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Researchers estimate that approximately 200 million people worldwide are affected by age-related macular degeneration (AMD), a condition that impairs central vision and can cause blurriness or other visual disturbances.

There are two forms of AMD. The more common type is dry AMD, which involves gradual damage to the macula—a region at the back of the retina—as part of the natural aging process. Wet AMD, on the other hand, occurs when abnormal blood vessels grow behind the eye and damage the macula, reported Medical News Today.

A recent study featured in the journal Food Science & Nutrition suggests that a mix of genetic factors and consuming instant coffee could raise the risk of developing dry age-related macular degeneration (AMD).

In this study, researchers gathered coffee consumption data from over 500,000 individuals using the UK Biobank genome-wide association studies (GWAS) summary statistics. Participants were categorised based on their coffee preferences: decaffeinated, ground, or instant coffee.

Additionally, data on both dry and wet age-related macular degeneration (AMD) in adults aged 50 and older was sourced from the Finngen GWAS dataset.

Using the collected data, researchers applied several analytical methods—such as Mendelian randomisation and linkage disequilibrium score regression (LDSC)—to explore potential genetic links.

By the end of the study, they discovered a genetic overlap between a predisposition for drinking instant coffee and an increased risk of developing dry AMD.

Moreover, within this genetic connection, they found that consuming instant coffee—as opposed to other types—was associated with a roughly sevenfold higher risk of dry AMD.

In this study, we analyzed the temporal trends in the burden of kidney cancer (KC) in China from 1990 to 2021. In 2021, the number of incident KC cases in China reached 65,799 (4.62 cases per 100,000 total population). Additionally, KC resulted in 24,867 deaths (1.75 deaths per 100,000 total population). Over the past 30 years, both the prevalence and mortality of KC have increased significantly. We observed a notable rise in the incidence, mortality, and disability-adjusted life years (DALYs) of kidney cancer in China over the three-decade period, with more pronounced increases in males than in females. The China age-standardized incidence rate (ASIR) of kidney cancer increased from 1.79 per 100,000 in 1990 to 3.31 per 100,000 in 2021. Furthermore, the age-standardized mortality rate (ASMR) of kidney cancer also rose, from 1.14 per 100,000 in 1990 to 2.25 per 100,000 in 2021.

The increasing burden of kidney cancer can be attributed to several key factors. First, population aging is a major driver, as the incidence of kidney cancer increases with age [26, 27]. China’s population is rapidly aging, with the proportion of individuals aged 65 and older projected to rise from 15.6% in 2024 to 26% in 2050 [28]. This demographic shift toward an older population contributes to a higher risk of developing kidney cancer [7]. Risk factors such as smoking, alcohol consumption, overweight, and hypertension have important implications for both kidney cancer incidence and mortality [14, 29, 30]. Our study showed that the burden of KC in males was consistently higher than in females across different age groups. Males are generally exposed to these risk factors for longer durations, making them more susceptible to KC. For example, the global smoking rate was estimated to be 32.6% in males and 6.5% in females in 2020 [31]. Previous studies have also indicated that males tend to have higher BMIs than females [32]. Moreover, industries with higher male participation may expose individuals to occupational hazards associated with urinary tract cancers [33] Reports suggest that males are approximately twice as likely as females to be occupationally exposed to trichloroethylene, and males also exhibit higher prevalence in jobs involving trichloroethylene exposure [34]. Between 1990 and 2021, smoking and high BMI were the primary drivers of KC in individuals aged 65 and older. Smoking significantly increases the risk of KC incidence and mortality [35].

Previous epidemiological evidence has indicated that age is an independent and critical risk factor for KC, with varying numbers of deaths across different age groups [11]. According to age-period-cohort analysis, KC prevalence and mortality increase with advancing age. After the 60–64 age group, the risk trend of the age effect increases roughly exponentially. Middle-aged and elderly individuals are more likely to have long-term smoking and obesity, which elevate their risk of KC [36]. The period effect refers to changes in medical technology, diagnostic methods, and economic and cultural factors that influence the disease burden of KC during specific time periods. According to the current study, the period effect on KC prevalence showed a slight decrease, possibly due to the recent popularization of medical knowledge in China, which has reduced some KC cases. The cohort effect highlights socioeconomic, behavioral, and environmental exposures in early life and the risks of different birth cohorts. In our study, the cohort effect on KC prevalence showed a downward trend: earlier birth cohorts had a higher risk of KC, while more recent cohorts had a lower risk. In addition to age, this decreasing effect can be attributed to better education and higher health awareness among younger generations.

Monitoring disease prevalence and predicting trends are essential components of disease prevention and control. As a predictive model, the Bayesian age-period-cohort (BAPC) model has been proven reliable [4]. Therefore, we conducted BAPC analysis to project trends in the age-standardized incidence and mortality rates of kidney cancer. According to the BAPC model, the prevalence and mortality of KC are expected to rise to 4.58 per 100,000 and 1.31 per 100,000 by 2036. The large gap between high KC prevalence and low awareness/treatment may partially explain the consistent increase in mortality in recent years. Thus, a comprehensive strategy is needed, including risk factor prevention at the primary care level, KC screening for the elderly and high-risk populations, and access to high-quality medical services, to reduce the burden of KC and achieve better health outcomes for KC patients.

Given the exponential rise in kidney cancer (KC) risk after 60–64 years of age and China’s rapidly aging population—with individuals aged ≥ 65 projected to account for 26% of the population by 2050—integrating age-stratified screening into primary care for older adults is critical. Priorities include expanding low-cost, non-invasive screening tools (e.g., urine cytology, renal ultrasound) for high-risk groups, particularly those with smoking or obesity histories. Multisectoral policies must address modifiable risks: strengthening tobacco taxation and smoke-free legislation, promoting population-wide body mass index (BMI) management through dietary and physical activity initiatives, and enhancing workplace safety regulations to reduce occupational carcinogen exposure—especially among male workers.

The lower KC risk observed in younger generations, likely linked to improved education and health awareness, highlights the need to scale public education programs emphasizing early detection, risk avoidance, and regular screening. Additionally, to address the projected rise in KC burden through 2036, healthcare infrastructure upgrades—particularly in resource-constrained regions—are essential to ensure equitable access to diagnostics and advanced therapies, such as targeted treatments for advanced KC.

Collectively, translating these findings into action requires a synergistic strategy integrating primary prevention (risk factor control), age- and sex-tailored screening, and tertiary care optimization, supported by robust surveillance models like the Bayesian age-period-cohort framework, to curtail rising KC burden and improve outcomes for at-risk populations in China.

Limitations

This analysis provides valuable data reference for KC prevention and control efforts. However, the study has several limitations. First, the data provided in GBD 2021 are based on estimates and mathematical modeling, which may affect the accuracy and reliability of burden estimates. Second, several types of KC, such as clear cell renal cell carcinoma, chromophobe renal cell carcinoma, and papillary renal cell carcinoma, are not included in the GBD database, precluding subtype-specific analysis of the KC burden. Third, our analysis of the KC burden was conducted at the national level without further exploration of the complex interactions between genetic and environmental factors contributing to KC development.

Table 1 presents differences in characteristics for those who reported losing and adopting foods after migration. Those who reported no longer consuming at least one type of food after migration were different from those who reported that they still ate all of the same items in terms of region of origin, economic standing, age, education, region of residence, years in the US, marital status, school children living at home, English fluency and visa type. Those who reported eating some new foods after migration were different from those who didn’t in terms of region of origin, economic standing, age, education, region of residence, years in the US, marital status, school children living at home, English fluency, and visa type.

Those who reported losing or adopting foods listed on average 3.5 foods that they no longer consumed and 3.2 foods that they started consuming after migration. Figure 2 lists foods no longer consumed in the US (lost) and foods newly consumed in the US (adopted). The most often reported lost food items were “ethnic foods” (21.9%) and vegetables (16.2%); the most often reported adopted food items were red (18.5%) and processed meats (17.2%).

Food groups no longer consumed in the US

PCA scree plots and eigenvalues composed of foods no longer eaten in the US indicated that a three- to six-factor solution was the best fit to the data. PCA for foods no longer eaten in the US stratified by years in the US and gender had excellent to acceptable fit for the three-factor solution (Appendix Table 2). A three-factor solution for foods no longer eaten in the US combined by gender and years in the US was selected as the most meaningful.

We assigned names to food patterns based on the positive factor loadings that contributed most to each pattern (≥0.20) Component 1: home country foods; Component 2: protein & whole grains; Component 3: meat & vegetables (Fig. 3, Panel A). 21% of the variance was explained with a three-factor solution. The home country foods pattern comprised of “ethnic foods” (includes items such as “bread from my home country, ethiopian bread, etc”), cheese, and refined grains with high negative loadings for fish, fruit and vegetables. A high negative loading for a food group means individuals that had listed food groups like “ethnic foods”, cheese, and refined grains were less likely than the overall sample to report losing foods such as fish, fruits and vegetables. The protein & whole grains pattern comprised of soup, whole grains, eggs, poultry, and beans/nuts/legumes/seeds with high negative loadings for chips/snacks, sweets, ethnic foods, and fruit. The meat & vegetables pattern comprised of fats, fish, eggs, poultry, red meat, and vegetables, with high negative loadings for whole grains and beans/legumes/nuts/seeds.

Patterns of foods no longer consumed in the US

Table 2 shows associations of individual covariates with the three lost food patterns described above. Note that in interpretation of estimates from the models of lost food patterns, a positive estimate means higher reporting of a lost food pattern and a negative estimate means lower reporting of a lost food pattern.

Individuals from East and South Asia and Europe were more likely to report losing foods in the meat & vegetables pattern [β (95% CI)]; [Component 3: Those from East & South Asia (0.19 [0.06,0.33]); Europe (0.28 [0.13,0.43]] and Europe were also more likely to report losing foods within the home country foods pattern [Component 1: (0.29 [0.12,0.47])] compared to those from Latin America. Men were less likely to report losing foods within the protein & whole grains pattern [Comp 2: -0.18 (-0.28,-0.08)] than women. Those with more education were less likely to report losing foods within the protein & whole grains pattern [Component 2: -0.01 (-0.03,-0.0008)]. Those currently living in the Western US were more likely to report losing foods within the home country foods pattern [Component 1: 0.22 (0.07,0.37)] compared to those who were living in the Southeast. Those who had lived in the US for longer were more likely to report losing foods within the home country foods pattern [Component 1: 0.01 (0.002,0.02)]. Those who migrated to the US on an employment visa were more likely to report losing foods within the home country foods pattern [Component 1: 0.17 (0.02,0.33)] compared to those who migrated on a family reunification visa.

Food groups consumed in the US

PCA scree plots and eigenvalues composed of foods adopted after coming to the US suggested that a three- to six-factor solution was the best fit to the data. PCA for foods adopted in the US stratified by years in the US revealed excellent to acceptable fit for the three factor solution. However, PCA adopted foods stratified by gender revealed a congruence coefficient below the threshold of 0.50, meaning the patterns for men and women are not similar enough to combine and we kept a 3-factor solution for adopted foods stratified by gender (36% of variance for both men and women) (Appendix Table 2).

For men, the names assigned based on the 3-factor solution and the factor loadings were: [Component 1: junk food; Component 2: meat (red and processed) and refined grains; Component 3: “ethnic” & refined grains]. (Fig. 3, Panel B). The junk food pattern comprised of pizza and processed meats, with a high negative loading for red meat. The meat & refined grains pattern comprised of processed meats, refined grains, and red meat with high negative loadings for fruits and vegetables. The “ethnic” & refined grains pattern comprised of “ethnic” (including soups) and refined grains with high negative loadings for pizza, processed meats, red meat, and fruits.

For women, (Fig. 3, Panel C), components explained 36% of the variance with a 3-factor solution [Component 1: fruits & vegetables; Component 2: red meat & poultry/eggs; Component 3: meat (red & processed) & fruits]. The fruits & vegetable pattern was comprised of fruits and vegetables with high negative loadings for pizza and processed meats. The red meat & poultry/eggs pattern was comprised of red meat and poultry/eggs with high negative loadings for processed meats and fruit. The meat & fruit pattern was comprised of processed meats, red meat, and fruit with a high negative loading for vegetables.

Patterns of foods consumed in the US

Men from Europe, Central Asia, Canada regions were less likely to report adopting foods within the junk foods pattern and the meat & refined grains [Components 1: -0.10 (-0.17,-0.02); Component 2: -0.18 (-0.25,-0.11)] compared to those from Latin America and the Caribbean (Table 3). Men who lived in rural areas compared to urban areas before migration were less likely to report adopting foods within the junk foods pattern and “ethnic” & refined grains pattern [Components 1 & 3] [Component 1: -0.06,-0.12,-0.003)]; Component 3: -0.07 (-0.11,-0.02)]. Men living in the Midwest, Northeast, and Western regions of the US were more likely to report adopting foods within the junk foods pattern [Component 1] compared to those living in the Southeast region [Midwest: 0.14 (0.06,0.23)]; [Northeast: 0.08 (0.01,0.15)]; [West: 0.11 (0.03,0.18)]. Men living in the Northeast were less likely to report adopting foods within the meat & refined grains pattern [Component 2] [-0.08 (-0.15,-0.02)]. Men who had come to the US on refugee visas were less likely to report adopting foods within the three components compared to men who arrived on a family reunification visas [Component 1: -0.14 (-0.23,-0.04]; [Component 2: -0.09 (-0.17,-0.0009)]; [Component 3: -0.12 (-0.18,-0.06)].

Women from East and South Asia and Europe were more likely to report adopting foods within the fruits & vegetables pattern [Component 1] compared to those from the Latin America and Caribbean region (Table 3) [East and South Asia: 0.11 (0.05,0.18)]; [Europe: 0.25 (0.17,0.32)]. Women from Middle East and North Africa were less likely to report adopting foods within the meat & fruit pattern [Component 3: -0.11 (-0.18,0.01)] compared to those from Latin America and Caribbean region. Women living in the Northeast were less likely to report adopting foods within the red meat & poultry/eggs pattern [Component 2] compared to women living in the Southeast [-0.09 (-0.15,-0.04)]. Women who had lived in the US for longer were less likely to report foods within the meat & fruit pattern [Component 3: -0.003 (-0.0005,-0.002)]. Women who had obtained a legalization visa in 2003 were more likely to report adopting foods in line with fruits & vegetables pattern [Component 1: 0.09 (0.006,0.17)] and red meat & poultry/eggs pattern [Component 2: 0.13 (0.06,0.22)] compared to those with a family reunification visa.

This study developed and validated a comprehensive questionnaire (Supplementary Table 3) aimed at identifying factors influencing hookah smoking behavior across personal, interpersonal, and organizational levels. The initial version of the questionnaire was informed by a qualitative study, which provided valuable insights into relevant factors. Through an iterative process, certain items were removed to enhance clarity and relevance, resulting in a refined instrument that was subsequently tested for content validity. The results confirmed the reliability and validity of the questionnaire. The final questionnaire included 81 items aligned with 16 factors. Having tested the face validity, content validity, and construct validity were substantiated. The results offer evidence that this questionnaire is a valid and reliable tool for assessing factors related to hookah smoking among women. To our knowledge, this is the first study to focus specifically on vulnerable populations, such as women who smoke hookah in the Eastern Mediterranean region. Further validation across different sites and cultural contexts would enhance its applicability and provide deeper insights into its broader relevance.

The need for a questionnaire on women’s hookah smoking in Iran is urgent due to the significant increase in hookah smoking among Iranian women and the adverse effects of consuming this tobacco product on health [24, 25]. Gender differences exist in why men and women start hookah smoking. For example, Iranian men with Turkmen ethnicity often begin smoking due to cultural identity and sense of adulthood [26], while women are more influenced by social approval and emotional needs [14, 27]. These differences suggest that public health strategies should be tailored by gender, and because of this, we need a gender-specific questionnaire. The lack of a questionnaire specifically designed for women shows the need to design one to measure the effective factors in the initiation and continuation of hookah smoking among women. This questionnaire can help develop systematic health promotion initiatives and interventions that specifically address women’s needs and behaviors. There are several questionnaires to evaluate hookah smoking, such as the Hookah Smoking Initiation for Women Questionnaire (HIWQ). This questionnaire was designed using an exploratory sequential mixed methods approach to include six dimensions: drawing the attention of other people, the need to have fun and be relaxed, hookah smoking in the family, availability of hookah, curiosity and having a positive attitude toward hookah. HIWQ aims to assess the initiation of hookah smoking by women. In the questionnaire used in the present study, besides these factors, other issues have also been addressed such as socio-economic deficiencies and role of advertisement and education [13]. Hookah Smoking Obscenity Measurement Scale for Adolescents evaluates the level of obscenity related to hookah smoking among adolescents. This instrument is not specifically designed for women, and considers a specific age group (i.e., adolescents) [12]. The Questionnaire on Smoking Urges for Assessment of Hookah Smoking evaluates the tendency to smoke hookah and, like the previous questionnaire, it is not specifically designed for women [11]. These questionnaires provide a basis for the development of a comprehensive and culturally relevant instrument. It evaluated the beginning and continuation of hookah, which, besides the factors included in these questionnaires, also deals with other factors at the personal, interpersonal and organizational levels.

These factors include socioeconomic deficiencies, role of advertisement and education, availability, fun and entertainment, hookah smoking in family and relatives, search for peace, attracting others’ attention and approval, physical and mental dependence, color, flavor and sound of hookah, happy environment of coffee shops, pleasant experience of the first puff of hookah smoking, The prevalence of acceptability of hookah smoking in society, false beliefs, Low self-efficacy, Peer pressure, and Family tendencies. These factors showed adequate internal consistency and construct validity and supported their use in evaluating the key factors underlying hookah smoking behavior.

Our developed and validated questionnaire addresses many dimensions, including low self-efficacy, physical/mental dependence, attracting others’ attention and approval, search for peace, positive attitude towards hookah, false beliefs about personal factors underlying hookah smoking, the color, taste, and sound of hookah, and the pleasant experience of the first puff of hookah. Low self-efficacy, or belief in one’s ability to resist hookah smoking, is a main factor that contributes to hookah smoking. Women with low self-efficacy are more likely to initiate and continue hookah smoking [15]. Self-efficacy assessment helps understand people’s vulnerability to hookah smoking. Moreover, hookah smoking can become addictive and make it hard for women to quit. Assessing the degree of dependence provides insights into the intensity of hookah smoking and the challenges of cessation [15]. Having a positive attitude towards hookah is a major reason for smoking among women. Women who hold more favorable beliefs about hookah are less likely to quit [14, 28]. Assessing attitudes helps identify women at risk of hookah smoking and guides researchers to design interventions to change these attitudes. Meanwhile, the spread of false beliefs about the harmlessness of hookah smoking affects people’s attitudes toward this tobacco product [29]. Some women believe that hookah is less harmful than cigarettes or even has health benefits. The belief that hookah smoking is pleasant and acceptable may add to its popularity among women. It is important to assess these misconceptions to correct them through education. Therefore, individual factors can be effective in women’s hookah smoking, and including relevant questions in questionnaires provides a comprehensive assessment of the risk of hookah smoking in women. This information can guide systematic interventions to prevent hookah initiation, reduce smoking, and promote hookah cessation.

Interpersonal factors also play a significant role in hookah smoking among women. These factors in the current study include the influence of peers and friends, family preferences, and the role of the family in hookah smoking. These factors are of utmost importance and need to be included in the questionnaire. The role of peers and friends is admittedly an important interpersonal factor involved in hookah smoking among women. Hookah smoking has deep roots in the culture and history of many societies. Climate and cultural norms can affect the prevalence of hookah smoking among women. For example, in some societies like Iran, hookah smoking is considered a social norm and a way to communicate with others as opposed to cigarette which carries stigma for women who smoke [14, 28, 29]. Social norms and peer pressure can initiate, encourage or prohibit the use of hookah. If people closely related to women are hookah smokers, it is more likely that they begin to smoke hookahs too [29]. Friends’ and acquaintances’ smoking can tempt women to smoke hookahs. Including questions about peer pressure in the questionnaire helps recognize the effect of social networks on hookah smoking and informs professionals about interventions that address these relationships. In some cultures, family members may encourage or prohibit hookah smoking, and women may be strongly influenced in their hookah smoking behavior. In this regard, researchers reported that familial habits like having hookah-smoking family members, especially parents or siblings can influence women’s decision to go for hookahs [29, 30]. It can be argued that people can copy hookah smoking by friends and family members and be tempted to smoke due to the availability of hookahs, or the environments that facilitate its use. Including questions about family tendencies in the questionnaire can highlight the role of family in hookah smoking and contribute to interventions that address family dynamics.

Organizational factors are among the other factors included in this questionnaire as advertisement and education. Advertising can promote hookah smoking by introducing hookah as a social and cultural norm. This could lead to a higher prevalence of hookah smoking among women, as they are more influenced by social norms and cultural expectations [28, 31]. Education can play a significant role in reducing the rate of hookah smoking among women. Educating women on the health risks of hookah smoking can help them make informed decisions about their health.

In the current study, social factors were also included in the questionnaire. Social factors play a significant role in women’s hookah smoking. These factors included availability, fun and entertainment, socio-economic deficiencies, and happy environment of coffee shops. Easy access to hookah and its low cost are the main factors underlying its prevalence. When hookah is readily available and affordable, women tend more to try it [16]. Moreover, recreational centers where hookah is sold, such as coffee shops and restaurants, can further encourage hookah smoking by providing a pleasant social environment and easy access to hookahs [14, 29]. In addition to the prevalence of hookah smoking in families, the prevalence in public places like coffee shops also familiarizes the young with hookah and gives them easy access to it. The lower cost of hookah compared to other recreational drugs has also attracted many people. The lack of appropriate and large enough social contexts for women, especially recreational facilities, can affect their hookah smoking patterns. This points to the necessity of considering the social and political factors that shape the opportunities and limitations facing women [15]. The political and regulatory system significantly affects the availability of hookahs [27]. Therefore, including questions about social factors in the questionnaire is essential to consider the role of these factors in hookah smoking among women. These factors can provide valuable insights into the social effects of hookah smoking.

The comprehensive nature of this questionnaire, which includes a wide range of factors, increases its effectiveness in capturing the multidimensional aspects of hookah smoking. Nevertheless, this study has some limitations. First, it was conducted in a single city in Iran, limiting the generalizability of the findings to the wider population of women in Iran or beyond. Further testing in different regions is necessary to enhance the study’s broader applicability. The questionnaire can indeed be applicable to women in other MENA countries as well as in other similar contexts. Second, all data were self-reported, which may introduce recall or reporting biases. Lastly, variations in the use of flavored and non-flavored hookah tobacco, which may influence users’ perceptions and behaviors, were not assessed in this study. Although women in Iran typically smoke mildly flavored hookah tobacco, future studies should account for this important factor.

Implications of the study

The present study has major implications for understanding and measuring the complex nature of hookah smoking behavior. Recognition and measurement of these factors give researchers and public health professionals a deeper understanding of the causes and effects of hookah smoking. This knowledge can help with the development of systematic interventions and policies aimed at reducing hookah smoking and its health risks. Future research can use this valid questionnaire to further investigate the factors affecting hookah smoking in different populations and environments. By expanding the scope of research and interventions based on the present findings, stakeholders can attempt to develop goal-oriented strategies to address the complex interplay of personal, interpersonal, and social factors underlying hookah smoking.