Agricultural Industry Research Articles

Nothing to hide: How governments justify the adoption of ag-gag laws.

Mainstream practices for producing meat, eggs, and dairy raise numerous concerns regarding public health, animal welfare, and environmental integrity. However, governments worldwide have expanded anti-whistleblower legislation that constrains informed public debate. Since 2019, several Canadian provinces have adopted so-called "ag-gag" laws designed to prevent hidden-camera investigations on farms and meat processing facilities. How do governments across Canada justify ag-gag laws as serving the public interest? To what extent do agricultural industry interests shape government adoption of ag-gag laws? Using Freedom of Information requests and debate records from provincial legislatures, we find that biosecurity is the most prominent justification for ag-gag laws, and that governments exhibit a close, collaborative relationship with industry actors. This case demonstrates that when it comes to contested sites of capital accumulation, governments are drawing on new spatial-legal tools to protect the status quo interests of private industry by dissuading dissent, debate, and public scrutiny.

Relationship between Oil Exports, Renewable Energy Consumption, Agriculture Industry, and Economic Growth in Selected OPEC Countries: A Panel ARDL Analysis

Relationship between Oil Exports, Renewable Energy Consumption, Agriculture Industry, and Economic Growth in Selected OPEC Countries: A Panel ARDL Analysis

Workplace mortality risk and social determinants among migrant workers: a systematic review and meta-analysis.

Migrant workers, a population of 170 million, often work in dangerous or unhealthy working environments and are likely to suffer workplace injuries and labour abuses. However, the risk of mortality in migrant workers compared with local workers is unknown. We aim to synthesise global evidence on migrant worker mortality risk and identify social determinants to inform health and safety protections for migrant workers. We conducted a systematic review and meta-analysis of peer-reviewed literature to examine mortality outcomes among migrant workers and associated risk factors. We searched MEDLINE, Embase, PsycINFO, and Ovid Global Health for studies published between Jan 1, 2000, and Jan 17, 2023, reporting quantitative primary research in English. A broad definition of migrant worker was used, including any worker who is foreign-born (ie, international first-generation migrant workers), either in paid employment or self-employment. Internal migrants, second-generation migrants, and foreign health-care workers were excluded. The primary outcome was any reported mortality, including all-cause mortality, cause-specific mortality, suicide, homicide, and fatal occupational injury. We used meta-analysis to compare outcomes between migrant worker and local worker populations, and a random-effects model to calculate pooled estimates. We used narrative synthesis to develop a data-driven conceptual framework capturing the intersectional social determinants of mortality in migrant workers. The study protocol is registered on PROSPERO, CRD42023372893. Of 11 495 identified records, 44 were included in the systematic review, of which 11 studies were pooled in meta-analyses. Data were from 16 countries, most of which were high-income countries, and included 44 338 migrant worker deaths, including migrants from the agriculture, construction, mining, and service industries. Compared with local workers, migrant workers had a higher risk of fatal occupational injury (pooled relative risk 1·71, 95% CI 1·22-2·38; eight studies; I2=99·4%), and a lower risk of all-cause mortality (0·94, 0·88-0·99; three studies, I2=90·7%). Migrant workers were more likely to die from external causes of death (such as falls or assaults) than internal causes of death (such as respiratory or digestive diseases) compared with local workers, with migrant workers also more likely to die from work-related homicides, especially in the retail and sex industries, with some evidence of higher suicide rates among female migrant workers compared with female local workers. Influential social determinants for poor fatality outcomes include migration-related factors (such as lower language proficiency, undocumented status, and long duration of stay) and labour-related factors (such as precarious employment, labour migration policies, and economic deregulation policies). Migrant workers have a higher risk of workplace fatal injury despite being generally healthier than local workers, which could be explained by structural determinants such as precarious employment and inadequate safety protection. This health inequity must be urgently addressed through future interventions that account for migration-related and labour-related social determinants of health at the structural level, such as extending labour protection laws to migrant workers, and improving occupational health and safety and workplace conditions for this vital and growing workforce. UK Medical Research Council and National Institute for Health and Care Research.

Coupling and coordination of food security and agricultural carbon emission efficiency: Changing trends, influencing factors, and different government priority scenarios

Seeking a balance between food security and carbon mitigation is key to achieving sustainable agricultural development. This study evaluates the coupling coordination degree (CCD) between the food security index (FSI) and agricultural carbon emission efficiency (ACEE) in China from 2010 to 2021 using the coupled coordination model. By adjusting the model coefficients, different government priority scenarios are simulated to explore their impact on CCD. The Geodetector method is employed to identify the influencing factors of CCD, investigate their interactions, and assess the differences in these factors across various government priority settings. The average CCD between FSI and ACEE exhibits a notable upward trend, rising from 0.4583 in 2010 to 0.6595 in 2021. Furthermore, regional disparities are widening, particularly in the major production areas. Catch-up effects exist within regions. Policy simulations showed staged interactions between food security and agricultural carbon efficiency, shifting from food security to balanced production and ecology, then to prioritizing low-carbon production for food security. Adjusting policy priorities can effectively improve coupling coordination in the short term, with increasing impact as priority shifts. CCD is influenced by policy, technology, economy, and society, varying with policy priorities. In the baseline scenario, key factors for CCD include the urban-rural income gap, technological advancement, urbanization, and farmers' education level. When the government prioritizes food security, the impact of narrowing income gaps and agricultural industry agglomeration becomes more pronounced. Conversely, emphasizing carbon emission efficiency enhances the influence of technological advancements and urbanization on CCD. Tailoring agricultural production strategies to local conditions and emphasizing interactive effects among factors is crucial for achieving environmentally friendly and high-quality agricultural development goals.

Genomic Variants Associated with Haematological Parameters and T Lymphocyte Subpopulations in a Large White and Min Pig Intercross Population

The breeding of disease-resistant pigs has consistently been a topic of significant interest and concern within the pig farming industry. The study of pig blood indicators has the potential to confer economic benefits upon the pig farming industry, whilst simultaneously providing valuable insights that can inform the study of human diseases. In this study, an F2 resource population of 489 individuals was generated through the intercrossing of Large White boars and Min pig sows. A total of 17 haematological parameters and T lymphocyte subpopulations were measured, including white blood cell count (WBC), lymphocyte count (LYM), lymphocyte count percentage (LYM%), monocyte count (MID), monocyte count percentage (MID%), neutrophilic granulocyte count (GRN), percentage of neutrophils (GRN%), mean platelet volume (MPV), platelet distribution width (PDW), platelet count (PLT), CD4+/CD8+, CD4+CD8+CD3+, CD4+CD8−CD3+, CD4−CD8+CD3+, CD4−CD8−CD3+, and CD3+. The Illumina PorcineSNP60 Genotyping BeadChip was obtained for all of the F2 animals. Subsequently, a genome-wide association study (GWAS) was conducted using the TASSEL 5.0 software to identify associated variants and candidate genes for the 17 traits. Significant association signals were identified for PCT and PLT on SSC7, with 1 and 11 significant SNP loci, respectively. A single nucleotide polymorphism (SNP) on SSC12 was identified as a significant predictor of the white blood cell (WBC) trait. Significant association signals were detected for the T lymphocyte subpopulations, namely CD4+/CD8+, CD4+CD8+CD3+, CD4+CD8−CD3+, and CD4−CD8+CD3+, with the majority of these signals observed on SSC7. The genes CLIC5, TRIM15, and SLC17A4 were identified as potential candidates for influencing CD4+/CD8+ and CD4−CD8+CD3+. A missense variant, c.2707 G>A, in the SLC17A4 gene has been demonstrated to be significantly associated with the CD4+/CD8+ and CD4-CD8+CD3+ traits. Three missense variants (c.425 A>C, c.500 C>T, and c.733 A>G) have been identified in the TRIM15 gene as being linked to the CD4+/CD8+ trait. Nevertheless, only c.425 A>C has been demonstrated to be significantly associated with CD4-CD8+CD3+. In the CLIC5 gene, one missense variant (c.957 T>C) has been identified as being associated with the CD4+/CD8+ and CD4-CD8+CD3+ traits. Additionally, significant association signals were observed for CD4+CD8+CD3+ and CD4+CD8−CD3+ on SSC2 and 5, respectively. Subsequently, a gene ontology (GO) enrichment analysis was conducted on all genes within the quantitative trait loci (QTL) intervals of platelet count, CD4+/CD8+, and CD4−CD8+CD3+. The MHC class II protein complex binding pathway was identified as the most significant pathway among the three immune traits. These results provide guidance for further research in the field of breeding disease-resistant pigs.

Considerations for the use of laboratory-based and field-based estimates of environmental tolerance in water management decisions for an endangered salmonid

Water infrastructure development and operation can provide for human economic activity, health, and safety. However, this infrastructure can also impact native fish populations resulting in regulatory protections that can, in turn, alter operations. Conflict over water allocation for ecological function and human use has come to the forefront at Shasta Reservoir, the largest water storage facility in California, USA. Shasta Reservoir supports irrigation for a multibillion-dollar agricultural industry, provides water for urban and domestic use, provides flood protection for downstream communities, and power generation as part of the larger Central Valley Project in California. Additionally, an endangered run of Chinook Salmon relies on cold water management at the dam for successful spawning and egg incubation. Tradeoffs between these uses can be explored through application of models that assess biological outcomes associated with flow and temperature management scenarios. However, the utility of models for predicting outcomes of management decisions is contingent on the data used to construct them, and data collected to evaluate their predictions. We evaluated laboratory and field data currently available to parameterize temperature-egg survival models for winter run Chinook Salmon that are used to inform Shasta Dam operations. Models based on both laboratory and field data types had poor predictive performance which appears to limit their value for management decisions. The sources of uncertainty that led to poor performance were different for each data type (field or laboratory) but were rooted in the fact that neither data set was collected with the intention to be used in a predictive model. Our findings suggest that if a predictive model is desired to evaluate operational tradeoffs, data should be collected for the specific variables and life stages desired, over an appropriate range of values, and at sufficient frequency to achieve the needed level of precision to address the modeling objective.

Involving Rural Youth in Agroecological Nature-Positive Farming and Culinary Agri-Ecotourism for Sustainable Development: The Indian Scenario

Industrial food systems produce most of the food that we consume globally today. But many observers acknowledge that industrial agriculture cannot be sustained in the long run. As such, agroecological practices that encourage sustainable farming practices with a focus on local markets and the local economy are being promoted more and more to change the way food systems work. The current research examines how rural youth can best be involved in food system transformation as a potential agent of change. The research considers the potential of payments for environmental services (PESs) in the study area. The economic potential of gastronomic agri-ecotourism in various traditional agricultural landscapes of different agroecosystems of India has also been investigated. Gastronomic agri-ecotourism has the potential to provide economic benefits to traditional agricultural landscapes and agroecosystems while also promoting sustainable tourism practices. The results of an exploratory study on rural youth participation in nature-friendly agroecological regenerative farming and culinary agri-ecotourism initiatives are presented in this paper in an effort to increase the sustainability of conventional farming and food systems. This study, which was carried out in four different agroecological settings in India, sheds light on the opportunities and problems faced by rural youth, as well as their motivations.

Intelligent inspection and quality control of table olives

Quality is a key factor of product-marketing in the field of agriculture and food industry. A number of researches have suggested the use of vision computer systems and machine learning (ML) techniques essentially to inspect imperfection surfaces and defects in fruit products. Following the trend, this paper still relies on the use of vision computer system by assuring an intelligent detection of table olive defect, with a certainty of its quality control. The specifically exploited computer vision system consists of automatically extracting the texture, colour, and shape features mainly from the global thresholding segmented image. With reference to the extracted features, the newly introduced system has the capacities of distinguishing between the defected and the healthy olive fruits rapidly and effectively at the same time. Subsequently, it is capable of identifying and specifying the diseased table olive. This system is also helpful for estimating the table olive size automatically. The experimental findings are indicative of the high accuracy of the binary classification algorithm, reaching 99, 32%, the average processing time for just one olive is about 0.4 s, which could meet the requirements of the real-time applications, and the error in estimating the size of the table olives does not exceed 10%.

A novel antibody treatment reduces deformed wing virus loads in the western honey bee (Apis mellifera).

Deformed wing virus (DWV) is considered to be a key component of declining honey bee health which threatens global food production. The virus can result in significantly shortened lifespan, deformities in developing bees, and impaired cognition. There is currently no method to directly control the virus. The virus can be indirectly controlled with acaricidal treatments that target a key vector, the parasitic varroa mite (Varroa destructor). But acaricide resistance and a lack of effective alternatives for the control of both Varroa and DWV are major threats to beekeeping and the wider agricultural industry. Our research presents a significant development in the ability to reduce DWV burden in honey bees using IgY antibodies. Moreover, immunoglobulin Y has the potential to be more broadly established as a new treatment modality to combat other pathogens and parasites in A. mellifera.

Monitoring monthly mortality of maricultured Atlantic salmon (Salmo salar L.) in Scotland II. A hierarchical dynamic linear model

The sustainability of the salmon farming industry is being challenged by increased mortality rates. Scotland’s open-source salmon production data provides the possibility of developing an industry-wide mortality monitoring model, valuable for identifying and addressing unexpected increases in mortality without needing data sharing agreements across different companies. This study aimed to utilize these data to develop a hierarchical dynamic linear model (DLM) for monitoring monthly mortality of maricultured Atlantic salmon in Scotland. We evaluated whether considering the hierarchical structure present in the data (country, region, and site) would improve mortality predictions when compared to the production cycle level DLMs developed in a previous study. Our findings demonstrated that the hierarchical DLM outperformed the production cycle level DLMs, confirming the value of this more complex modelling approach. Nevertheless, the hierarchical model, like the production cycle level DLMs, exhibited some uncertainty in the mortality predictions. When mortality is higher than expected, site level warnings are generated, which can encourage producers and inspectors to further investigate the cause. Between 2015 and 2020, approximately 25% of the production cycles and 50% of the sites encountered at least one warning, with most warnings happening in the summer and autumn months. Additionally, the hierarchical model enabled monitoring mortality at multiple levels. This information is useful for various stakeholders as part of a monitoring system, offering insights into mortality trends at national, regional, and sites levels that may benefit from strategic resource management. Recommendations for model improvements include utilizing shorter data aggregation periods, such as weekly, which are not currently available as open-source data.

The low-carbon development path of China’s animal husbandry industry

To address global warming, China has committed to achieving carbon neutrality by 2060. As a major source of carbon emissions in China, it is necessary to implement carbon reduction measures in animal husbandry. This paper mainly explores the mainstream low-carbon development measures for animal husbandry from three aspects: production, processing, and transportation. At the same time, suggestions have been put forward for the green and low-carbon development of animal husbandry in the future, which can provide reference for research on low-carbon development of animal husbandry.

Smart Irrigation System using IOT

The majority of nations rely heavily on agriculture to power their economies. A nation's growth is mostly dependent on agriculture, notably for people's livelihood and the production of food and other raw resources. The rise of agriculture is the main driver of a nation's economy. One type of irrigation system that is frequently utilized in the agricultural industry is the smart irrigation system. In areas of farming where water is scarce, irrigation is used. This intelligent irrigation system is designed with farmers in mind. In this paper, the proposed smart irrigation system uses NodeMCU ESP8266. This system reads the values using sensors and waters the plants based on those values. Also, the system will send notification as well as email to the owner for a certain interval of time depending on the owner specification. The owner can also remotely monitor values by using the mobile application or web application. It is very easy to implement, and will save manpower, leading to a cost-effective solution for efficient water management in agriculture. This system harnesses the power of a microcontroller to monitor and control irrigation process, ensuring optimal water usage.

Integrating Machine Learning for Enhanced Agricultural Productivity: A Focus on Bananas and Arecanut in the Context of India’s Economic Growth

AbstractAgriculture is one of the sectors that has an important impact, taking into account the problem of sufficient food supply on a global level. The process of predicting the yield of crops is among the most challenging undertakings in the agricultural industry. Agriculture is the main source of income for most developing nations. The purpose of the study is to investigate the significant role that agriculture plays in boosting India's economic growth. Additionally, the research considers the challenges posed by a growing population and a changing environment in terms of agricultural production and food security. The research focuses on analysing the complex characteristics of the agricultural industry, with a particular emphasis on the nutritional importance of tropical fruits, notably bananas and arecanut. These fruits are well-known for their vital nutrients and their role in ensuring world food security. This study acknowledges the importance of sustainable agriculture practices and incorporates sophisticated machine learning algorithms as dynamic tools to forecast crop yields and enhance decision-making processes throughout the crop development cycle. The main aim of this study is to create strong machine learning models and statistical techniques that can accurately predict crop yield by combining a variety of environmental parameters, then assess which models outperform each other. Assist yield projections may provide governments and policymakers with valuable information to make well-informed choices about food security, import–export policies, and resource allocation. It facilitates national- and regional-level food supply planning. The validation method utilises important metrics like R square (R2), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). This present research adds to the continuing discussion on using creative methods to promote sustainable agricultural growth and ensure food security.

Modelling and Simulation of the Single-Period Vehicle Routing Problem in the Agriculture Industry

Modelling and Simulation of the Single-Period Vehicle Routing Problem in the Agriculture Industry

Are migrant workers at greater risk of workplace deaths? A systematic review and meta-analysis

Abstract Background Globally, 170 million individuals migrate for work. Yet, evidence on their mortality risk remains unclear. Our aim was to synthesize global evidence on migrant worker mortality risk compared to local workers and to identify the multiple intersecting social determinants of mortality. Methods We conducted a systematic review of peer-reviewed literature which reported on mortality outcome of migrant workers. Studies published between 1 Jan 2000 to 17 Jan 2023 in English were searched in MEDLINE, Embase, PsycINFO, and Ovid Global Health. Meta-analysis using random effects model was used to calculate pooled estimates and narrative synthesis was used to develop a data-driven framework on intersectional social determinants. Results Out of 11,495 identified records, 44 were included, of which 11 were pooled in meta-analyses. The combined migrant worker death count was 44,338, with data from 16 countries, including migrants from agriculture, construction, and service industries. Compared to local workers, migrant workers had a higher risk of fatal occupational injury (pooled RR = 1.71, 95%CI: 1.22-2.38, I² = 99.4%), and a lower risk of all-cause mortality (pooled RR = 0.94, 95%CI: 0.88-0.99, I² = 90.7%). Key social determinants associated with increased mortality risk were either migration-related (e.g. lower language proficiency, undocumented status) or labour-related (e.g. precarious employment, labour migration policies) interacting over migrant workers’ life course. Conclusions As the largest evidence synthesis to date, these findings indicate that migrant workers have higher fatal occupational injury rates than local workers, indicating the need for tailored protections for migrant workers. These data confirm that the all-cause mortality advantage observed in migrant populations applies to the working population. Future interventions should be designed to address both migration- and labour-related determinants of migrant worker health. Key messages • Migrant workers have a higher risk of workplace fatality despite being generally healthier than local workers, explained by structural determinants such as precarious employment. • Future interventions must address migration- and labour-related social determinants of health at structural levels, such as extending labour protection laws to migrant workers.

Design and Experimental Optimization of an Automated Longline-Suspended Oyster Spat Insertion Device

To address the challenges of labor-intensive and costly manual oyster spat insertion in longline-suspended farming, an automated oyster spat insertion device was designed based on negative pressure suction and bundling fixation technologies. Using this device as the experimental platform, a three-factor, three-level Box–Behnken experiment was conducted, with fixation mechanism inclination, negative pressure suction cup span, and horizontal distance between turnover and fixation mechanisms as the experimental factors. The performance of the device was evaluated using the effective fixation rate and damage rate as the experimental indicators. The quadratic polynomial regression models were established to assess the impact of these factors on operational performance, while the response surface method was employed to analyze the interaction effects between factors. Parameter optimization and experimental validation were also performed. The results indicate that the factors affecting the effective fixation rate, in order of significance, are as follows: fixation mechanism inclination, horizontal distance between turnover and fixation mechanisms, and negative pressure suction cup span. For the damage rate, the order of significance is as follows: fixation mechanism inclination > negative pressure suction cup span < horizontal distance between turnover and fixation mechanisms. The optimization results show that when the fixation mechanism inclination is set at 43°, the negative pressure suction cup span at 27 mm, and the horizontal distance between turnover and fixation mechanisms at 179 mm, the effective fixation rate reaches 92.08%, and the damage rate is 4.71%. The relative errors between the measured and model-predicted values are less than 5%, indicating that the regression models are reliable. This research provides valuable insights for advancing the mechanization of the oyster farming industry and replacing manual labor with mechanized equipment.

Three-Stage Solid-State Fermentation Technology for Distillers’ Grain Feed Protein Based on Different Microorganisms Considering Oxygen Requirements

The shortage of feed protein has plagued the development of the animal husbandry industry in China. In this study, a new three-stage fermentation technology for producing distillers’ grain feed protein was developed by introducing Aspergillus niger, yeast, and lactic acid bacteria. During the aerobic stage, there was a negative correlation between the reducing sugar content in the distillers’ grains and the amount of Aspergillus niger. The maximum reducing sugar concentration (36.89 mg g−1) was obtained when the oxygen supply was 30 mL min−1 and the fermentation time was two days. During the microaerophilic stage, the natural exchange of oxygen achieved optimal true protein enhancement (from 10.8% to 16.4%) among the three oxygen supply modes (natural exchange, forced ventilation, and filling supplement). During the anaerobic stage, lactic acid bacteria were inoculated for feed protein preservation and flavor enhancement. Our results provided insight and practical guidance for the high-value use of distillers’ grains.

School-Based Agricultural Education Teachers’ Interest in and Confidence for Preparing Students to Compete in Career Development Events

School-based agricultural education (SBAE) teachers have an obligation to teach students about agriculture and prepare them for agricultural careers. Yet, considering the vast number of sectors within the agricultural industry, this task can be daunting. One way teachers can accomplish this mission is through preparing their students to participate in Career Development Events (CDEs). This study assessed SBAE teachers’ level of self-efficacy for each of the 33 CDEs recognized and offered at the [State] State FFA Interscholastic Event. The SBAE teachers surveyed in the study expressed a greater interest in preparing their students in 32 of the 33 CDEs than they did their confidence to prepare them. Such perceptions may lead to a reluctance to prepare students for CDEs, especially in areas where teachers feel less efficacious, which could cause students to have less awareness of, appreciation for, and preparation in various agricultural careers. The findings of the study have implications for the professional development needs of inservice SBAE teachers. Such professional development should be provided to develop SBAE teachers’ perceived inadequacies by targeting the CDEs with the greatest mean difference scores. Specific focus should be placed on food science and technology, veterinary science, and meat evaluation and technology CDEs. SBAE teachers should be provided opportunities to develop mastery in these areas by pairing teachers with expert mentors across the state to allow for vicarious experiences to evolve and complement their perceived shortcomings. Additional research should ensue to determine the impact CDEs have on students’ future career choices and employability.

A preliminary study on the degradation of AFB1 by Tenebrio molitor, Rhizopus oryzae and Trichoderma reesei

Abstract Recently, genus Aspergillus, a fungus capable of producing aflatoxins, secondary highly toxic metabolites, has spread to new areas. These areas became suitable habitats due to the recent climate changes. The use of aflatoxin-contaminated crops is a cause of great concern in guaranteeing food safety and is responsible for major economic losses along the supply chain. For this reason, several strategies have been investigated to utilize these contaminated products as a possible food or feed resource by reducing or eliminating their aflatoxin content, but with limited relevant success. The presented study was aimed to evaluate a combination of biological processes to use aflatoxin B1 contaminated crops for their reintroduction into the production chain. The high tolerance to AFB1 and the apparent lack of accumulation in yellow mealworm larvae, reared on wheat bran substrates, spiked with increasing AFB1 concentration (0, 125, 250, 500 μg/kg) to obtain proteins of high biological value. Subsequently, the aflatoxin-degrading capacity of Rhizopus oryzae and Trichoderma reesei was applied to insect breeding waste (frass) in a fermentation process to ensure further utilization of biohazardous frass as soil conditioner. Individually, each process proven to be able to reduce the AFB1 present by about 80%, while the combination of the two approaches ensured the total degradation of aflatoxin B1-contaminated substrate and frass, which resulted in the possible production of biomass, that could be used for the feed and agricultural industry.

Factors Related to mHealth App Use Among Japanese Workers: Cross-Sectional Survey.

Health care providers can make health guidance more effective by using mobile health technologies such as health apps. Although health care providers need to know who uses health apps, existing studies have yielded inconsistent results. The aim of the study was (1) to clarify the prevalence and patterns of health app use to improve health behaviors for preventing lifestyle-related diseases among Japanese workers and (2) to identify the associations among demographic characteristics, health behavior, and internet use and health app use by gender. Data were collected from a cross-sectional internet survey in 2023. In total, 2200 participants were included, with an even distribution of men and women in each age group aged 20 to 60 years. The participants were workers with smartphones and reported their gender, age, residence area, marital status, education, employment status, occupation, work pattern, diseases under treatment, health checkups, health guidance, health behaviors, internet use duration, and number of devices used. We asked about current and previous health app use for 1 month. A multivariate logistic regression analysis was conducted by gender. Of the participants, 472 (21.5%) and 189 (8.6%) were current and previous health app users, respectively. Most current and previous health app users used features that record and track their physical activity and other health behaviors. Health app users-both men and women-were more likely to have health checkups (odds ratio [OR] 1.53, 95% CI 1.12-2.11 and OR 1.51, 95% CI 1.10-2.07, respectively), receive health guidance (OR 2.01, 95% CI 1.47-2.74 and OR 1.86, 95% CI 1.32-2.62, respectively), engage in regular physical activity (OR 2.57, 95% CI 1.91-3.47 and OR 1.94, 95% CI 1.41-2.67, respectively), use the internet for 120-179 minutes per day (OR 1.76, 95% CI 1.13-2.75 and OR 1.70, 95% CI 1.12-2.57, respectively), and were less likely to be older (50-59 years: OR 0.54, 95% CI 0.33-0.88 and OR 0.40, 95% CI 0.25-0.6, respectively, and 60-69 years: OR 0.37, 95% CI 0.22-0.62 and OR 0.47, 95% CI 0.28-0.77, respectively). According to gender, male health app users were more likely to be married (OR 1.69, 95% CI 1.23-2.33) and less likely to work in the security, agriculture, forestry, fishing, manufacturing, or transportation industries (OR 0.62, 95% CI 0.41-0.95). Female health app users were more likely to have a university education or higher (OR 1.55, 95% CI 1.061-2.26), maintain an appropriate body weight (OR 1.52, 95% CI 1.10-2.11), and use 3 or more devices (OR 2.13, 95% CI 1.41-3.23). Physical activity and health guidance are strong predictors of app use. Health care providers should assess the target populations' preferences for app use based on their characteristics, support their app use, and enhance the effectiveness of health guidance.