Coffee consumption in the United States amounted to over 26.3 million 60-kilogram bags in the 2022/2023 fiscal year. This is a slight decrease from the total U.S. coffee consumption in the previous fiscal year.

Coffee production The coffee plant has its origins in Ethiopia and is now grown all over the world. Most of the world’s coffee is cultivated in South America, followed by Asia and Oceania. In 2021, over 77 million 60-kilogram bags of coffee were produced in South America. The majority of South America’s coffee production is attributed to Brazil. In the 2020/2021 fiscal year, global coffee production reached 175 million 60-kilogram bags.

Coffee brewing in the United States Americans love their coffee and have dozens of different methods and gadgets for brewing and preparing coffee. A 2020 survey of U.S. consumers found that the most commonly used coffee preparation methods were drip coffee makers and single cup brewers. However, drip coffee makers have become less popular over time. In 2010, 77 percent of coffee drinkers used drip coffee makers, while in 2020 this share had dropped to 41 percent.

Coffee is one of the most widely consumed beverages in the world. In 2021/2022, nearly 176 million 60 kilogram bags of coffee were consumed worldwide, a slight increase from almost 167 million bags in the previous year.

Coffee Brewing Innovations The coffee industry is regularly coming up with innovative new methods for brewing coffee and serving it. Single cup brewers are a relatively new innovation which offer a quick and mess-free coffee brewing method for when one only wants a single cup of coffee without the hassle of brewing an entire pot. Keurig Green Mountain is the leading vendor of single-cup coffee in the United States.

Cold Brew Coffee Cold brew coffee is made by leaving coffee to brew in cold or room temperature water for 12 to 24 hours and results in a mellower, less acidic tasting coffee. It has become a popular menu item at coffee shops and cafes, but it also easy to make at home. The market for cold brew coffee was valued at 321 million U.S. dollars in 2017, and is expected to reach a staggering 1.37 billion U.S. dollars in market value by 2023.

In 2024, approximately 300,000 of 60 kilogram bags of coffee were consumed in Malaysia. This was a decrease from around 400,000 of 60 kilogram bags consumed in the previous year. Overall, coffee consumption has been declining over the years. Coffee drinking culture For most Malaysians, drinking warm beverages such as tea and coffee has been a part of their daily lives for decades. However, as of October 2019, Milo, a combination of chocolate and malt powder normally mixed with milk or hot water to make a drink, was recorded as the most popular brand in coffee and tea brand category on YouTube. This signified that coffee was less preferred by Malaysians. Traditionally, coffee was enjoyed by older Malaysians in the local "kopitiam", which is a local coffee shop. However, Malaysians who had lived abroad and adopted coffee drinking culture started to popularize café culture. Furthermore, the expansion of international retail café businesses such as Starbucks and The Coffee Bean & The Tea Leaf, as well as local coffee shop brands such as OldTown White Coffee also contributed to its popularity among the younger generation. Coffee production The main coffee bean types that are grown in Malaysia are robusta and liberica. In 2024, Malaysia recorded robusta coffee production of 1.5 million 60 kg bags. To keep up with the demand from both domestic and global market, Malaysia imports coffee from its neighboring country, Indonesia.

ObjectiveWe aimed to investigate the association between coffee consumption and frailty in older American adults. We focused on individuals at higher frailty risk, such as women, ethnic minorities, smokers, and those with obesity and insufficient physical activity.MethodsThe data of 8,087 individuals aged over 60 years from the 2007–2018 National Health and Nutrition Examination Surveys were used for this cross-sectional study. The coffee drinks were classified into two categories: caffeinated and decaffeinated. Frailty was measured using the 53-item frailty index. Weighted binary logistic regression was used to evaluate the association between coffee intake and frailty risk. Restricted cubic spline models were used to assess the dose–response relationship between caffeinated coffee intake and frailty.ResultsAmong the 8,087 participants, 2,458 (30.4%) had frailty. Compared with those who reported no coffee consumption, the odds ratios [ORs; 95% confidence intervals (CIs)] of total coffee consumption > 498.9 (g/day) were 0.65 (0.52, 0.79) in the fully adjusted model. Compared with those who reported no caffeinated coffee consumption, the ORs (95% CIs) of total coffee consumption > 488.4 (g/day) were 0.68 (0.54, 0.85) in the fully adjusted model. Compared with those who reported no decaffeinated coffee consumption, the ORs (95% CIs) of total coffee consumption > 0 (g/day) were 0.87 (0.71, 1.06) in the fully adjusted model. Nonlinear associations were detected between total coffee and caffeinated coffee consumption and frailty. In the subgroup analyses by smoking status, the association between coffee consumption and the risk of frailty was more pronounced in non-smokers (P for interaction = 0.031).ConclusionCaffeinated coffee consumption was independently and nonlinearly associated with frailty, especially in non-smokers. However, decaffeinated coffee consumption was not associated with frailty.

The dataset, Survey-SR, provides the nutrient data for assessing dietary intakes from the national survey What We Eat In America, National Health and Nutrition Examination Survey (WWEIA, NHANES). Historically, USDA databases have been used for national nutrition monitoring (1). Currently, the Food and Nutrient Database for Dietary Studies (FNDDS) (2), is used by Food Surveys Research Group, ARS, to process dietary intake data from WWEIA, NHANES. Nutrient values for FNDDS are based on Survey-SR. Survey-SR was referred to as the "Primary Data Set" in older publications. Early versions of the dataset were composed mainly of commodity-type items such as wheat flour, sugar, milk, etc. However, with increased consumption of commercial processed and restaurant foods and changes in how national nutrition monitoring data are used (1), many commercial processed and restaurant items have been added to Survey-SR. The current version, Survey-SR 2013-2014, is mainly based on the USDA National Nutrient Database for Standard Reference (SR) 28 (2) and contains sixty-six nutrientseach for 3,404 foods. These nutrient data will be used for assessing intake data from WWEIA, NHANES 2013-2014. Nutrient profiles were added for 265 new foods and updated for about 500 foods from the version used for the previous survey (WWEIA, NHANES 2011-12). New foods added include mainly commercially processed foods such as several gluten-free products, milk substitutes, sauces and condiments such as sriracha, pesto and wasabi, Greek yogurt, breakfast cereals, low-sodium meat products, whole grain pastas and baked products, and several beverages including bottled tea and coffee, coconut water, malt beverages, hard cider, fruit-flavored drinks, fortified fruit juices and fruit and/or vegetable smoothies. Several school lunch pizzas and chicken products, fast-food sandwiches, and new beef cuts were also added, as they are now reported more frequently by survey respondents. Nutrient profiles were updated for several commonly consumed foods such as cheddar, mozzarella and American cheese, ground beef, butter, and catsup. The changes in nutrient values may be due to reformulations in products, changes in the market shares of brands, or more accurate data. Examples of more accurate data include analytical data, market share data, and data from a nationally representative sample. Resources in this dataset:Resource Title: USDA National Nutrient Database for Standard Reference Dataset for What We Eat In America, NHANES 2013-14 (Survey SR 2013-14). File Name: SurveySR_2013_14 (1).zipResource Description: Access database downloaded on November 16, 2017. US Department of Agriculture, Agricultural Research Service, Nutrient Data Laboratory. USDA National Nutrient Database for Standard Reference Dataset for What We Eat In America, NHANES (Survey-SR), October 2015. Resource Title: Data Dictionary. File Name: SurveySR_DD.pdf

During the 2024 financial year, Starbucks generated a majority of its global revenue from beverage products which amounted to 21.88 billion U.S. dollars. In comparison, the revenue from its food products amounted to 6.75 billion U.S. dollars. The drop in revenue from 2019 to 2020 can be at least partly attributed to the coronavirus (COVID-19) pandemic. What are Starbucks’ total assets? With over 40 thousand Starbucks stores worldwide in 2024, the company has established itself as one of the world’s leading coffeehouse chains. During that same year, Starbucks’ total assets amounted to approximately 31.34 billion U.S. dollars. This figure represents an increase of nearly two billion U.S. dollars when compared to the previous year’s total of 29.45 billion in 2023. How much does Starbucks spend on advertising? Starbucks was valued at over 69 billion U.S. dollars worldwide in 2024, making it the second most valuable quick service restaurant brand in the world. In its fiscal year ending September 2023, Starbucks’ advertising costs totaled roughly 507 million U.S. dollars. This figure represents an increase in global advertising investments compared to the previous year, in which the coffeehouse chain spent 416.7 million U.S. dollars promoting its products and services.

Linked to the journal article published in bioRxiv (https://doi.org/10.1101/2024.06.14.599002).

Abstract

Quantifying feeding patterns provides valuable insights into animal behaviour. However, small invertebrates often consume incredibly small amounts of food. This renders traditional methods, such as weighing individuals before and after food acquisition, either inaccurate or prohibitively expensive. Here, we present a non-invasive method to quantify food consumption of small invertebrates whose body expands during feeding. Using the markerless pose estimation software DeepLabCut, we three-dimensionally track the body of Argentine ants, Linepithema humile. Using these extracted markers, we developed an algorithm which computationally reconstructs the ant’s body, directly measuring volumetric change over time. Moreover, we provide measures of accuracy and quantify the ant’s feeding response to a range of sucrose concentrations, as well as a gradient of caffeine-laced sucrose solutions. Small invertebrates are often prolific invasive species and disease vectors, causing significant ecological and economical damage. Understanding their feeding behaviour could be an important step towards effective control strategies.

• VolEst_C1_volume_calculation_multiprocessing.py: Takes as input H5 3D DeepLabCut files, calculates the gaster volume at every frame using seven different methods and outputs these as CSV files.
• VolEst_C2_interactive_GUI.py: Given a folder with Volume CSV files, interactively plots the volume over time, 3D coordinates tracked by DeepLabCut and the frame of interest for both cameras.
• VolEst_C3_linear_regression.py: Applies a linear regression to each feeding event tracked and provides measures of interest such as crop load and consumption rate.
• VolEst_C4_statistical_analysis: Complete statistical analysis and code for the manuscript.
• VolEst_D1_sucrose_density.csv: Data obtained to quantify the density of sucrose solutions of varying molarity.
• VolEst_D2_accuracy_weight_metadata.csv: Manually collected metadata pertaining to experimental conditions, subjects, and treatments for the weight-volume accuracy measurements.
• VolEst_D3_accuracy_weight.zip: Folder containing the raw points tracked using DeepLabCut, all relevant data obtained from the algorithms created, and a sample video of the experiment for the weight-volume accuracy measurements.
• VolEst_D4_accuracy_nanoliter_metadata.csv: Manually collected metadata pertaining to experimental conditions, subjects, and treatments for the volume-volume accuracy measurements.
• VolEst_D5_accuracy_nanoliter.zip: Folder containing the raw points tracked using DeepLabCut, all relevant data obtained from the algorithms created, and a sample video of the experiment for the volume-volume accuracy measurements.
• VolEst_D6_sucrose_caffeine_consumption_metadata.csv: Manually collected metadata pertaining to experimental conditions, subjects, and treatments for the sucrose and caffeine dilutions application measurements.
• VolEst_D7_sucrose_caffeine_consumption.zip: Folder containing the raw points tracked using DeepLabCut, all relevant data obtained from the algorithms created, and a sample video of the experiment for the sucrose and caffeine dilutions application measurements.
• VolEst_Camera_A-Henrique-2023-09-20.zip: DeepLabCut labels and trained network for camera A.
• VolEst_Camera_B-Henrique-2023-09-20.zip: DeepLabCut labels and trained network for camera B.
• VolEst_base.stl: 3D file for the resin platform used in the experimental validation of the setup.
• VolEst_platform.stl: 3D file for the resin platform used in the experimental validation of the setup.