Dataset of obesity in relation to female-specific cancers in middle eastern countries, 1990 to 2016

Abstract

Objectives

Understanding the relationship between obesity and female-specific cancers (FSCs) is crucial for public health planning and policy development. The current data paper presented a dataset that includes obesity prevalence and incidence rates of breast, ovarian, cervical, and uterine cancers among women in Middle Eastern countries. This dataset could be used for time-trend analysis and different forecasting models. Moreover, exploring the relationship between obesity and FSCs is important to develop preventive healthcare services, especially among developing countries.

Data description

The dataset comprises official statistics obtained from reputable sources including the world bank and global burden of disease (GBD) database. The data include a total of 405 observations across 15 middle-eastern countries, from 1990 to 2016. Key variables are obesity prevalence and incidence rate of four major cancers in women including breast cancer, ovarian cancer, cervical cancer, and uterine cancer. This panel data is mainly prepared to investigate the temporal relationship between obesity prevalence and FSC incidence rates, and also performing Counterfactual analysis. Moreover, this data could be utilized for advanced machine learning techniques to estimate future shifts in trend and patterns over time.

Objective

Cancer remains one of the leading causes of morbidity and mortality worldwide, posing significant public health challenges across diverse populations [1]. Among the various types of cancer, female-specific cancers (FSCs) represent a significant concern. These cancers not only affect survival rates but also have profound implications for the quality of life of women and their families, leading to emotional distress, financial burdens, and shifts in social dynamics [2]. The burden of these diseases underscores the necessity for effective prevention and early detection strategies, which can significantly reduce the associated health burdens [3]. Addressing these cancers requires a multifaceted approach that includes public awareness, access to screening programs, and improved healthcare resources. As the incidence of FSCs continues to rise, it becomes increasingly imperative to prioritize research and interventions that target risk factors and promote women’s health on a broader scale [3, 4].

The current global obesity epidemic has paralleled the rising incidence of various cancers, with a notable increase in FSCs [5]. This trend is particularly alarming in Middle Eastern countries, where a shift towards a more westernized lifestyle has contributed to the growing prevalence of both obesity and cancer [5, 6]. Hence, the interplay between obesity and female cancers as a crucial concern may require further investigations.

This panel data has been curated to facilitate research aimed at elucidating the temporal relationship between obesity and the incidence rates of FSCs in Middle Eastern countries. Understanding this relationship is crucial for public health planning and policy, as it aids in identifying trends that inform targeted interventions and preventive healthcare services, particularly in developing countries [6]. The dataset supports time-trend and counterfactual analyses, and can also be utilized for advanced machine learning techniques to forecast future trends and patterns, including join-point analysis and ‘what-if’ scenario modeling.

Data description

The dataset comprises yearly data on obesity prevalence and the incidence rates of FSCs across 15 Middle Eastern countries. It includes essential information on country names, years, obesity prevalence sourced from the World Bank [7], as well as incidence rates for each FSC derived from the Global Burden of Disease (GBD) study [8]. Additionally, five additional variables (from the world bank) were included. The dataset encompasses 15 Middle Eastern countries and spans 27 years (1990–2016), resulting in a total of 405 observations (data file 1, Table 1).

The dataset includes following key variables and their definitions. “Country”: Represents the name of the Middle Eastern country and is recorded as a string. “Year”: Indicates the year of data collection, ranging from 1990 to 2016. “Obesity_Prev”: Measures the percentage of the adult female population classified as obese. The following Four variables refer to incidence rate of breast cancer (“BreastCa_Inc”), ovarian cancer (“OvarianCa_Inc”), cervical cancer (“CervicalCa_Inc”), uterine cancer (“UterineCa_Inc”). The variables represent the age-standardized incidence rates of the respective cancers, measured per 100,000 women. The following variables, sourced from world bank, are also included as additional variables: “Age65_Perc”: Represents the percentage of adult females aged 65 and older. “ExpSchool_Yr”: Captures the average number of years of schooling expected for females. “Urb_Perc”: The percentage of the total population living in urban areas. “Birth_Rate”: Indicates the number of live births during a year per 1,000 people. “GDP_Percap”: This variable represents the gross domestic product (GDP) per capita in purchasing power parity, measured in U.S. dollars.

To ensure the dataset’s reliability, the data were collected meticulously and in separate steps. Initially, obesity prevalence data were obtained for different countries. In the next step, the incidence rates for FSCs were extracted from the GBD database. Finally, both data were cross-referenced to ensure alignment with the respective years and countries, thereby enhancing the dataset’s accuracy. The data collection process involved identifying the relevant variables based on existing literature and public health significance. The focus on FSCs was driven by their increasing incidence and the potential link to rising obesity rates in the Middle Eastern region. Data were collected from existing databases, ensuring that the most reliable and relevant information was included.

Furthermore, to enhance the usability of the dataset, it was recorded in an Excel file that includes all observations and variables. Additionally, a codebook in PDF format was created to provide detailed descriptions of each variable, including definitions, units of measurement, and sources. This codebook might assist researchers in understanding the dataset’s structure and the context of the collected data (data file 2, Table 1).

The data files are available in the Figshare repository [9], where they can be accessed by researchers and public health professionals.

Table 1 Overview of data files/data sets

Limitations

• Data on obesity prevalence is limited to 2016, so more recent data could not be collected.

• Missing data regarding the variable “expected years of schooling” is prevalent in the dataset.

• Data on other risk factors (e.g., smoking, physical inactivity, oral contraception) were not collected, as they were outside the scope of the main study. Other researchers may need to include these variables if necessary.