workers living within or close to these complexes. In contrast, communities living outside these complexes showed higher levels of exposure, possibly due to limited chemical awareness and a lack of precautionary measures. Despite this contrast between communities, women remained the most vulnerable members, likely due to their socioeconomic roles in African society. Monitoring women's pesticide exposure is crucial for providing an early warning system for community exposure.

Background: Malaria remains one of the deadliest diseases worldwide, especially among young children in sub-Saharan Africa. Predictive models are necessary for effective planning and resource allocation; however, statistical models suffer from association pitfalls. In this study, we used empirical dynamic modelling (EDM) to investigate causal links between climatic factors and intervention coverage with malaria for short-term forecasting.

Methods: Based on data spanning the period from 2008 to 2022, we used convergent cross-mapping (CCM) to identify suitable lags for climatic drivers and investigate their effects, interaction strength, and suitability ranges on malaria incidence. Monthly malaria cases were collected at St. Elizabeth Lwak Mission Hospital. Intervention coverage and population movement data were obtained from household surveys in Asembo, western Kenya. Daytime land surface temperature (LSTD), rainfall, relative humidity (RH), wind speed, solar radiation, crop cover, and surface water coverage were extracted from remote sensing sources. Short-term forecasting of malaria incidence was performed using state-space reconstruction.

Results: We observed causal links between climatic drivers, bed net use, and malaria incidence. LSTD lagged over the previous month; rainfall and RH lagged over the previous two months; and wind speed in the current month had the highest predictive skills. Increases in LSTD, wind speed, and bed net use negatively affected incidence, while increases in rainfall and humidity had positive effects. Interaction strengths were more pronounced at temperature, rainfall, RH, wind speed, and bed net coverage ranges of 30-35°C, 30-120 mm, 67-80%, 0.5-0.7 m/s, and above 90%, respectively. Temperature and rainfall exceeding 35°C and 180 mm, respectively, had a greater negative effect. We also observed good short-term predictive performance using the multivariable forecasting model (Pearson correlation coefficient = 0.85, root mean square error = 0.15).

Conclusions: Our findings demonstrate the utility of CCM in establishing causal linkages between malaria incidence and both climatic and non-climatic drivers. By identifying these causal links and suitability ranges, we provide valuable information for modelling the impact of future climate scenarios.

Background: Although socioeconomic status (SES) is considered a risk factor for cardio-cerebrovascular diseases (CCVDs), few studies have examined this association. In this cross-sectional study, we aimed to assess the prevalence and trends of CCVDs across different SES groups over a 12-year period in a representative Korean population.

Methods: We analysed 47 745 economically active adults aged ≥30 and <65 years from 97 622 patients in the Korean National Health and Nutrition Examination Survey (2007-18), where a new independent sample of the population was examined each year. We categorised the participants into four groups based on education level and income. The prevalence of hypertension, diabetes mellitus, dyslipidaemia, and CCVD, including angina, myocardial infarction, and stroke, was analysed at four-year intervals.

Results: Average age, urban residence, white-collar occupation, and body mass index >30 increased, whereas CCVD prevalence did not change significantly (P = 0.410) over the study period. Low education (odds ratio (OR) = 1.24; 95% confidence interval (CI) = 1.04-1.47, P < 0.001) and low income (OR = 1.14; 95% CI = 1.02-1.28, P = 0.017) were significant determinants of CCVD in addition to existing traditional risk factors. CCVD prevalence was significantly higher in both the low-education and low-income groups compared to the high-education and high-income groups every four years, with no significant change in this gap over the study period (P = 0.239).

Conclusions: Despite the increase in the elderly population and the prevalence of obesity, the incidence of CCVDs in Korea has remained unchanged. Individuals with low education or low income had a significantly higher prevalence of CCVD, with the lowest SES group, defined by both low education and low income, consistently having the highest prevalence of CCVDs.

Background: Delayed diagnosis and treatment of vision-threatening diabetic retinopathy (VTDR) is a common cause of visual impairment in individuals with type 2 diabetes mellitus (T2DM). Identification of VTDR predictors is the key to early prevention and intervention, but the predictors from previous studies are inconsistent. This study aims to conduct a systematic review and meta-analysis of the existing evidence for VTDR predictors, then to develop a risk prediction model after quantitatively summarising the predictors across studies, and finally to validate the model with two Chinese cohorts.

Methods: We systematically retrieved cohort studies that reported predictors of VTDR in T2DM patients from PubMed, Ovid, Embase, Scopus, Cochrane Library, Web of Science, and ProQuest from their inception to December 2023. We extracted predictors reported in two or more studies and combined their corresponding relative risk (RRs) using meta-analysis to obtain pooled RRs. We only selected predictors with statistically significant pooled RRs to develop the prediction model. We also prospectively collected two Chinese cohorts of T2DM patients as the validation set and assessed the discrimination and calibration performance of the prediction model by the time-dependent ROC curve and calibration curve.

Results: Twenty-one cohort studies involving 622 490 patients with T2DM and 57 107 patients with VTDR were included in the meta-analysis. Age of diabetes onset, duration of diabetes, glycosylated haemoglobin (HbA1c), estimated glomerular filtration rate (eGFR), hypertension, high albuminuria and diabetic treatment were used to construct the prediction model. We validated the model externally in a prospective multicentre cohort of 555 patients with a median follow-up of 52 months (interquartile range = 39-77). The area under the curve (AUC) of the prediction model was all above 0.8 for 3- to 10-year follow-up periods and different cut-off value of each year provided the optimal balance between sensitivity and specificity. The data points of the calibration curves for each year closely surround the corresponding dashed line.

Conclusions: The risk prediction model of VTDR has high discrimination and calibration performance based on validation cohorts. Given its demonstrated effectiveness, there is significant potential to expand the utilisation of this model within clinical settings to enhance the detection and management of individuals at high risk of VTDR.

Background: Global population ageing has brought about new challenges for elderly care. Exploring intrinsic capacity (IC) over time, which is designed as a composite measure of an individual's physical and mental capabilities, is essential for promoting healthy ageing and preventing dependency, such as that emerging from disability in activities of daily living (ADL). We aimed to identify and examine the differences between classes of IC trajectory and onset of ADL disability.

Methods: We conducted an observational study using data from three waves (2011-15) of the China Health and Retirement Longitudinal Study, comprising 2609 participants with 6034 observations. IC was measured by five domains, including locomotion, cognition, psychological, sensory capacities, and vitality. We used joint latent class modelling to identify distinct classes with similar patterns of IC trajectory and onset of ADL disability, as well as to explore the variation in IC trajectory and predict five-year risks of ADL disability considering the heterogeneity in the elderly population.

Results: The average baseline IC score was 7.15 (range: 0-15). We observed that IC scores slowly decreased with age, with 17.25% of participants developing ADL disability. We identified three classes of IC, which could be described as moderate health (class 1: n = 1634, 62.63%), at-risk (class 2: n = 716, 27.44%; had the highest risk of ADL disability), and optimal health (class 3: n = 259, 9.93%; had the lowest baseline risk of ADL disability). The probability of being in the moderate health class was decreased the most by emotional problems (odds ratio (OR) = 0.219; P < 0.001). Having a self-rated poor standard of living substantially reduced the chances of moderate (OR = 0.308; P = 0.001) and optimal health (OR = 0.110; P < 0.001).

Conclusions: Observing IC trajectories and the onset of ADL disability can stratify the elderly into heterogeneous groups, as well as provide data for implementing person-centred care plans to reverse the trend and delay the adverse outcomes in clinical practice.