Introduction: Although sex differences in allergic diseases such as atopic dermatitis (AD), allergic rhinitis (AR), and asthma are considered important, a limited number of studies during the COVID-19 pandemic investigated this aspect. Therefore, this study aimed to analyze sex-specific and long-term trends and risk factors for allergic diseases before and during the pandemic. Methods: This study utilized data from the Korea National Health and Nutrition Examination Survey, 2007–2022, including 92,135 participants aged 19 years and older. This study used weighted multivariate regression analysis to examine the estimates of related factors and assessed weighted odds ratios or β-coefficients for these factors across multiple categories. Results: During the study period (2007–2022), the prevalence of AR was more common in females than in males. Particularly in 2022, the prevalence among females was 19.3% (95% confidence interval, 17.3–21.3), while among males, it was 15.6% (13.8–17.4). The prevalence of AD and asthma showed a slight disparity between males and females. Before and during the pandemic, the prevalence of AD and AR showed a continuous increase (AD: from 2.8% [2.5–3.2] in 2007–2009 to 4.7% [3.9–5.4] in 2022; AR: from 11.7% [11.1–12.4] in 2007–2009 to 17.4% [16.0–18.9] in 2022), while asthma maintained a relatively stable trend. Moreover, this study identified several sex-specific factors that seem to be associated with a higher prevalence of allergic diseases in females, such as high household income, smoking, and being overweight or obese. Conclusions: Throughout all the periods examined, females consistently exhibited a higher prevalence of AR compared to males. Moreover, the risk factors for males and females varied depending on the disease, with females generally facing a greater number of risk factors. Consequently, this study highlights the necessity for sex-specific health interventions and further research to comprehend the complex influence of socioeconomic factors and lifestyle choices on the prevalence and risk of AD, AR, and asthma.

Allergic diseases, including atopic dermatitis (AD), allergic rhinitis (AR), and asthma, represent a significant global health burden, affecting a substantial portion of the population worldwide [1‒3], which may lead to a significant decline in the quality of life [4]. This situation underscores the importance of understanding the factors associated with allergic diseases, including the role of different variables. According to a previous study, the prevalence of asthma has been reported to be 20% higher specifically in females aged over 35 years on a global scale [5]. Furthermore, another previous study found that females reported a higher history of personal and familial AD [6]. Such a discrepancy may be attributed to the influence of sex hormones on allergic diseases, resulting in a higher incidence of allergies in females post-puberty compared to males [7].

Although it is important to consider sex differences when examining allergic diseases, recent studies have not been designed to investigate the sex-specific and long-term prevalence and risk factors of these allergic diseases, especially during the COVID-19 pandemic. The COVID-19 pandemic has introduced several challenges and changes to healthcare systems and individual health behaviors, which could have influenced the prevalence and management of allergic diseases [8]. For instance, changes in hygiene practices, mask-wearing, and alterations in healthcare access during the pandemic may have had differential impacts on allergic disease prevalence and control across different sexes.

Therefore, this study investigates sex-specific, long-term prevalence, and risk factors of allergic diseases such as AD, AR, and asthma, explicitly considering the influence of sex and several variables before and during the COVID-19 pandemic [9]. The data for this analysis are derived from the Korea National Health and Nutrition Examination Survey (KNHANES), conducted from 2007 to 2022. By conducting this study, we can investigate the long-term prevalence and risk factors of allergic diseases in South Korea, emphasizing sex differences and the potential impact of the COVID-19 pandemic on these conditions.

Data Source

This study used data from the KNHANES, an annual survey administered by the Korea Disease Control and Prevention Agency from 2007 to 2022 [9]. The KNHANES employs a complex stratified cluster sampling method to ensure representativeness and minimize bias [9]. In addition, the survey applies weighting factors to the collected data, accurately reflecting the Korean population’s distribution, thereby allowing for precise national health and nutrition assessments. Based on previous studies, we included variables that may influence allergic diseases: age, sex, region of residence, body mass index (BMI), education level, household income, and smoking status. For the analysis of sex-specific prevalence in AD, AR, and asthma, a nationally representative sample of 92,135 participants was selected. The survey spanned 16 years, with participant counts per year grouped as follows: 16,768 in 2007–2009; 17,773 in 2010–2012; 22,488 in 2013–2016; 18,548 in 2017–2019; 5,801 in 2020; 5,553 in 2021; and 5,204 in 2022. The study was approved by the Institutional Review Board of the Korea Disease Control and Prevention Agency (2007-02CON-04-P, 2008-04EXP-01-C, 2009-01CON-03-2C, 2010-02CON-21-C, 2011-02CON-06-C, 2012-01EXP-01–2C, 2013-07CON-03–4C, 2013-12EXP-03–5C, 2018-01-03-P-A, 2018-01-03-C-A, 2018-01-03-2C-A, 2018-01-03-5C-A, and 2018-01-03-4C-A), and written informed consent was obtained from all participants. The study was conducted using the principles outlined in the Declaration of Helsinki.

Definition of Allergic Diseases

The objective of this study was to assess the overall trends in the sex-specific prevalence of AD, AR, and asthma from 2007 to 2022. Each allergic disease was defined by the question as follows: AD was defined as those who answered “yes” to “Have you ever been diagnosed with AD by a doctor?”; AR was defined as those who answered “yes” to “Have you ever been diagnosed with AR by a doctor?”; Asthma was defined as those who answered “yes” to “Have you ever been diagnosed with asthma by a doctor?” [9] Based on these questions, allergic diseases were determined according to their presence or absence. Furthermore, data were collected on potential risk factors for the onset of allergic diseases, including age, sex, and socioeconomic status [10].

Covariates

The covariates considered in this study were selected based on previous studies indicating their potential influence on allergic diseases [11]. These covariates included sex, age (19–39, 40–59, and ≥60 years), region of residence (urban and rural) [12], BMI (underweight or normal, and overweight or obese), smoking status (none and current smoking), level of education (high school or lower education, and college or higher education), and household income (low and high). BMI categories were classified according to the Asian-Pacific guidelines into four groups: underweight (<18.5 kg/m2), normal weight (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25.0 kg/m2) [13, 14]. Furthermore, current smokers were defined as those who engaged in smoking at least once within 1 month.

Statistical Analyses

Using data from the KNHANES from 2007 to 2022, with data grouped annually, we examined trends in the sex-specific prevalence of AD, AR, and asthma. The survey period from 2007 to 2022 was segmented as follows: 2007–2009, 2010–2012, 2013–2016, 2017–2019, 2020, 2021, and 2022, with the pandemic period considered separately. The outcomes of this study were obtained through qualitative data expressed as proportions or percentages. Weighted complex sampling analysis was implemented to ensure precise estimation, minimizing the effect of the difference in the number of participants each year. For statistical analysis, weighted linear or binomial logistic regression models were utilized to compute odds ratios or β-coefficients with a 95% confidence interval (CI). To enhance the reliability of the findings, stratification analysis was carried out, accounting for variables such as age, sex, level of education, region of residence, household income, and smoking in all regression models. Moreover, weighted multivariate regression models were employed to compare the estimates of relevant factors before and during the pandemic. The results were presented in weighted odds ratios and their corresponding 95% CI. All statistical analyses were performed using SAS software (version 9.4; SAS Institute, Cary, NC, USA) with a two-sided test, and significance was considered at a p value <0.05 [15].

This study included a total of 92,135 participants for analysis after excluding 7,306 individuals with missing smoking status, education level, household income, BMI, and weighted data from the total sample of 99,441 survey respondents. The weighted baseline characteristics of the participants are as follows: sex (male, 49.6% [95% CI, 49.3–50.0]) and age (19–39 years, 36.2% [95% CI, 35.5–36.9]; 40–59 years, 39.3% [95% CI, 38.7–39.9]; and ≥60 years, 24.5% [95% CI, 23.9–25.2]; Table 1).

Table 1.

General characteristics of Korean based on data obtained from the KNHANES, 2007–2022 (n = 92,135)

CharacteristicTotalBefore the pandemicDuring the pandemic
2007–20092010–20122013–20162017–2019202020212022
Overall, n (%) 92,135 16,768 17,773 22,488 18,548 5,801 5,553 5,204 
Crude rate, n (%) 
Sex, n (%) 
 Male 39,719 (43.11) 7,118 (7.73) 7,504 (8.14) 9,568 (10.38) 8,209 (8.91) 2,611 (2.83) 2,444 (2.65) 2,265 (2.46) 
 Female 52,416 (56.89) 9,650 (10.47) 10,269 (11.15) 12,920 (14.02) 10,339 (11.22) 3,190 (3.46) 3,109 (3.37) 2,939 (3.19) 
Age, n (%) 
 19–39 years 26,478 (28.74) 5,637 (6.12) 5,335 (5.79) 6,395 (6.94) 4,972 (5.40) 1,556 (1.69) 1,308 (1.42) 1,275 (1.38) 
 40–59 years 33,838 (36.73) 6,131 (6.65) 6,560 (7.12) 8,430 (9.15) 6,954 (7.55) 2,022 (2.19) 1,965 (2.13) 1,776 (1.93) 
 ≥60 years 31,819 (34.54) 5,000 (5.43) 5,878 (6.38) 7,663 (8.32) 6,622 (7.19) 2,223 (2.41) 2,280 (2.47) 2,153 (2.34) 
Region of residence, n (%) 
 Urban 41,701 (45.26) 7,208 (7.82) 8,182 (8.88) 10,396 (11.28) 8,585 (9.32) 2,553 (2.77) 2,553 (2.77) 2,224 (2.41) 
 Rural 50,434 (54.74) 9,560 (10.38) 9,591 (10.41) 12,092 (13.12) 9,963 (10.81) 3,248 (3.53) 3,000 (3.26) 2,980 (3.23) 
BMI, n (%)a 
 Underweight or normal 39,686 (43.07) 7,421 (8.05) 7,992 (8.67) 9,693 (10.52) 7,901 (8.58) 2,273 (2.47) 2,246 (2.44) 2,160 (2.34) 
 Overweight or obese 52,449 (56.93) 9,347 (10.14) 9,781 (10.62) 12,795 (13.89) 10,647 (11.56) 3,528 (3.83) 3,307 (3.59) 3,044 (3.30) 
Smoking status, n (%) 
 No 74,763 (81.15) 13,060 (14.17) 14,164 (15.37) 18,357 (19.92) 15,258 (16.56) 4,835 (5.25) 4,671 (5.07) 4,418 (4.80) 
 Yes 17,372 (18.85) 3,708 (4.02) 3,609 (3.92) 4,131 (4.48) 3,290 (3.57) 0.966 (1.05) 0.882 (0.96) 0.786 (0.85) 
Level of education, n (%) 
 High school or lower education 52,677 (57.17) 11,275 (12.24) 11,122 (12.07) 12,517 (13.59) 9,605 (10.42) 2,764 (3.00) 2,839 (3.08) 2,555 (2.77) 
 College or higher education 35,888 (38.95) 5,450 (5.92) 6,477 (7.03) 8,605 (9.34) 7,968 (8.65) 2,559 (2.78) 2,385 (2.59) 2,444 (2.65) 
 Unknown 3,570 (3.87) 0.043 (0.05) 0.174 (0.19) 1,366 (1.48) 0.975 (1.06) 0.478 (0.52) 0.329 (0.36) 0.205 (0.22) 
Household income, n (%) 
 Lowest and second quartile 41,389 (44.92) 7,767 (8.43) 8,098 (8.79) 10,129 (10.99) 8,204 (8.90) 2,451 (2.66) 2,418 (2.62) 2,322 (2.52) 
 Third and highest quartile 50,746 (55.08) 9,001 (9.77) 9,675 (10.50) 12,359 (13.41) 10,344 (11.23) 3,350 (3.64) 3,135 (3.40) 2,882 (3.13) 
Weighted rate (95% CI) 
Sex, weighted % (95% CI) 
 Male 49.63 (49.25–50.01) 49.60 (48.88–50.32) 49.11 (48.35–49.86) 49.13 (48.50–49.76) 49.84 (49.11–50.57) 49.94 (48.87–51.02) 49.89 (48.58–51.20) 49.79 (48.40–51.18) 
 Female 50.37 (49.99–50.75) 50.40 (49.68–51.12) 50.89 (50.14–51.65) 50.87 (50.24–51.50) 50.16 (49.43–50.89) 50.06 (48.98–51.13) 50.11 (48.80–51.42) 50.21 (48.82–51.60) 
Age, weighted % (95% CI) 
 19–39 years 36.19 (35.50–36.87) 42.70 (41.27–44.14) 40.01 (38.69–41.33) 37.20 (36.10–38.31) 35.15 (33.90–36.41) 34.09 (31.77–36.40) 33.22 (31.03–35.40) 32.55 (30.19–34.91) 
 40–59 years 39.27 (38.69–39.85) 38.86 (37.65–40.07) 39.98 (38.93–41.03) 40.45 (39.53–41.37) 39.85 (38.76–40.93) 39.17 (37.09–41.25) 38.56 (36.86–40.26) 38.17 (36.06–40.27) 
 ≥60 years 24.54 (23.90–25.19) 18.44 (17.50–19.38) 20.01 (19.03–20.99) 22.35 (21.44–23.26) 25.00 (23.71–26.30) 26.74 (24.33–29.16) 28.23 (25.84–30.61) 29.29 (26.96–31.61) 
Region of residence, weighted % (95% CI) 
 Urban 46.05 (44.74–47.37) 46.93 (44.84–49.03) 46.90 (44.66–49.13) 46.94 (44.77–49.11) 46.64 (43.31–49.97) 45.25 (38.13–52.36) 45.67 (38.82–52.52) 44.38 (40.63–48.12) 
 Rural 53.95 (52.63–55.26) 53.07 (50.97–55.16) 53.10 (50.87–55.34) 53.06 (50.89–55.23) 53.36 (50.03–56.69) 54.75 (47.64–61.87) 54.33 (47.48–61.18) 55.62 (51.88–59.37) 
BMI, weighted % (95% CI)a 
 Underweight or normal 42.16 (41.66–42.66) 44.51 (43.58–45.44) 45.09 (44.08–46.09) 43.79 (42.94–44.63) 42.91 (42.02–43.81) 38.38 (36.84–39.92) 41.02 (39.25–42.80) 40.32 (38.64–42.00) 
 Overweight or obese 57.84 (57.34–58.34) 55.49 (54.56–56.42) 54.91 (53.91–55.92) 56.21 (55.37–57.06) 57.09 (56.19–57.98) 61.62 (60.08–63.16) 58.98 (57.20–60.75) 59.68 (58.00–61.36) 
Smoking status, weighted % (95% CI) 
 No 78.68 (78.22–79.14) 73.06 (72.21–73.91) 73.82 (72.91–74.73) 77.73 (76.96–78.50) 79.24 (78.38–80.10) 80.77 (79.28–82.26) 81.59 (80.17–83.01) 82.92 (81.36–84.48) 
 Yes 21.32 (20.86–21.78) 26.94 (26.09–27.79) 26.18 (25.27–27.09) 22.27 (21.50–23.04) 20.76 (19.90–21.62) 19.23 (17.74–20.72) 18.41 (16.99–19.83) 17.08 (15.52–18.64) 
Level of education, weighted % (95% CI) 
 High school or lower education 47.84 (47.03–48.66) 59.91 (58.37–61.44) 56.83 (55.33–58.32) 48.72 (47.43–50.01) 44.94 (43.28–46.60) 41.96 (38.99–44.93) 43.82 (40.97–46.68) 41.88 (39.55–44.20) 
 College or higher education 47.93 (47.07–48.78) 39.88 (38.33–41.42) 42.01 (40.50–43.51) 44.64 (43.33–45.96) 49.70 (47.97–51.42) 50.63 (47.40–53.85) 50.96 (47.94–53.98) 55.35 (52.81–57.88) 
 Unknown 4.23 (3.96–4.50) 0.22 (0.14–0.30) 1.16 (0.93–1.40) 6.63 (6.07–7.19) 5.36 (4.79–5.94) 7.41 (6.16–8.67) 5.22 (4.25–6.19) 2.78 (2.24–3.31) 
Household income, weighted % (95% CI) 
 Lowest and second quartile 39.36 (38.45–40.26) 41.30 (39.53–43.07) 43.43 (41.88–44.98) 40.38 (38.88–41.88) 39.98 (38.21–41.75) 36.72 (33.24–40.19) 36.54 (33.25–39.82) 38.09 (35.43–40.75) 
 Third and highest quartile 60.64 (59.74–61.55) 58.70 (56.93–60.47) 56.57 (55.02–58.12) 59.62 (58.12–61.12) 60.02 (58.25–61.79) 63.28 (59.81–66.76) 63.46 (60.18–66.75) 61.91 (59.25–64.57) 
CharacteristicTotalBefore the pandemicDuring the pandemic
2007–20092010–20122013–20162017–2019202020212022
Overall, n (%) 92,135 16,768 17,773 22,488 18,548 5,801 5,553 5,204 
Crude rate, n (%) 
Sex, n (%) 
 Male 39,719 (43.11) 7,118 (7.73) 7,504 (8.14) 9,568 (10.38) 8,209 (8.91) 2,611 (2.83) 2,444 (2.65) 2,265 (2.46) 
 Female 52,416 (56.89) 9,650 (10.47) 10,269 (11.15) 12,920 (14.02) 10,339 (11.22) 3,190 (3.46) 3,109 (3.37) 2,939 (3.19) 
Age, n (%) 
 19–39 years 26,478 (28.74) 5,637 (6.12) 5,335 (5.79) 6,395 (6.94) 4,972 (5.40) 1,556 (1.69) 1,308 (1.42) 1,275 (1.38) 
 40–59 years 33,838 (36.73) 6,131 (6.65) 6,560 (7.12) 8,430 (9.15) 6,954 (7.55) 2,022 (2.19) 1,965 (2.13) 1,776 (1.93) 
 ≥60 years 31,819 (34.54) 5,000 (5.43) 5,878 (6.38) 7,663 (8.32) 6,622 (7.19) 2,223 (2.41) 2,280 (2.47) 2,153 (2.34) 
Region of residence, n (%) 
 Urban 41,701 (45.26) 7,208 (7.82) 8,182 (8.88) 10,396 (11.28) 8,585 (9.32) 2,553 (2.77) 2,553 (2.77) 2,224 (2.41) 
 Rural 50,434 (54.74) 9,560 (10.38) 9,591 (10.41) 12,092 (13.12) 9,963 (10.81) 3,248 (3.53) 3,000 (3.26) 2,980 (3.23) 
BMI, n (%)a 
 Underweight or normal 39,686 (43.07) 7,421 (8.05) 7,992 (8.67) 9,693 (10.52) 7,901 (8.58) 2,273 (2.47) 2,246 (2.44) 2,160 (2.34) 
 Overweight or obese 52,449 (56.93) 9,347 (10.14) 9,781 (10.62) 12,795 (13.89) 10,647 (11.56) 3,528 (3.83) 3,307 (3.59) 3,044 (3.30) 
Smoking status, n (%) 
 No 74,763 (81.15) 13,060 (14.17) 14,164 (15.37) 18,357 (19.92) 15,258 (16.56) 4,835 (5.25) 4,671 (5.07) 4,418 (4.80) 
 Yes 17,372 (18.85) 3,708 (4.02) 3,609 (3.92) 4,131 (4.48) 3,290 (3.57) 0.966 (1.05) 0.882 (0.96) 0.786 (0.85) 
Level of education, n (%) 
 High school or lower education 52,677 (57.17) 11,275 (12.24) 11,122 (12.07) 12,517 (13.59) 9,605 (10.42) 2,764 (3.00) 2,839 (3.08) 2,555 (2.77) 
 College or higher education 35,888 (38.95) 5,450 (5.92) 6,477 (7.03) 8,605 (9.34) 7,968 (8.65) 2,559 (2.78) 2,385 (2.59) 2,444 (2.65) 
 Unknown 3,570 (3.87) 0.043 (0.05) 0.174 (0.19) 1,366 (1.48) 0.975 (1.06) 0.478 (0.52) 0.329 (0.36) 0.205 (0.22) 
Household income, n (%) 
 Lowest and second quartile 41,389 (44.92) 7,767 (8.43) 8,098 (8.79) 10,129 (10.99) 8,204 (8.90) 2,451 (2.66) 2,418 (2.62) 2,322 (2.52) 
 Third and highest quartile 50,746 (55.08) 9,001 (9.77) 9,675 (10.50) 12,359 (13.41) 10,344 (11.23) 3,350 (3.64) 3,135 (3.40) 2,882 (3.13) 
Weighted rate (95% CI) 
Sex, weighted % (95% CI) 
 Male 49.63 (49.25–50.01) 49.60 (48.88–50.32) 49.11 (48.35–49.86) 49.13 (48.50–49.76) 49.84 (49.11–50.57) 49.94 (48.87–51.02) 49.89 (48.58–51.20) 49.79 (48.40–51.18) 
 Female 50.37 (49.99–50.75) 50.40 (49.68–51.12) 50.89 (50.14–51.65) 50.87 (50.24–51.50) 50.16 (49.43–50.89) 50.06 (48.98–51.13) 50.11 (48.80–51.42) 50.21 (48.82–51.60) 
Age, weighted % (95% CI) 
 19–39 years 36.19 (35.50–36.87) 42.70 (41.27–44.14) 40.01 (38.69–41.33) 37.20 (36.10–38.31) 35.15 (33.90–36.41) 34.09 (31.77–36.40) 33.22 (31.03–35.40) 32.55 (30.19–34.91) 
 40–59 years 39.27 (38.69–39.85) 38.86 (37.65–40.07) 39.98 (38.93–41.03) 40.45 (39.53–41.37) 39.85 (38.76–40.93) 39.17 (37.09–41.25) 38.56 (36.86–40.26) 38.17 (36.06–40.27) 
 ≥60 years 24.54 (23.90–25.19) 18.44 (17.50–19.38) 20.01 (19.03–20.99) 22.35 (21.44–23.26) 25.00 (23.71–26.30) 26.74 (24.33–29.16) 28.23 (25.84–30.61) 29.29 (26.96–31.61) 
Region of residence, weighted % (95% CI) 
 Urban 46.05 (44.74–47.37) 46.93 (44.84–49.03) 46.90 (44.66–49.13) 46.94 (44.77–49.11) 46.64 (43.31–49.97) 45.25 (38.13–52.36) 45.67 (38.82–52.52) 44.38 (40.63–48.12) 
 Rural 53.95 (52.63–55.26) 53.07 (50.97–55.16) 53.10 (50.87–55.34) 53.06 (50.89–55.23) 53.36 (50.03–56.69) 54.75 (47.64–61.87) 54.33 (47.48–61.18) 55.62 (51.88–59.37) 
BMI, weighted % (95% CI)a 
 Underweight or normal 42.16 (41.66–42.66) 44.51 (43.58–45.44) 45.09 (44.08–46.09) 43.79 (42.94–44.63) 42.91 (42.02–43.81) 38.38 (36.84–39.92) 41.02 (39.25–42.80) 40.32 (38.64–42.00) 
 Overweight or obese 57.84 (57.34–58.34) 55.49 (54.56–56.42) 54.91 (53.91–55.92) 56.21 (55.37–57.06) 57.09 (56.19–57.98) 61.62 (60.08–63.16) 58.98 (57.20–60.75) 59.68 (58.00–61.36) 
Smoking status, weighted % (95% CI) 
 No 78.68 (78.22–79.14) 73.06 (72.21–73.91) 73.82 (72.91–74.73) 77.73 (76.96–78.50) 79.24 (78.38–80.10) 80.77 (79.28–82.26) 81.59 (80.17–83.01) 82.92 (81.36–84.48) 
 Yes 21.32 (20.86–21.78) 26.94 (26.09–27.79) 26.18 (25.27–27.09) 22.27 (21.50–23.04) 20.76 (19.90–21.62) 19.23 (17.74–20.72) 18.41 (16.99–19.83) 17.08 (15.52–18.64) 
Level of education, weighted % (95% CI) 
 High school or lower education 47.84 (47.03–48.66) 59.91 (58.37–61.44) 56.83 (55.33–58.32) 48.72 (47.43–50.01) 44.94 (43.28–46.60) 41.96 (38.99–44.93) 43.82 (40.97–46.68) 41.88 (39.55–44.20) 
 College or higher education 47.93 (47.07–48.78) 39.88 (38.33–41.42) 42.01 (40.50–43.51) 44.64 (43.33–45.96) 49.70 (47.97–51.42) 50.63 (47.40–53.85) 50.96 (47.94–53.98) 55.35 (52.81–57.88) 
 Unknown 4.23 (3.96–4.50) 0.22 (0.14–0.30) 1.16 (0.93–1.40) 6.63 (6.07–7.19) 5.36 (4.79–5.94) 7.41 (6.16–8.67) 5.22 (4.25–6.19) 2.78 (2.24–3.31) 
Household income, weighted % (95% CI) 
 Lowest and second quartile 39.36 (38.45–40.26) 41.30 (39.53–43.07) 43.43 (41.88–44.98) 40.38 (38.88–41.88) 39.98 (38.21–41.75) 36.72 (33.24–40.19) 36.54 (33.25–39.82) 38.09 (35.43–40.75) 
 Third and highest quartile 60.64 (59.74–61.55) 58.70 (56.93–60.47) 56.57 (55.02–58.12) 59.62 (58.12–61.12) 60.02 (58.25–61.79) 63.28 (59.81–66.76) 63.46 (60.18–66.75) 61.91 (59.25–64.57) 

BMI, body mass index; CI, confidence interval; KNHANES, Korea National Health and Nutrition Examination Survey.

aAccording to Asian-Pacific guidelines, BMI is divided into four groups: underweight (<18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25.0 kg/m2).

Table 2 and Figure 1 show the sex-specific prevalence of AD, AR, and asthma data comparing the periods before and during the COVID-19 pandemic from 2007 to 2022. For AD, there was an observed increase in prevalence among females, from 3.0% (95% CI, 2.6–3.4) during 2007–2009 to 4.3% (95% CI, 3.4–5.3) in 2022. Males similarly exhibited an increase, from 2.7% (95% CI, 2.2–3.2) in 2007–2009 to 5.0% (95% CI, 3.9–6.1) in 2022. The difference in prevalence between males and females was most pronounced in the case of AR. The rate of females was from 12.9% (95% CI, 12.1–13.7) in 2007–2009 to 19.3% (95% CI, 17.3–21.3) in 2022, while for males, the rate was from 10.5% (95% CI, 9.7–11.4) in 2007–2009 to 15.6% (95% CI, 13.8–17.4) in 2022. As for asthma, the prevalence showed a stable trend in both sexes. Females exhibited similar prevalence rates from 3.2% (95% CI, 2.7–3.6) in 2007–2009 to 3.0% (95% CI, 2.3–3.7) in 2022. Males exhibited a marginal increase from 2.2% (95% CI, 1.8–2.6) in 2007–2009 to 2.6% (95% CI, 1.9–3.3) in 2022.

Table 2.

Sex-specific trends in the prevalence of allergic disease and β-coefficients before and during the COVID-19 pandemic (weighted % [95% CI]) among males and females, based on data obtained from the KNHANES

GroupBefore the pandemicDuring the pandemicTrends before the pandemic, β (95% CI)Trends in the pandemic, β (95% CI)βdiff between 2007–2019 and 2019–2022 (95% CI)
2007–20092010–20122013–20162017–2019202020212022
AD 
Overall 2.84 (2.51–3.17) 2.97 (2.60–3.34) 3.03 (2.74–3.32) 3.56 (3.21–3.92) 4.02 (3.36–4.68) 4.22 (3.53–4.90) 4.66 (3.92–5.40) 0.023 (0.007 to 0.038)** 0.033 (−0.006–0.071) 0.010 (−0.032 to 0.052) 
Sex 
 Male 2.68 (2.21–3.15) 2.92 (2.35–3.48) 3.19 (2.72–3.65) 3.59 (3.06–4.12) 3.94 (3.00–4.89) 3.84 (2.92–4.76) 5.01 (3.87–6.14) 0.030 (0.007 to 0.053)** 0.012 (−0.039 to 0.064) −0.018 (−0.074 to 0.038) 
 Female 3.00 (2.58–3.42) 3.03 (2.57–3.49) 2.88 (2.51–3.25) 3.54 (3.09–3.99) 4.10 (3.18–5.02) 4.59 (3.62–5.57) 4.32 (3.38–5.26) 0.015 (−0.004 to 0.035) 0.053 (0.000–0.106) 0.038 (−0.018 to 0.094) 
Age 
 Male 
  19–39 years 4.12 (3.23–5.00) 5.02 (3.84–6.20) 6.16 (5.12–7.19) 7.12 (5.92–8.33) 8.16 (5.87–10.46) 8.56 (6.24–10.87) 11.76 (8.97–14.54) 0.102 (0.054 to 0.149)*** 0.072 (−0.055 to 0.199) −0.030 (−0.166 to 0.106) 
  40–59 years 1.61 (1.06–2.16) 1.46 (0.82–2.10) 1.25 (0.84–1.65) 1.47 (0.97–1.96) 1.85 (0.88–2.82) 1.57 (0.69–2.45) 1.47 (0.57–2.37) −0.006 (−0.029 to 0.018) 0.005 (−0.045 to 0.055) 0.011 (−0.044 to 0.066) 
  ≥60 years 1.38 (0.79–1.97) 1.29 (0.77–1.82) 1.30 (0.87–1.72) 1.56 (0.95–2.17) 1.17 (0.51–1.82) 0.93 (0.32–1.55) 1.55 (0.58–2.51) 0.007 (−0.020 to 0.033) −0.031 (−0.074 to 0.012) −0.038 (−0.089 to 0.013) 
 Female 
  19–39 years 4.89 (4.02–5.76) 5.93 (4.89–6.96) 5.91 (5.00–6.81) 8.14 (6.90–9.38) 9.87 (7.58–12.16) 11.85 (9.17–14.52) 10.65 (7.98–13.31) 0.097 (0.050 to 0.144)*** 0.185 (0.040 to 0.331)* 0.088 (−0.065 to 0.241) 
  40–59 years 1.93 (1.42–2.45) 1.54 (1.04–2.04) 1.18 (0.84–1.53) 1.30 (0.93–1.66) 1.67 (0.73–2.62) 1.64 (0.68–2.59) 2.10 (1.18–3.02) −0.022 (−0.042 to −0.002)* 0.017 (−0.033 to 0.068) 0.039 (−0.015 to 0.093) 
  ≥60 years 1.22 (0.73–1.71) 0.67 (0.36–0.99) 1.32 (0.92–1.72) 1.19 (0.78–1.60) 0.88 (0.31–1.45) 0.75 (0.30–1.20) 0.75 (0.31–1.20) 0.006 (−0.013 to 0.026) −0.022 (−0.052 to 0.008) −0.028 (−0.064 to 0.008) 
Region of residence 
 Male 
  Urban 3.08 (2.29–3.87) 3.16 (2.31–4.01) 3.29 (2.59–3.99) 3.94 (3.11–4.77) 5.36 (3.66–7.07) 3.83 (2.46–5.19) 5.77 (3.95–7.58) 0.028 (−0.008 to 0.064) −0.005 (−0.083 to 0.072) −0.033 (−0.118 to 0.052) 
  Rural 2.34 (1.79–2.89) 2.71 (1.96–3.47) 3.09 (2.49–3.70) 3.29 (2.61–3.96) 2.81 (1.79–3.83) 3.84 (2.60–5.08) 4.43 (2.99–5.86) 0.032 (0.004 to 0.060)* 0.028 (−0.041 to 0.098) −0.004 (−0.079 to 0.071) 
 Female 
  Urban 3.14 (2.49–3.79) 3.09 (2.42–3.77) 2.80 (2.25–3.35) 3.66 (2.99–4.33) 4.75 (3.36–6.15) 4.30 (2.97–5.63) 5.34 (3.69–6.99) 0.013 (−0.016 to 0.043) 0.032 (−0.041 to 0.105) 0.019 (−0.060 to 0.098) 
  Rural 2.88 (2.34–3.41) 2.97 (2.34–3.60) 2.95 (2.46–3.45) 3.43 (2.82–4.04) 3.54 (2.34–4.73) 4.85 (3.44–6.25) 3.46 (2.50–4.43) 0.017 (−0.009 to 0.043) 0.071 (−0.006 to 0.147) 0.054 (−0.027 to 0.135) 
BMIa 
 Male 
  Underweight or normal 2.44 (1.72–3.17) 3.27 (2.40–4.15) 3.20 (2.46–3.95) 3.48 (2.64–4.32) 5.29 (3.10–7.48) 3.94 (2.43–5.46) 5.87 (3.69–8.04) 0.030 (−0.005 to 0.065) 0.025 (−0.060 to 0.111) −0.005 (−0.097 to 0.087) 
  Overweight or obese 2.83 (2.22–3.43) 2.69 (1.99–3.39) 3.18 (2.62–3.74) 3.64 (2.98–4.31) 3.46 (2.44–4.47) 3.79 (2.69–4.89) 4.63 (3.36–5.90) 0.030 (0.001 to 0.059)* 0.008 (−0.056 to 0.071) −0.022 (−0.092 to 0.048) 
 Female 
  Underweight or normal 3.50 (2.89–4.11) 3.86 (3.14–4.58) 3.61 (3.03–4.18) 4.57 (3.86–5.29) 4.58 (3.21–5.95) 5.47 (4.07–6.87) 5.45 (4.02–6.87) 0.030 (0.001 to 0.060)* 0.045 (−0.033 to 0.123) 0.015 (−0.069 to 0.099) 
  Overweight or obese 2.47 (1.93–3.01) 2.16 (1.65–2.66) 2.10 (1.69–2.51) 2.39 (1.85–2.93) 3.62 (2.35–4.88) 3.63 (2.28–4.99) 3.17 (2.08–4.27) −0.003 (−0.026 to 0.021) 0.062 (−0.010 to 0.134) 0.065 (−0.011 to 0.141) 
Smoking status 
 Male 
  Non-smoker 2.55 (1.94–3.17) 3.36 (2.54–4.18) 3.32 (2.74–3.89) 3.64 (3.02–4.26) 3.71 (2.71–4.71) 3.69 (2.60–4.78) 4.49 (3.20–5.77) 0.031 (0.003 to 0.060)* 0.002 (−0.060 to 0.064) −0.029 (−0.097 to 0.039) 
  Smoker 2.83 (2.13–3.53) 2.40 (1.72–3.08) 2.98 (2.29–3.68) 3.49 (2.59–4.39) 4.42 (2.47–6.36) 4.16 (2.45–5.88) 6.25 (3.74–8.75) 0.025 (−0.010 to 0.060) 0.035 (−0.059 to 0.129) 0.010 (−0.090 to 0.110) 
 Female 
  Non-smoker 2.94 (2.51–3.37) 2.73 (2.28–3.17) 2.79 (2.42–3.16) 3.39 (2.94–3.84) 3.82 (2.88–4.75) 4.50 (3.52–5.49) 4.02 (3.14–4.90) 0.015 (−0.005–0.035) 0.055 (0.002 to 0.109)* 0.040 (−0.017 to 0.097) 
  Smoker 3.83 (2.11–5.56) 6.97 (4.32–9.61) 4.35 (2.55–6.16) 5.86 (3.28–8.45) 8.90 (3.10–14.69) 6.05 (2.14–9.96) 10.21 (4.17–16.26) 0.035 (−0.064 to 0.134) 0.008 (−0.228 to 0.243) −0.027 (−0.282 to 0.228) 
Education level 
 Male 
  High school or lower education 2.09 (1.57–2.62) 1.90 (1.32–2.48) 2.04 (1.53–2.54) 2.02 (1.46–2.59) 2.50 (1.08–3.92) 2.16 (1.16–3.16) 3.46 (2.00–4.93) −0.001 (−0.025 to 0.023) 0.006 (−0.051–0.064) 0.007 (−0.055–0.069) 
  College or higher education 3.35 (2.59–4.10) 4.03 (3.06–5.00) 4.57 (3.77–5.37) 5.05 (4.21–5.89) 5.41 (4.05–6.76) 5.42 (3.90–6.94) 6.16 (4.55–7.77) 0.056 (0.020 to 0.093)** 0.018 (−0.066 to 0.103) −0.038 (−0.130 to 0.054) 
 Female 
  High school or lower education 1.88 (1.50–2.26) 1.59 (1.18–2.01) 1.46 (1.15–1.76) 2.02 (1.56–2.49) 1.68 (0.91–2.45) 2.10 (1.33–2.87) 1.68 (0.92–2.45) 0.002 (−0.017 to 0.021) 0.003 (−0.041 to 0.048) 0.001 (−0.047 to 0.049) 
  College or higher education 5.36 (4.34–6.38) 5.68 (4.67–6.68) 5.35 (4.54–6.17) 5.66 (4.79–6.53) 7.16 (5.37–8.95) 7.64 (5.82–9.46) 7.03 (5.39–8.68) 0.006 (−0.036 to 0.048) 0.098 (−0.002 to 0.199) 0.092 (−0.017 to 0.201) 
Household income 
 Male 
  Lowest and second quartile 2.32 (1.64–3.00) 3.03 (2.12–3.94) 2.74 (2.07–3.41) 3.64 (2.81–4.48) 4.62 (2.83–6.42) 3.68 (2.25–5.11) 5.78 (3.77–7.79) 0.037 (0.002 to 0.071)* 0.003 (−0.079 to 0.084) −0.034 (−0.123 to 0.055) 
  Third and highest quartile 2.92 (2.30–3.53) 2.84 (2.14–3.54) 3.45 (2.87–4.04) 3.56 (2.90–4.21) 3.58 (2.51–4.65) 3.92 (2.72–5.11) 4.60 (3.18–6.02) 0.025 (−0.003–0.054) 0.018 (−0.049 to 0.085) −0.007 (−0.080 to 0.066) 
 Female 
  Lowest and second quartile 2.85 (2.25–3.46) 2.43 (1.84–3.02) 2.43 (1.95–2.91) 2.99 (2.32–3.66) 2.75 (1.68–3.83) 3.40 (2.14–4.66) 3.53 (2.32–4.74) 0.005 (−0.023 to 0.033) 0.020 (−0.050 to 0.090) 0.015 (−0.060 to 0.090) 
  Third and highest quartile 3.12 (2.54–3.70) 3.54 (2.85–4.22) 3.22 (2.69–3.74) 3.96 (3.34–4.57) 4.95 (3.64–6.26) 5.38 (4.07–6.69) 4.88 (3.57–6.20) 0.022 (−0.004 to 0.049) 0.071 (−0.001 to 0.143) 0.049 (−0.028 to 0.126) 
AR 
Overall 11.71 (11.07–12.36) N/A 13.99 (13.40–14.58) 15.01 (14.32–15.69) 15.77 (14.62–16.93) 16.15 (14.87–17.44) 17.44 (15.97–18.90) 0.110 (0.080 to 0.141)*** 0.057 (−0.015 to 0.130) −0.053 (−0.132 to 0.026) 
Sex 
 Male 10.53 (9.67–11.39) N/A 12.13 (11.30–12.96) 12.90 (12.04–13.76) 12.89 (11.32–14.45) 14.74 (12.96–16.52) 15.56 (13.76–17.36) 0.079 (0.040 to 0.119)*** 0.092 (−0.006 to 0.191) 0.013 (−0.093 to 0.119) 
 Female 12.88 (12.05–13.70) N/A 15.79 (15.00–16.58) 17.09 (16.13–18.06) 18.65 (17.01–20.30) 17.56 (15.92–19.20) 19.30 (17.33–21.28) 0.141 (0.100 to 0.182)*** 0.023 (−0.071 to 0.117) −0.118 (−0.221 to −0.015)* 
Age 
 Male 
  19–39 years 14.09 (12.56–15.63) N/A 17.80 (16.26–19.33) 19.56 (17.90–21.22) 19.00 (15.70–22.30) 22.86 (19.01–26.72) 23.88 (19.98–27.79) 0.183 (0.110 to 0.256)*** 0.163 (−0.041 to 0.368) −0.020 (−0.237 to 0.197) 
  40–59 years 8.84 (7.69–9.98) N/A 9.53 (8.43–10.63) 10.74 (9.52–11.97) 11.60 (9.16–14.04) 12.35 (10.05–14.66) 13.41 (10.93–15.88) 0.061 (0.006 to 0.115)* 0.080 (−0.049 to 0.210) 0.019 (−0.122 to 0.160) 
  ≥60 years 4.88 (3.82–5.95) N/A 6.27 (5.29–7.24) 5.81 (4.86–6.76) 6.05 (4.36–7.75) 7.45 (5.32–9.57) 8.11 (6.15–10.07) 0.033 (−0.015 to 0.080) 0.083 (−0.033 to 0.200) 0.050 (−0.076 to 0.176) 
 Female 
  19–39 years 18.96 (17.39–20.52) N/A 23.80 (22.21–25.38) 25.62 (23.75–27.49) 28.35 (25.10–31.59) 23.55 (19.81–27.28) 27.42 (23.62–31.22) 0.225 (0.147 to 0.303)*** −0.102 (−0.307 to 0.103) −0.327 (−0.546 to −0.108)* 
  40–59 years 10.95 (9.76–12.14) N/A 14.55 (13.41–15.69) 16.33 (14.97–17.68) 18.63 (16.00–21.27) 19.18 (16.32–22.05) 20.89 (17.78–24.00) 0.179 (0.121 to 0.238)*** 0.143 (−0.012 to 0.298) −0.036 (−0.202 to 0.130) 
  ≥60 years 4.36 (3.41–5.30) N/A 6.39 (5.56–7.21) 7.86 (6.83–8.89) 7.84 (6.04–9.64) 9.34 (7.51–11.17) 9.47 (7.54–11.39) 0.116 (0.070 to 0.162)*** 0.076 (−0.030 to 0.182) −0.040 (−0.156 to 0.076) 
Region of residence 
 Male 
  Urban 11.12 (9.86–12.38) N/A 12.85 (11.59–14.11) 13.22 (11.91–14.53) 12.86 (10.27–15.45) 14.96 (12.23–17.69) 15.96 (13.29–18.62) 0.072 (0.013 to 0.131)* 0.087 (−0.066 to 0.239) 0.015 (−0.149 to 0.179) 
  Rural 10.01 (8.84–11.18) N/A 11.51 (10.40–12.61) 12.63 (11.48–13.77) 12.91 (10.98–14.84) 14.56 (12.24–16.89) 15.25 (12.87–17.63) 0.086 (0.032 to 0.140)** 0.097 (−0.031 to 0.226) 0.011 (−0.128 to 0.150) 
 Female 
  Urban 13.05 (11.82–14.28) N/A 16.26 (15.13–17.40) 17.29 (15.88–18.69) 18.44 (16.02–20.86) 19.07 (16.71–21.43) 18.99 (16.32–21.67) 0.143 (0.083 to 0.203)*** 0.089 (−0.046 to 0.224) −0.054 (−0.202 to 0.094) 
  Rural 12.72 (11.61–13.83) N/A 15.35 (14.25–16.45) 16.92 (15.59–18.26) 18.84 (16.57–21.11) 16.26 (13.94–18.58) 19.56 (16.68–22.44) 0.139 (0.083 to 0.195)*** −0.034 (−0.166 to 0.098) −0.173 (−0.316 to −0.030)* 
BMIa 
 Male 
  Underweight or normal 10.38 (9.01–11.75) N/A 12.31 (10.98–13.65) 13.24 (11.68–14.80) 12.64 (9.75–15.53) 12.24 (9.51–14.97) 15.59 (12.27–18.90) 0.095 (0.029 to 0.162)** −0.050 (−0.206 to 0.106) −0.145 (−0.315 to 0.025) 
  Overweight or obese 10.62 (9.50–11.73) N/A 12.03 (10.98–13.07) 12.74 (11.66–13.81) 12.98 (11.21–14.74) 15.80 (13.63–17.97) 15.55 (13.35–17.74) 0.071 (0.020 to 0.121)** 0.155 (0.033 to 0.276)* 0.084 (−0.048 to 0.216) 
 Female 
  Underweight or normal 14.58 (13.34–15.82) N/A 17.91 (16.73–19.08) 19.22 (17.87–20.57) 21.16 (18.83–23.49) 19.45 (17.06–21.85) 21.11 (18.50–23.72) 0.156 (0.097 to 0.215)*** 0.011 (−0.122 to 0.145) −0.145 (−0.291 to 0.001) 
  Overweight or obese 11.08 (9.94–12.21) N/A 13.51 (12.54–14.49) 14.73 (13.57–15.89) 16.12 (13.91–18.33) 15.48 (13.41–17.56) 17.47 (15.02–19.93) 0.122 (0.069 to 0.175)*** 0.037 (−0.081 to 0.156) −0.085 (−0.215 to 0.045) 
Smoking status 
 Male 
  Non-smoker 11.52 (10.26–12.77) N/A 12.61 (11.52–13.70) 14.12 (12.99–15.25) 13.53 (11.51–15.54) 15.30 (12.99–17.61) 16.28 (14.01–18.56) 0.084 (0.029 to 0.140)** 0.061 (−0.067 to 0.188) −0.023 (−0.162 to 0.116) 
  Smoker 9.42 (8.25–10.60) N/A 11.39 (10.13–12.64) 10.71 (9.35–12.07) 11.58 (8.96–14.20) 13.49 (10.46–16.52) 13.82 (10.36–17.28) 0.052 (−0.006 to 0.109) 0.138 (−0.025 to 0.301) 0.086 (−0.087 to 0.259) 
 Female 
  Non-smoker 13.05 (12.19–13.91) N/A 15.71 (14.89–16.52) 16.65 (15.67–17.63) 18.37 (16.63–20.10) 17.34 (15.64–19.03) 19.11 (17.00–21.22) 0.122 (0.080 to 0.164)*** 0.034 (−0.064 to 0.132) −0.088 (−0.195 to 0.019) 
  Smoker 10.57 (7.67–13.47) N/A 17.07 (13.84–20.30) 24.09 (19.78–28.40) 23.48 (15.69–31.28) 21.00 (12.71–29.30) 23.24 (14.13–32.34) 0.433 (0.271 to 0.596)*** −0.155 (−0.624 to 0.314) −0.588 (−1.084 to −0.092)* 
Education level 
 Male 
  High school or lower education 7.42 (6.38–8.45) N/A 8.19 (7.17–9.20) 8.46 (7.36–9.57) 9.53 (7.60–11.47) 11.28 (8.83–13.73) 9.92 (7.63–12.20) 0.036 (−0.013–0.085) 0.141 (0.008 to 0.274)* 0.105 (−0.037 to 0.247) 
  College or higher education 14.00 (12.52–15.48) N/A 17.07 (15.76–18.39) 17.37 (16.06–18.69) 16.76 (14.38–19.13) 18.65 (16.04–21.26) 19.67 (17.04–22.29) 0.116 (0.051 to 0.181)** 0.064 (−0.082 to 0.210) −0.052 (−0.212 to 0.108) 
 Female 
  High school or lower education 9.66 (8.83–10.49) N/A 12.08 (11.15–13.00) 12.57 (11.49–13.65) 14.85 (12.80–16.89) 14.23 (12.04–16.42) 13.90 (11.67–16.14) 0.101 (0.058 to 0.144)*** 0.084 (−0.038 to 0.206) −0.017 (−0.146 to 0.112) 
  College or higher education 19.65 (17.92–21.39) N/A 23.42 (21.93–24.91) 24.15 (22.58–25.73) 25.58 (22.96–28.20) 22.83 (19.85–25.82) 25.33 (22.53–28.13) 0.152 (0.075 to 0.229)*** −0.069 (−0.238 to 0.101) −0.221 (−0.407 to −0.035)* 
Household income 
 Male 
  Lowest and second quartile 8.33 (7.03–9.63) N/A 10.53 (9.27–11.79) 11.67 (10.32–13.02) 10.31 (8.09–12.53) 11.17 (8.64–13.69) 11.45 (8.66–14.24) 0.111 (0.050 to 0.172)*** −0.026 (−0.170 to 0.117) −0.137 (−0.293 to 0.019) 
  Third and highest quartile 11.94 (10.84–13.04) N/A 13.10 (12.00–14.19) 13.62 (12.50–14.75) 14.26 (12.20–16.31) 16.53 (14.11–18.95) 17.70 (15.45–19.95) 0.056 (0.005 to 0.108)* 0.146 (0.015 to 0.278)* 0.090 (−0.051 to 0.231) 
 Female 
  Lowest and second quartile 10.77 (9.67–11.87) N/A 13.57 (12.43–14.71) 14.94 (13.57–16.31) 13.75 (11.38–16.13) 13.75 (11.45–16.05) 16.60 (14.23–18.97) 0.139 (0.083 to 0.195)*** −0.060 (−0.193 to 0.073) −0.199 (−0.343 to −0.055)* 
  Third and highest quartile 14.49 (13.37–15.62) N/A 17.45 (16.38–18.52) 18.72 (17.48–19.97) 21.75 (19.45–24.06) 20.06 (17.63–22.49) 21.25 (18.61–23.89) 0.142 (0.087 to 0.196)*** 0.064 (−0.072 to 0.199) −0.078 (−0.224 to 0.068) 
Asthma 
Overall 2.67 (2.39–2.95) 2.97 (2.64–3.31) 2.75 (2.50–3.01) 2.98 (2.67–3.29) 2.87 (2.32–3.43) 3.06 (2.50–3.62) 2.81 (2.31–3.30) 0.007 (−0.006 to 0.020) 0.004 (−0.028 to 0.035) −0.003 (−0.037 to 0.031) 
Sex 
 Male 2.19 (1.82–2.55) 2.70 (2.21–3.19) 2.17 (1.82–2.52) 3.01 (2.56–3.47) 2.94 (2.12–3.76) 2.42 (1.72–3.13) 2.62 (1.91–3.33) 0.020 (0.002–0.039)* −0.030 (−0.071 to 0.012) −0.050 (−0.095 to −0.005)* 
 Female 3.15 (2.72–3.57) 3.24 (2.79–3.68) 3.31 (2.95–3.68) 2.95 (2.57–3.33) 2.80 (2.07–3.53) 3.69 (2.83–4.55) 2.99 (2.31–3.67) −0.006 (−0.024 to 0.012) 0.037 (−0.009 to 0.083) 0.043 (−0.006 to 0.092) 
Age 
 Male 
  19–39 years 1.71 (1.13–2.30) 3.11 (2.22–4.00) 2.80 (2.09–3.51) 4.52 (3.53–5.52) 4.46 (2.69–6.23) 3.18 (1.66–4.69) 3.40 (1.81–5.00) 0.081 (0.045 to 0.118)*** −0.067 (−0.158 to 0.024) −0.148 (−0.246 to −0.050)* 
  40–59 years 1.81 (1.31–2.32) 1.58 (1.01–2.15) 1.29 (0.86–1.71) 1.30 (0.85–1.75) 1.55 (0.59–2.51) 1.73 (0.77–2.70) 1.78 (0.84–2.71) −0.018 (−0.039 to 0.003) 0.022 (−0.031 to 0.074) 0.040 (−0.017 to 0.097) 
  ≥60 years 4.39 (3.44–5.34) 4.31 (3.39–5.23) 2.76 (2.13–3.40) 3.59 (2.71–4.47) 2.96 (1.70–4.23) 2.46 (1.25–3.67) 2.85 (1.64–4.05) −0.036 (−0.076 to 0.005) −0.056 (−0.131 to 0.018) −0.020 (−0.105 to 0.065) 
 Female 
  19–39 years 2.03 (1.46–2.60) 2.30 (1.65–2.94) 2.90 (2.25–3.56) 2.87 (2.10–3.65) 2.96 (1.37–4.55) 3.44 (1.93–4.94) 2.91 (1.71–4.11) 0.031 (0.001 to 0.061)* 0.028 (−0.055 to 0.111) −0.003 (−0.091 to 0.085) 
  40–59 years 2.65 (2.02–3.29) 2.79 (2.09–3.48) 2.23 (1.76–2.70) 2.20 (1.68–2.72) 1.79 (0.79–2.79) 2.23 (1.20–3.27) 2.02 (1.19–2.85) −0.019 (−0.045 to 0.007) 0.002 (−0.056 to 0.059) 0.021 (−0.042 to 0.084) 
  ≥60 years 6.28 (5.24–7.31) 5.64 (4.63–6.65) 5.65 (4.81–6.49) 4.13 (3.38–4.88) 3.98 (2.74–5.23) 5.75 (4.10–7.39) 4.23 (2.80–5.66) −0.067 (−0.107 to −0.027)** 0.083 (−0.007 to 0.174) 0.150 (0.051–0.249)* 
Region of residence 
 Male 
  Urban 2.35 (1.77–2.92) 2.78 (2.07–3.49) 1.88 (1.39–2.36) 2.87 (2.22–3.53) 2.92 (1.72–4.13) 2.67 (1.52–3.83) 2.61 (1.59–3.63) 0.008 (−0.020 to 0.035) −0.010 (−0.076 to 0.056) −0.018 (−0.090 to 0.054) 
  Rural 2.04 (1.59–2.49) 2.63 (1.96–3.30) 2.43 (1.93–2.93) 3.14 (2.50–3.77) 2.96 (1.82–4.09) 2.22 (1.36–3.08) 2.63 (1.64–3.61) 0.031 (0.006 to 0.056)* −0.046 (−0.099 to 0.007) −0.077 (−0.136 to −0.018)* 
 Female 
  Urban 3.40 (2.72–4.07) 3.46 (2.78–4.15) 3.27 (2.75–3.79) 3.08 (2.48–3.68) 2.51 (1.40–3.62) 3.45 (2.34–4.56) 3.09 (2.00–4.19) −0.012 (−0.040 to 0.017) 0.019 (−0.043 to 0.080) 0.031 (−0.037 to 0.099) 
  Rural 2.93 (2.39–3.46) 3.03 (2.45–3.62) 3.35 (2.84–3.86) 2.84 (2.37–3.31) 3.06 (2.10–4.01) 3.89 (2.60–5.18) 2.91 (2.03–3.79) 0.001 (−0.023 to 0.022) 0.053 (−0.015 to 0.121) 0.053 (−0.019 to 0.125) 
BMIa 
 Male 
  Underweight or normal 2.27 (1.64–2.89) 2.77 (2.03–3.50) 2.32 (1.72–2.93) 3.27 (2.47–4.07) 2.09 (0.88–3.30) 2.13 (1.08–3.18) 3.19 (1.75–4.62) 0.026 (−0.006 to 0.058) −0.058 (−0.124 to 0.008) −0.084 (−0.157 to −0.011)* 
  Overweight or obese 2.14 (1.68–2.59) 2.66 (2.04–3.28) 2.09 (1.66–2.52) 2.89 (2.34–3.43) 3.25 (2.22–4.27) 2.55 (1.63–3.47) 2.37 (1.58–3.17) 0.018 (−0.005 to 0.041) −0.017 (−0.071 to 0.036) −0.035 (−0.093 to 0.023) 
 Female 
  Underweight or normal 2.23 (1.72–2.75) 2.53 (1.98–3.07) 2.61 (2.14–3.09) 2.64 (2.12–3.15) 2.52 (1.61–3.44) 3.19 (2.08–4.30) 2.01 (1.24–2.78) 0.013 (−0.010 to 0.036) 0.028 (−0.033 to 0.088) 0.015 (−0.050 to 0.080) 
  Overweight or obese 4.11 (3.47–4.76) 3.98 (3.27–4.69) 4.06 (3.52–4.60) 3.30 (2.74–3.86) 3.09 (2.06–4.12) 4.23 (3.11–5.35) 3.99 (2.87–5.11) −0.024 (−0.051 to 0.003) 0.047 (−0.015 to 0.109) 0.071 (0.003–0.139)* 
Smoking status 
 Male 
  Non-smoker 2.64 (2.09–3.19) 2.80 (2.16–3.45) 2.21 (1.79–2.63) 3.01 (2.44–3.57) 3.27 (2.26–4.29) 2.32 (1.49–3.15) 2.75 (1.89–3.61) 0.007 (−0.018 to 0.032) −0.035 (−0.085 to 0.015) −0.042 (−0.098 to 0.014) 
  Smoker 1.68 (1.21–2.15) 2.58 (1.82–3.34) 2.12 (1.53–2.71) 3.03 (2.18–3.87) 2.26 (0.96–3.56) 2.65 (1.34–3.96) 2.32 (1.14–3.49) 0.036 (0.006 to 0.066)* −0.020 (−0.097 to 0.057) −0.056 (−0.139 to 0.027) 
 Female 
  Non-smoker 2.95 (2.52–3.37) 3.26 (2.80–3.71) 3.23 (2.86–3.60) 2.87 (2.49–3.25) 2.39 (1.74–3.03) 3.71 (2.81–4.61) 3.01 (2.30–3.72) −0.003 (−0.021 to 0.015) 0.042 (−0.006 to 0.091) 0.045 (−0.007 to 0.097) 
  Smoker 5.82 (3.60–8.04) 2.96 (1.23–4.69) 4.59 (2.68–6.50) 4.22 (2.46–5.98) 9.91 (4.81–15.01) 3.30 (0.83–5.77) 2.66 (0.31–5.02) −0.031 (−0.120 to 0.057) −0.050 (−0.207 to 0.108) −0.019 (−0.200 to 0.162) 
Education level 
 Male 
  High school or lower education 2.61 (2.13–3.09) 2.80 (2.18–3.42) 2.10 (1.61–2.59) 2.58 (1.96–3.20) 3.50 (2.23–4.76) 2.03 (1.12–2.94) 2.69 (1.58–3.81) −0.008 (−0.033 to 0.016) −0.028 (−0.083 to 0.026) −0.020 (−0.080 to 0.040) 
  College or higher education 1.73 (1.19–2.28) 2.64 (1.93–3.36) 2.48 (1.92–3.04) 3.60 (2.88–4.33) 2.93 (1.76–4.09) 2.94 (1.84–4.04) 2.69 (1.74–3.64) 0.055 (0.026 to 0.085)*** −0.033 (−0.099 to 0.033) −0.088 (−0.160 to −0.016)* 
 Female 
  High school or lower education 3.64 (3.14–4.14) 3.91 (3.29–4.53) 4.12 (3.60–4.64) 3.23 (2.71–3.75) 3.74 (2.61–4.87) 4.08 (3.08–5.09) 3.56 (2.28–4.83) −0.009 (−0.032 to 0.014) 0.043 (−0.013 to 0.098) 0.052 (−0.008 to 0.112) 
  College or higher education 2.14 (1.48–2.79) 2.11 (1.50–2.73) 2.65 (2.05–3.25) 2.94 (2.31–3.56) 2.35 (1.22–3.47) 3.68 (2.21–5.15) 2.64 (1.80–3.47) 0.030 (0.002–0.059)* 0.038 (−0.041 to 0.118) 0.008 (−0.076 to 0.092) 
Household income 
 Male 
  Lowest and second quartile 2.99 (2.33–3.64) 3.16 (2.38–3.93) 2.13 (1.61–2.65) 3.83 (3.10–4.56) 3.61 (2.25–4.97) 2.19 (1.24–3.13) 3.16 (1.85–4.46) 0.016 (−0.015 to 0.047) −0.081 (−0.142 to −0.021)* −0.097 (−0.165 to −0.029)* 
  Third and highest quartile 1.67 (1.25–2.09) 2.39 (1.74–3.03) 2.20 (1.72–2.67) 2.54 (1.99–3.09) 2.59 (1.62–3.55) 2.54 (1.62–3.47) 2.34 (1.48–3.19) 0.024 (0.002 to 0.047)* 0.001 (−0.054 to 0.054) −0.024 (−0.083 to 0.035) 
 Female 
  Lowest and second quartile 3.94 (3.32–4.56) 3.69 (3.03–4.35) 4.03 (3.43–4.63) 3.28 (2.68–3.88) 3.81 (2.61–5.01) 4.67 (3.40–5.94) 2.77 (1.79–3.76) −0.017 (−0.044 to 0.010) 0.070 (0.000–0.139) 0.087 (0.012–0.162)* 
  Third and highest quartile 2.54 (2.01–3.06) 2.85 (2.29–3.41) 2.77 (2.31–3.23) 2.70 (2.19–3.21) 2.17 (1.38–2.95) 3.04 (2.05–4.03) 3.15 (2.25–4.05) 0.004 (−0.019 to 0.027) 0.018 (−0.037 to 0.073) 0.014 (−0.046 to 0.074) 
GroupBefore the pandemicDuring the pandemicTrends before the pandemic, β (95% CI)Trends in the pandemic, β (95% CI)βdiff between 2007–2019 and 2019–2022 (95% CI)
2007–20092010–20122013–20162017–2019202020212022
AD 
Overall 2.84 (2.51–3.17) 2.97 (2.60–3.34) 3.03 (2.74–3.32) 3.56 (3.21–3.92) 4.02 (3.36–4.68) 4.22 (3.53–4.90) 4.66 (3.92–5.40) 0.023 (0.007 to 0.038)** 0.033 (−0.006–0.071) 0.010 (−0.032 to 0.052) 
Sex 
 Male 2.68 (2.21–3.15) 2.92 (2.35–3.48) 3.19 (2.72–3.65) 3.59 (3.06–4.12) 3.94 (3.00–4.89) 3.84 (2.92–4.76) 5.01 (3.87–6.14) 0.030 (0.007 to 0.053)** 0.012 (−0.039 to 0.064) −0.018 (−0.074 to 0.038) 
 Female 3.00 (2.58–3.42) 3.03 (2.57–3.49) 2.88 (2.51–3.25) 3.54 (3.09–3.99) 4.10 (3.18–5.02) 4.59 (3.62–5.57) 4.32 (3.38–5.26) 0.015 (−0.004 to 0.035) 0.053 (0.000–0.106) 0.038 (−0.018 to 0.094) 
Age 
 Male 
  19–39 years 4.12 (3.23–5.00) 5.02 (3.84–6.20) 6.16 (5.12–7.19) 7.12 (5.92–8.33) 8.16 (5.87–10.46) 8.56 (6.24–10.87) 11.76 (8.97–14.54) 0.102 (0.054 to 0.149)*** 0.072 (−0.055 to 0.199) −0.030 (−0.166 to 0.106) 
  40–59 years 1.61 (1.06–2.16) 1.46 (0.82–2.10) 1.25 (0.84–1.65) 1.47 (0.97–1.96) 1.85 (0.88–2.82) 1.57 (0.69–2.45) 1.47 (0.57–2.37) −0.006 (−0.029 to 0.018) 0.005 (−0.045 to 0.055) 0.011 (−0.044 to 0.066) 
  ≥60 years 1.38 (0.79–1.97) 1.29 (0.77–1.82) 1.30 (0.87–1.72) 1.56 (0.95–2.17) 1.17 (0.51–1.82) 0.93 (0.32–1.55) 1.55 (0.58–2.51) 0.007 (−0.020 to 0.033) −0.031 (−0.074 to 0.012) −0.038 (−0.089 to 0.013) 
 Female 
  19–39 years 4.89 (4.02–5.76) 5.93 (4.89–6.96) 5.91 (5.00–6.81) 8.14 (6.90–9.38) 9.87 (7.58–12.16) 11.85 (9.17–14.52) 10.65 (7.98–13.31) 0.097 (0.050 to 0.144)*** 0.185 (0.040 to 0.331)* 0.088 (−0.065 to 0.241) 
  40–59 years 1.93 (1.42–2.45) 1.54 (1.04–2.04) 1.18 (0.84–1.53) 1.30 (0.93–1.66) 1.67 (0.73–2.62) 1.64 (0.68–2.59) 2.10 (1.18–3.02) −0.022 (−0.042 to −0.002)* 0.017 (−0.033 to 0.068) 0.039 (−0.015 to 0.093) 
  ≥60 years 1.22 (0.73–1.71) 0.67 (0.36–0.99) 1.32 (0.92–1.72) 1.19 (0.78–1.60) 0.88 (0.31–1.45) 0.75 (0.30–1.20) 0.75 (0.31–1.20) 0.006 (−0.013 to 0.026) −0.022 (−0.052 to 0.008) −0.028 (−0.064 to 0.008) 
Region of residence 
 Male 
  Urban 3.08 (2.29–3.87) 3.16 (2.31–4.01) 3.29 (2.59–3.99) 3.94 (3.11–4.77) 5.36 (3.66–7.07) 3.83 (2.46–5.19) 5.77 (3.95–7.58) 0.028 (−0.008 to 0.064) −0.005 (−0.083 to 0.072) −0.033 (−0.118 to 0.052) 
  Rural 2.34 (1.79–2.89) 2.71 (1.96–3.47) 3.09 (2.49–3.70) 3.29 (2.61–3.96) 2.81 (1.79–3.83) 3.84 (2.60–5.08) 4.43 (2.99–5.86) 0.032 (0.004 to 0.060)* 0.028 (−0.041 to 0.098) −0.004 (−0.079 to 0.071) 
 Female 
  Urban 3.14 (2.49–3.79) 3.09 (2.42–3.77) 2.80 (2.25–3.35) 3.66 (2.99–4.33) 4.75 (3.36–6.15) 4.30 (2.97–5.63) 5.34 (3.69–6.99) 0.013 (−0.016 to 0.043) 0.032 (−0.041 to 0.105) 0.019 (−0.060 to 0.098) 
  Rural 2.88 (2.34–3.41) 2.97 (2.34–3.60) 2.95 (2.46–3.45) 3.43 (2.82–4.04) 3.54 (2.34–4.73) 4.85 (3.44–6.25) 3.46 (2.50–4.43) 0.017 (−0.009 to 0.043) 0.071 (−0.006 to 0.147) 0.054 (−0.027 to 0.135) 
BMIa 
 Male 
  Underweight or normal 2.44 (1.72–3.17) 3.27 (2.40–4.15) 3.20 (2.46–3.95) 3.48 (2.64–4.32) 5.29 (3.10–7.48) 3.94 (2.43–5.46) 5.87 (3.69–8.04) 0.030 (−0.005 to 0.065) 0.025 (−0.060 to 0.111) −0.005 (−0.097 to 0.087) 
  Overweight or obese 2.83 (2.22–3.43) 2.69 (1.99–3.39) 3.18 (2.62–3.74) 3.64 (2.98–4.31) 3.46 (2.44–4.47) 3.79 (2.69–4.89) 4.63 (3.36–5.90) 0.030 (0.001 to 0.059)* 0.008 (−0.056 to 0.071) −0.022 (−0.092 to 0.048) 
 Female 
  Underweight or normal 3.50 (2.89–4.11) 3.86 (3.14–4.58) 3.61 (3.03–4.18) 4.57 (3.86–5.29) 4.58 (3.21–5.95) 5.47 (4.07–6.87) 5.45 (4.02–6.87) 0.030 (0.001 to 0.060)* 0.045 (−0.033 to 0.123) 0.015 (−0.069 to 0.099) 
  Overweight or obese 2.47 (1.93–3.01) 2.16 (1.65–2.66) 2.10 (1.69–2.51) 2.39 (1.85–2.93) 3.62 (2.35–4.88) 3.63 (2.28–4.99) 3.17 (2.08–4.27) −0.003 (−0.026 to 0.021) 0.062 (−0.010 to 0.134) 0.065 (−0.011 to 0.141) 
Smoking status 
 Male 
  Non-smoker 2.55 (1.94–3.17) 3.36 (2.54–4.18) 3.32 (2.74–3.89) 3.64 (3.02–4.26) 3.71 (2.71–4.71) 3.69 (2.60–4.78) 4.49 (3.20–5.77) 0.031 (0.003 to 0.060)* 0.002 (−0.060 to 0.064) −0.029 (−0.097 to 0.039) 
  Smoker 2.83 (2.13–3.53) 2.40 (1.72–3.08) 2.98 (2.29–3.68) 3.49 (2.59–4.39) 4.42 (2.47–6.36) 4.16 (2.45–5.88) 6.25 (3.74–8.75) 0.025 (−0.010 to 0.060) 0.035 (−0.059 to 0.129) 0.010 (−0.090 to 0.110) 
 Female 
  Non-smoker 2.94 (2.51–3.37) 2.73 (2.28–3.17) 2.79 (2.42–3.16) 3.39 (2.94–3.84) 3.82 (2.88–4.75) 4.50 (3.52–5.49) 4.02 (3.14–4.90) 0.015 (−0.005–0.035) 0.055 (0.002 to 0.109)* 0.040 (−0.017 to 0.097) 
  Smoker 3.83 (2.11–5.56) 6.97 (4.32–9.61) 4.35 (2.55–6.16) 5.86 (3.28–8.45) 8.90 (3.10–14.69) 6.05 (2.14–9.96) 10.21 (4.17–16.26) 0.035 (−0.064 to 0.134) 0.008 (−0.228 to 0.243) −0.027 (−0.282 to 0.228) 
Education level 
 Male 
  High school or lower education 2.09 (1.57–2.62) 1.90 (1.32–2.48) 2.04 (1.53–2.54) 2.02 (1.46–2.59) 2.50 (1.08–3.92) 2.16 (1.16–3.16) 3.46 (2.00–4.93) −0.001 (−0.025 to 0.023) 0.006 (−0.051–0.064) 0.007 (−0.055–0.069) 
  College or higher education 3.35 (2.59–4.10) 4.03 (3.06–5.00) 4.57 (3.77–5.37) 5.05 (4.21–5.89) 5.41 (4.05–6.76) 5.42 (3.90–6.94) 6.16 (4.55–7.77) 0.056 (0.020 to 0.093)** 0.018 (−0.066 to 0.103) −0.038 (−0.130 to 0.054) 
 Female 
  High school or lower education 1.88 (1.50–2.26) 1.59 (1.18–2.01) 1.46 (1.15–1.76) 2.02 (1.56–2.49) 1.68 (0.91–2.45) 2.10 (1.33–2.87) 1.68 (0.92–2.45) 0.002 (−0.017 to 0.021) 0.003 (−0.041 to 0.048) 0.001 (−0.047 to 0.049) 
  College or higher education 5.36 (4.34–6.38) 5.68 (4.67–6.68) 5.35 (4.54–6.17) 5.66 (4.79–6.53) 7.16 (5.37–8.95) 7.64 (5.82–9.46) 7.03 (5.39–8.68) 0.006 (−0.036 to 0.048) 0.098 (−0.002 to 0.199) 0.092 (−0.017 to 0.201) 
Household income 
 Male 
  Lowest and second quartile 2.32 (1.64–3.00) 3.03 (2.12–3.94) 2.74 (2.07–3.41) 3.64 (2.81–4.48) 4.62 (2.83–6.42) 3.68 (2.25–5.11) 5.78 (3.77–7.79) 0.037 (0.002 to 0.071)* 0.003 (−0.079 to 0.084) −0.034 (−0.123 to 0.055) 
  Third and highest quartile 2.92 (2.30–3.53) 2.84 (2.14–3.54) 3.45 (2.87–4.04) 3.56 (2.90–4.21) 3.58 (2.51–4.65) 3.92 (2.72–5.11) 4.60 (3.18–6.02) 0.025 (−0.003–0.054) 0.018 (−0.049 to 0.085) −0.007 (−0.080 to 0.066) 
 Female 
  Lowest and second quartile 2.85 (2.25–3.46) 2.43 (1.84–3.02) 2.43 (1.95–2.91) 2.99 (2.32–3.66) 2.75 (1.68–3.83) 3.40 (2.14–4.66) 3.53 (2.32–4.74) 0.005 (−0.023 to 0.033) 0.020 (−0.050 to 0.090) 0.015 (−0.060 to 0.090) 
  Third and highest quartile 3.12 (2.54–3.70) 3.54 (2.85–4.22) 3.22 (2.69–3.74) 3.96 (3.34–4.57) 4.95 (3.64–6.26) 5.38 (4.07–6.69) 4.88 (3.57–6.20) 0.022 (−0.004 to 0.049) 0.071 (−0.001 to 0.143) 0.049 (−0.028 to 0.126) 
AR 
Overall 11.71 (11.07–12.36) N/A 13.99 (13.40–14.58) 15.01 (14.32–15.69) 15.77 (14.62–16.93) 16.15 (14.87–17.44) 17.44 (15.97–18.90) 0.110 (0.080 to 0.141)*** 0.057 (−0.015 to 0.130) −0.053 (−0.132 to 0.026) 
Sex 
 Male 10.53 (9.67–11.39) N/A 12.13 (11.30–12.96) 12.90 (12.04–13.76) 12.89 (11.32–14.45) 14.74 (12.96–16.52) 15.56 (13.76–17.36) 0.079 (0.040 to 0.119)*** 0.092 (−0.006 to 0.191) 0.013 (−0.093 to 0.119) 
 Female 12.88 (12.05–13.70) N/A 15.79 (15.00–16.58) 17.09 (16.13–18.06) 18.65 (17.01–20.30) 17.56 (15.92–19.20) 19.30 (17.33–21.28) 0.141 (0.100 to 0.182)*** 0.023 (−0.071 to 0.117) −0.118 (−0.221 to −0.015)* 
Age 
 Male 
  19–39 years 14.09 (12.56–15.63) N/A 17.80 (16.26–19.33) 19.56 (17.90–21.22) 19.00 (15.70–22.30) 22.86 (19.01–26.72) 23.88 (19.98–27.79) 0.183 (0.110 to 0.256)*** 0.163 (−0.041 to 0.368) −0.020 (−0.237 to 0.197) 
  40–59 years 8.84 (7.69–9.98) N/A 9.53 (8.43–10.63) 10.74 (9.52–11.97) 11.60 (9.16–14.04) 12.35 (10.05–14.66) 13.41 (10.93–15.88) 0.061 (0.006 to 0.115)* 0.080 (−0.049 to 0.210) 0.019 (−0.122 to 0.160) 
  ≥60 years 4.88 (3.82–5.95) N/A 6.27 (5.29–7.24) 5.81 (4.86–6.76) 6.05 (4.36–7.75) 7.45 (5.32–9.57) 8.11 (6.15–10.07) 0.033 (−0.015 to 0.080) 0.083 (−0.033 to 0.200) 0.050 (−0.076 to 0.176) 
 Female 
  19–39 years 18.96 (17.39–20.52) N/A 23.80 (22.21–25.38) 25.62 (23.75–27.49) 28.35 (25.10–31.59) 23.55 (19.81–27.28) 27.42 (23.62–31.22) 0.225 (0.147 to 0.303)*** −0.102 (−0.307 to 0.103) −0.327 (−0.546 to −0.108)* 
  40–59 years 10.95 (9.76–12.14) N/A 14.55 (13.41–15.69) 16.33 (14.97–17.68) 18.63 (16.00–21.27) 19.18 (16.32–22.05) 20.89 (17.78–24.00) 0.179 (0.121 to 0.238)*** 0.143 (−0.012 to 0.298) −0.036 (−0.202 to 0.130) 
  ≥60 years 4.36 (3.41–5.30) N/A 6.39 (5.56–7.21) 7.86 (6.83–8.89) 7.84 (6.04–9.64) 9.34 (7.51–11.17) 9.47 (7.54–11.39) 0.116 (0.070 to 0.162)*** 0.076 (−0.030 to 0.182) −0.040 (−0.156 to 0.076) 
Region of residence 
 Male 
  Urban 11.12 (9.86–12.38) N/A 12.85 (11.59–14.11) 13.22 (11.91–14.53) 12.86 (10.27–15.45) 14.96 (12.23–17.69) 15.96 (13.29–18.62) 0.072 (0.013 to 0.131)* 0.087 (−0.066 to 0.239) 0.015 (−0.149 to 0.179) 
  Rural 10.01 (8.84–11.18) N/A 11.51 (10.40–12.61) 12.63 (11.48–13.77) 12.91 (10.98–14.84) 14.56 (12.24–16.89) 15.25 (12.87–17.63) 0.086 (0.032 to 0.140)** 0.097 (−0.031 to 0.226) 0.011 (−0.128 to 0.150) 
 Female 
  Urban 13.05 (11.82–14.28) N/A 16.26 (15.13–17.40) 17.29 (15.88–18.69) 18.44 (16.02–20.86) 19.07 (16.71–21.43) 18.99 (16.32–21.67) 0.143 (0.083 to 0.203)*** 0.089 (−0.046 to 0.224) −0.054 (−0.202 to 0.094) 
  Rural 12.72 (11.61–13.83) N/A 15.35 (14.25–16.45) 16.92 (15.59–18.26) 18.84 (16.57–21.11) 16.26 (13.94–18.58) 19.56 (16.68–22.44) 0.139 (0.083 to 0.195)*** −0.034 (−0.166 to 0.098) −0.173 (−0.316 to −0.030)* 
BMIa 
 Male 
  Underweight or normal 10.38 (9.01–11.75) N/A 12.31 (10.98–13.65) 13.24 (11.68–14.80) 12.64 (9.75–15.53) 12.24 (9.51–14.97) 15.59 (12.27–18.90) 0.095 (0.029 to 0.162)** −0.050 (−0.206 to 0.106) −0.145 (−0.315 to 0.025) 
  Overweight or obese 10.62 (9.50–11.73) N/A 12.03 (10.98–13.07) 12.74 (11.66–13.81) 12.98 (11.21–14.74) 15.80 (13.63–17.97) 15.55 (13.35–17.74) 0.071 (0.020 to 0.121)** 0.155 (0.033 to 0.276)* 0.084 (−0.048 to 0.216) 
 Female 
  Underweight or normal 14.58 (13.34–15.82) N/A 17.91 (16.73–19.08) 19.22 (17.87–20.57) 21.16 (18.83–23.49) 19.45 (17.06–21.85) 21.11 (18.50–23.72) 0.156 (0.097 to 0.215)*** 0.011 (−0.122 to 0.145) −0.145 (−0.291 to 0.001) 
  Overweight or obese 11.08 (9.94–12.21) N/A 13.51 (12.54–14.49) 14.73 (13.57–15.89) 16.12 (13.91–18.33) 15.48 (13.41–17.56) 17.47 (15.02–19.93) 0.122 (0.069 to 0.175)*** 0.037 (−0.081 to 0.156) −0.085 (−0.215 to 0.045) 
Smoking status 
 Male 
  Non-smoker 11.52 (10.26–12.77) N/A 12.61 (11.52–13.70) 14.12 (12.99–15.25) 13.53 (11.51–15.54) 15.30 (12.99–17.61) 16.28 (14.01–18.56) 0.084 (0.029 to 0.140)** 0.061 (−0.067 to 0.188) −0.023 (−0.162 to 0.116) 
  Smoker 9.42 (8.25–10.60) N/A 11.39 (10.13–12.64) 10.71 (9.35–12.07) 11.58 (8.96–14.20) 13.49 (10.46–16.52) 13.82 (10.36–17.28) 0.052 (−0.006 to 0.109) 0.138 (−0.025 to 0.301) 0.086 (−0.087 to 0.259) 
 Female 
  Non-smoker 13.05 (12.19–13.91) N/A 15.71 (14.89–16.52) 16.65 (15.67–17.63) 18.37 (16.63–20.10) 17.34 (15.64–19.03) 19.11 (17.00–21.22) 0.122 (0.080 to 0.164)*** 0.034 (−0.064 to 0.132) −0.088 (−0.195 to 0.019) 
  Smoker 10.57 (7.67–13.47) N/A 17.07 (13.84–20.30) 24.09 (19.78–28.40) 23.48 (15.69–31.28) 21.00 (12.71–29.30) 23.24 (14.13–32.34) 0.433 (0.271 to 0.596)*** −0.155 (−0.624 to 0.314) −0.588 (−1.084 to −0.092)* 
Education level 
 Male 
  High school or lower education 7.42 (6.38–8.45) N/A 8.19 (7.17–9.20) 8.46 (7.36–9.57) 9.53 (7.60–11.47) 11.28 (8.83–13.73) 9.92 (7.63–12.20) 0.036 (−0.013–0.085) 0.141 (0.008 to 0.274)* 0.105 (−0.037 to 0.247) 
  College or higher education 14.00 (12.52–15.48) N/A 17.07 (15.76–18.39) 17.37 (16.06–18.69) 16.76 (14.38–19.13) 18.65 (16.04–21.26) 19.67 (17.04–22.29) 0.116 (0.051 to 0.181)** 0.064 (−0.082 to 0.210) −0.052 (−0.212 to 0.108) 
 Female 
  High school or lower education 9.66 (8.83–10.49) N/A 12.08 (11.15–13.00) 12.57 (11.49–13.65) 14.85 (12.80–16.89) 14.23 (12.04–16.42) 13.90 (11.67–16.14) 0.101 (0.058 to 0.144)*** 0.084 (−0.038 to 0.206) −0.017 (−0.146 to 0.112) 
  College or higher education 19.65 (17.92–21.39) N/A 23.42 (21.93–24.91) 24.15 (22.58–25.73) 25.58 (22.96–28.20) 22.83 (19.85–25.82) 25.33 (22.53–28.13) 0.152 (0.075 to 0.229)*** −0.069 (−0.238 to 0.101) −0.221 (−0.407 to −0.035)* 
Household income 
 Male 
  Lowest and second quartile 8.33 (7.03–9.63) N/A 10.53 (9.27–11.79) 11.67 (10.32–13.02) 10.31 (8.09–12.53) 11.17 (8.64–13.69) 11.45 (8.66–14.24) 0.111 (0.050 to 0.172)*** −0.026 (−0.170 to 0.117) −0.137 (−0.293 to 0.019) 
  Third and highest quartile 11.94 (10.84–13.04) N/A 13.10 (12.00–14.19) 13.62 (12.50–14.75) 14.26 (12.20–16.31) 16.53 (14.11–18.95) 17.70 (15.45–19.95) 0.056 (0.005 to 0.108)* 0.146 (0.015 to 0.278)* 0.090 (−0.051 to 0.231) 
 Female 
  Lowest and second quartile 10.77 (9.67–11.87) N/A 13.57 (12.43–14.71) 14.94 (13.57–16.31) 13.75 (11.38–16.13) 13.75 (11.45–16.05) 16.60 (14.23–18.97) 0.139 (0.083 to 0.195)*** −0.060 (−0.193 to 0.073) −0.199 (−0.343 to −0.055)* 
  Third and highest quartile 14.49 (13.37–15.62) N/A 17.45 (16.38–18.52) 18.72 (17.48–19.97) 21.75 (19.45–24.06) 20.06 (17.63–22.49) 21.25 (18.61–23.89) 0.142 (0.087 to 0.196)*** 0.064 (−0.072 to 0.199) −0.078 (−0.224 to 0.068) 
Asthma 
Overall 2.67 (2.39–2.95) 2.97 (2.64–3.31) 2.75 (2.50–3.01) 2.98 (2.67–3.29) 2.87 (2.32–3.43) 3.06 (2.50–3.62) 2.81 (2.31–3.30) 0.007 (−0.006 to 0.020) 0.004 (−0.028 to 0.035) −0.003 (−0.037 to 0.031) 
Sex 
 Male 2.19 (1.82–2.55) 2.70 (2.21–3.19) 2.17 (1.82–2.52) 3.01 (2.56–3.47) 2.94 (2.12–3.76) 2.42 (1.72–3.13) 2.62 (1.91–3.33) 0.020 (0.002–0.039)* −0.030 (−0.071 to 0.012) −0.050 (−0.095 to −0.005)* 
 Female 3.15 (2.72–3.57) 3.24 (2.79–3.68) 3.31 (2.95–3.68) 2.95 (2.57–3.33) 2.80 (2.07–3.53) 3.69 (2.83–4.55) 2.99 (2.31–3.67) −0.006 (−0.024 to 0.012) 0.037 (−0.009 to 0.083) 0.043 (−0.006 to 0.092) 
Age 
 Male 
  19–39 years 1.71 (1.13–2.30) 3.11 (2.22–4.00) 2.80 (2.09–3.51) 4.52 (3.53–5.52) 4.46 (2.69–6.23) 3.18 (1.66–4.69) 3.40 (1.81–5.00) 0.081 (0.045 to 0.118)*** −0.067 (−0.158 to 0.024) −0.148 (−0.246 to −0.050)* 
  40–59 years 1.81 (1.31–2.32) 1.58 (1.01–2.15) 1.29 (0.86–1.71) 1.30 (0.85–1.75) 1.55 (0.59–2.51) 1.73 (0.77–2.70) 1.78 (0.84–2.71) −0.018 (−0.039 to 0.003) 0.022 (−0.031 to 0.074) 0.040 (−0.017 to 0.097) 
  ≥60 years 4.39 (3.44–5.34) 4.31 (3.39–5.23) 2.76 (2.13–3.40) 3.59 (2.71–4.47) 2.96 (1.70–4.23) 2.46 (1.25–3.67) 2.85 (1.64–4.05) −0.036 (−0.076 to 0.005) −0.056 (−0.131 to 0.018) −0.020 (−0.105 to 0.065) 
 Female 
  19–39 years 2.03 (1.46–2.60) 2.30 (1.65–2.94) 2.90 (2.25–3.56) 2.87 (2.10–3.65) 2.96 (1.37–4.55) 3.44 (1.93–4.94) 2.91 (1.71–4.11) 0.031 (0.001 to 0.061)* 0.028 (−0.055 to 0.111) −0.003 (−0.091 to 0.085) 
  40–59 years 2.65 (2.02–3.29) 2.79 (2.09–3.48) 2.23 (1.76–2.70) 2.20 (1.68–2.72) 1.79 (0.79–2.79) 2.23 (1.20–3.27) 2.02 (1.19–2.85) −0.019 (−0.045 to 0.007) 0.002 (−0.056 to 0.059) 0.021 (−0.042 to 0.084) 
  ≥60 years 6.28 (5.24–7.31) 5.64 (4.63–6.65) 5.65 (4.81–6.49) 4.13 (3.38–4.88) 3.98 (2.74–5.23) 5.75 (4.10–7.39) 4.23 (2.80–5.66) −0.067 (−0.107 to −0.027)** 0.083 (−0.007 to 0.174) 0.150 (0.051–0.249)* 
Region of residence 
 Male 
  Urban 2.35 (1.77–2.92) 2.78 (2.07–3.49) 1.88 (1.39–2.36) 2.87 (2.22–3.53) 2.92 (1.72–4.13) 2.67 (1.52–3.83) 2.61 (1.59–3.63) 0.008 (−0.020 to 0.035) −0.010 (−0.076 to 0.056) −0.018 (−0.090 to 0.054) 
  Rural 2.04 (1.59–2.49) 2.63 (1.96–3.30) 2.43 (1.93–2.93) 3.14 (2.50–3.77) 2.96 (1.82–4.09) 2.22 (1.36–3.08) 2.63 (1.64–3.61) 0.031 (0.006 to 0.056)* −0.046 (−0.099 to 0.007) −0.077 (−0.136 to −0.018)* 
 Female 
  Urban 3.40 (2.72–4.07) 3.46 (2.78–4.15) 3.27 (2.75–3.79) 3.08 (2.48–3.68) 2.51 (1.40–3.62) 3.45 (2.34–4.56) 3.09 (2.00–4.19) −0.012 (−0.040 to 0.017) 0.019 (−0.043 to 0.080) 0.031 (−0.037 to 0.099) 
  Rural 2.93 (2.39–3.46) 3.03 (2.45–3.62) 3.35 (2.84–3.86) 2.84 (2.37–3.31) 3.06 (2.10–4.01) 3.89 (2.60–5.18) 2.91 (2.03–3.79) 0.001 (−0.023 to 0.022) 0.053 (−0.015 to 0.121) 0.053 (−0.019 to 0.125) 
BMIa 
 Male 
  Underweight or normal 2.27 (1.64–2.89) 2.77 (2.03–3.50) 2.32 (1.72–2.93) 3.27 (2.47–4.07) 2.09 (0.88–3.30) 2.13 (1.08–3.18) 3.19 (1.75–4.62) 0.026 (−0.006 to 0.058) −0.058 (−0.124 to 0.008) −0.084 (−0.157 to −0.011)* 
  Overweight or obese 2.14 (1.68–2.59) 2.66 (2.04–3.28) 2.09 (1.66–2.52) 2.89 (2.34–3.43) 3.25 (2.22–4.27) 2.55 (1.63–3.47) 2.37 (1.58–3.17) 0.018 (−0.005 to 0.041) −0.017 (−0.071 to 0.036) −0.035 (−0.093 to 0.023) 
 Female 
  Underweight or normal 2.23 (1.72–2.75) 2.53 (1.98–3.07) 2.61 (2.14–3.09) 2.64 (2.12–3.15) 2.52 (1.61–3.44) 3.19 (2.08–4.30) 2.01 (1.24–2.78) 0.013 (−0.010 to 0.036) 0.028 (−0.033 to 0.088) 0.015 (−0.050 to 0.080) 
  Overweight or obese 4.11 (3.47–4.76) 3.98 (3.27–4.69) 4.06 (3.52–4.60) 3.30 (2.74–3.86) 3.09 (2.06–4.12) 4.23 (3.11–5.35) 3.99 (2.87–5.11) −0.024 (−0.051 to 0.003) 0.047 (−0.015 to 0.109) 0.071 (0.003–0.139)* 
Smoking status 
 Male 
  Non-smoker 2.64 (2.09–3.19) 2.80 (2.16–3.45) 2.21 (1.79–2.63) 3.01 (2.44–3.57) 3.27 (2.26–4.29) 2.32 (1.49–3.15) 2.75 (1.89–3.61) 0.007 (−0.018 to 0.032) −0.035 (−0.085 to 0.015) −0.042 (−0.098 to 0.014) 
  Smoker 1.68 (1.21–2.15) 2.58 (1.82–3.34) 2.12 (1.53–2.71) 3.03 (2.18–3.87) 2.26 (0.96–3.56) 2.65 (1.34–3.96) 2.32 (1.14–3.49) 0.036 (0.006 to 0.066)* −0.020 (−0.097 to 0.057) −0.056 (−0.139 to 0.027) 
 Female 
  Non-smoker 2.95 (2.52–3.37) 3.26 (2.80–3.71) 3.23 (2.86–3.60) 2.87 (2.49–3.25) 2.39 (1.74–3.03) 3.71 (2.81–4.61) 3.01 (2.30–3.72) −0.003 (−0.021 to 0.015) 0.042 (−0.006 to 0.091) 0.045 (−0.007 to 0.097) 
  Smoker 5.82 (3.60–8.04) 2.96 (1.23–4.69) 4.59 (2.68–6.50) 4.22 (2.46–5.98) 9.91 (4.81–15.01) 3.30 (0.83–5.77) 2.66 (0.31–5.02) −0.031 (−0.120 to 0.057) −0.050 (−0.207 to 0.108) −0.019 (−0.200 to 0.162) 
Education level 
 Male 
  High school or lower education 2.61 (2.13–3.09) 2.80 (2.18–3.42) 2.10 (1.61–2.59) 2.58 (1.96–3.20) 3.50 (2.23–4.76) 2.03 (1.12–2.94) 2.69 (1.58–3.81) −0.008 (−0.033 to 0.016) −0.028 (−0.083 to 0.026) −0.020 (−0.080 to 0.040) 
  College or higher education 1.73 (1.19–2.28) 2.64 (1.93–3.36) 2.48 (1.92–3.04) 3.60 (2.88–4.33) 2.93 (1.76–4.09) 2.94 (1.84–4.04) 2.69 (1.74–3.64) 0.055 (0.026 to 0.085)*** −0.033 (−0.099 to 0.033) −0.088 (−0.160 to −0.016)* 
 Female 
  High school or lower education 3.64 (3.14–4.14) 3.91 (3.29–4.53) 4.12 (3.60–4.64) 3.23 (2.71–3.75) 3.74 (2.61–4.87) 4.08 (3.08–5.09) 3.56 (2.28–4.83) −0.009 (−0.032 to 0.014) 0.043 (−0.013 to 0.098) 0.052 (−0.008 to 0.112) 
  College or higher education 2.14 (1.48–2.79) 2.11 (1.50–2.73) 2.65 (2.05–3.25) 2.94 (2.31–3.56) 2.35 (1.22–3.47) 3.68 (2.21–5.15) 2.64 (1.80–3.47) 0.030 (0.002–0.059)* 0.038 (−0.041 to 0.118) 0.008 (−0.076 to 0.092) 
Household income 
 Male 
  Lowest and second quartile 2.99 (2.33–3.64) 3.16 (2.38–3.93) 2.13 (1.61–2.65) 3.83 (3.10–4.56) 3.61 (2.25–4.97) 2.19 (1.24–3.13) 3.16 (1.85–4.46) 0.016 (−0.015 to 0.047) −0.081 (−0.142 to −0.021)* −0.097 (−0.165 to −0.029)* 
  Third and highest quartile 1.67 (1.25–2.09) 2.39 (1.74–3.03) 2.20 (1.72–2.67) 2.54 (1.99–3.09) 2.59 (1.62–3.55) 2.54 (1.62–3.47) 2.34 (1.48–3.19) 0.024 (0.002 to 0.047)* 0.001 (−0.054 to 0.054) −0.024 (−0.083 to 0.035) 
 Female 
  Lowest and second quartile 3.94 (3.32–4.56) 3.69 (3.03–4.35) 4.03 (3.43–4.63) 3.28 (2.68–3.88) 3.81 (2.61–5.01) 4.67 (3.40–5.94) 2.77 (1.79–3.76) −0.017 (−0.044 to 0.010) 0.070 (0.000–0.139) 0.087 (0.012–0.162)* 
  Third and highest quartile 2.54 (2.01–3.06) 2.85 (2.29–3.41) 2.77 (2.31–3.23) 2.70 (2.19–3.21) 2.17 (1.38–2.95) 3.04 (2.05–4.03) 3.15 (2.25–4.05) 0.004 (−0.019 to 0.027) 0.018 (−0.037 to 0.073) 0.014 (−0.046 to 0.074) 

The β values were multiplied by 10 owing to their minimal number.

AD, atopic dermatitis; AR, allergic rhinitis; BMI, body mass index; CI, confidence interval; KNHANES, Korea National Health and Nutrition Examination Survey.

aAccording to Asian-Pacific guidelines, BMI is divided into four groups: underweight (<18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25.0 kg/m2).

The figures in bold represent a significant variance (*p value between 0.05 and 0.01, **p value between 0.01 and 0.001, and ***p value <0.001).

Fig. 1.

Nationwide trends of allergic disease prevalence over 16 years among 92,135 Korean population, stratified by AD, AR, and asthma, 2007–2022.

Fig. 1.

Nationwide trends of allergic disease prevalence over 16 years among 92,135 Korean population, stratified by AD, AR, and asthma, 2007–2022.

Close modal

For both males and females, the trends before the pandemic showed a continuous increase in the prevalence of AD and AR (AD: 2.8% [95% CI, 2.5–3.2] in 2007–2009; 3.6% [95% CI, 3.2–3.9] in 2017–2019; AR: 11.7% [95% CI, 11.1–12.4] in 2007–2009; 15.0% [95% CI, 14.3–15.7] in 2017–2019), while asthma maintained a relatively stable trend (2.7% [95% CI, 2.4–3.0] in 2007–2009; 3.0% [95% CI, 2.7–3.3] in 2017–2019).

During the pandemic, AD and AR also experienced an increase in prevalence (AD: 4.0% [95% CI, 3.4–4.7] in 2020; 4.7% [95% CI, 3.9–5.4] in 2022; AR: 15.8% [95% CI, 14.6–16.9] in 2020; 17.4% [95% CI, 16.0–18.9] in 2022); in contrast, asthma exhibited slight decreases in their trends (2.9% [95% CI, 2.3–3.4] in 2020; 2.8% [95% CI, 2.3–3.3] in 2022; online suppl. Table S1; for all online suppl. material, see https://doi.org/10.1159/000540928). However, there were no statistically significant differences in the prevalence of AD, AR, and asthma between the COVID-19 period and the pre-pandemic period.

Figure 2a–c and online supplementary Table S2 outline total and sex-specific risk factors. The risk factors associated with the prevalence of specific diseases among males and females were found to differ, indicating a broader range of risk factors for females as follows: First, for AD, both sexes exhibited common risk factors, including the age range of 19–39 years and an education level of college or higher. However, smoking and high household income emerged as an additional risk factor for females. Next, regarding AR, individuals aged 19–39 and those with high income and a college education or higher were identified as risk factors for both males and females. Nonetheless, smoking was identified as an additional risk factor for females. Lastly, for asthma, being overweight or obese and smoking were found to be risk factors for females.

Fig. 2.

Ratio of ORs for differences in AD (a), AR (b), and asthma (c) prevalence before and during the COVID-19 (weighted % [95% CI]) among males and females, based on data obtained from the KNHANES (heatmap). BMI, body mass index; CI, confidence interval; KNHANES, Korea National Health and Nutrition Examination Survey; wOR, weighted odds ratio. *According to Asian-Pacific guidelines, BMI is divided into four groups: underweight (<18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25.0 kg/m2). Darker colors indicate higher OR values and values greater than 1 suggest increased risk, while values less than 1 suggest decreased risk. The figures in bold represent a significant variance (*p value between 0.05 and 0.01, **p value between 0.01 and 0.001, and ***p value <0.001).

Fig. 2.

Ratio of ORs for differences in AD (a), AR (b), and asthma (c) prevalence before and during the COVID-19 (weighted % [95% CI]) among males and females, based on data obtained from the KNHANES (heatmap). BMI, body mass index; CI, confidence interval; KNHANES, Korea National Health and Nutrition Examination Survey; wOR, weighted odds ratio. *According to Asian-Pacific guidelines, BMI is divided into four groups: underweight (<18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25.0 kg/m2). Darker colors indicate higher OR values and values greater than 1 suggest increased risk, while values less than 1 suggest decreased risk. The figures in bold represent a significant variance (*p value between 0.05 and 0.01, **p value between 0.01 and 0.001, and ***p value <0.001).

Close modal

Online supplementary Table S3 and Table S4 provide the weighted odds ratios (wORs) for AD, AR, and asthma compared to previous periods. Compared to the period from 2013 to 2016, the prevalence of AD and AR among females increased from 2017 to 2019 (AD: wORs, 1.2 [95% CI, 1.0–1.5]; AR: wORs, 1.1 [95% CI, 1.0–1.2]), while the prevalence of asthma increased among males (wORs, 1.4 [95% CI, 1.1–1.8]). Additionally, in 2020, compared to 2017–2019, there was an increase in the prevalence of AD among male smokers (wORs, 1.3 [95% CI, 0.8 to 2.9]) and an increase in the prevalence of asthma among female smokers (wORs, 2.5 [95% CI, 1.3–5.1]).

Key Finding

This study presents a large-scale analysis of sex-specific and long-term trends in AD, AR, and asthma prevalence over 16 years, from 2007 to 2022, involving 92,135 participants. For both sexes, the prevalence of AD and AR increased before the COVID-19 pandemic and continued to rise during the pandemic. Interestingly, among the three allergic diseases, AR exhibited a significant disparity in prevalence between males and females, with females showing higher rates. Meanwhile, the prevalence of asthma remained stable in both sexes. In addition, in the analysis of AD and AR, common risk factors for both males and females were the age range of 19–39 years and an education level of college or higher. However, females were found to have more risk factors for all three diseases, including smoking. Moreover, for AD, high income was identified as an additional risk factor, and for asthma, being overweight or obese was identified as an additional risk factor for females.

Plausible Underlying Mechanisms and Comparison of Previous Studies

In this study, more risk factors were identified in females than in males. This is likely because females are biologically more sensitive to hormonal and environmental factors than males [16]. Previous studies have shown that allergic diseases are notably more prevalent among females post-puberty [17], mainly due to the significant impact of sex hormones on the prevalence of allergic diseases [18]. For instance, the increase in estrogen levels during the periovulatory stage of the menstrual cycle has been linked to exacerbated nasal congestion and more severe symptoms of rhinitis, contributing to the higher incidence of these conditions in females [19].

Moreover, smoking and obesity not only increase the risk of allergic diseases but also can have more detrimental effects on females than on males due to physiological and hormonal differences [20]. Females are more susceptible to smoking-related respiratory symptoms, potentially owing to hormonal variations and the anti-estrogenic effects of smoking [21]. Additionally, obese females are at a higher risk of developing asthma than males, likely because of obesity’s restrictive impact on lung function [22].

The previous nationwide study conducted in Mexico regarding the shift in the male-to-female ratio in allergic disease before and after adolescence also revealed a higher incidence of the three diseases in females than males in adults [23]. In contrast, the weighted prevalence of AR was reported to be significantly higher in males than in females in a previous study conducted in China (n = 184,326). However, risk factors such as younger age, smoking, higher education level, and higher income were similar to the results of this study [24].

Previous studies have primarily focused on trends and risk factors in children and adolescents, with a particular emphasis on well-known risk factors such as obesity [25, 26]. Furthermore, they have often examined single major allergic diseases, such as asthma, rather than a range of allergic conditions [27]. In contrast, this study distinguishes itself by analyzing representative data to identify long-term trends and risk factors for major allergic diseases, specifically AD, AR, and asthma, in adults. Additionally, by considering these trends and risk factors separately by sex, the study offers valuable insights into the differing manifestations of allergic diseases in males and females.

Clinical and Policy Implications

Given the significant national and financial burdens associated with allergic diseases, policymakers, and healthcare professionals have to manage these conditions effectively [28]. This study identifies several factors that render patients, especially females, more vulnerable to allergic diseases, including smoking, high household income, and overweight or obesity. Therefore, tailored management and interventions considering these factors by sex are essential.

First of all, public health campaigns aimed at promoting healthier lifestyle choices, such as quitting smoking and maintaining a healthy weight, should be implemented. These campaigns should target both sexes but pay special attention to females [29]. Furthermore, it is essential to raise awareness among policymakers and healthcare professionals about the influence of allergic diseases on individuals’ health [30]. Increased funding and resources for study, prevention, and treatment programs targeting allergic diseases can significantly address this challenge.

Developing comprehensive strategies tailored to the specific factors identified in this study is vital for reducing the prevalence of allergic diseases and improving the overall health outcomes of the population. Applying the findings of this study could enhance organizations’ effectiveness in combating allergic diseases.

Strengths and Limitations

This study effectively showed sex-specific trends in allergic disease prevalence using 16 years of nationally representative data. In addition, this study is the most updated and comprehensive analysis of the sex-specific prevalence, identifying various vulnerable factors. Notably, this approach allows patients with allergic diseases to recognize different risk factors depending on their sex and assist in managing these factors, such as age, education level, household income, BMI, and smoking. Moreover, this study offers essential insights for health policymakers and professionals on creating sex-specific health interventions, which could improve disease prevention and management efficiency and reducing long-term socioeconomic costs.

This study has certain limitations. First, this study could not attain the AR data from the KNHANES between 2010 and 2012; however, since the analysis is over 13 years, the absence of data for these 3 years may not significantly influence the comparison of overall prevalence by sex [31, 32]. Second, the identification of high income as a female risk factor could stem from the over-representation of individuals with high incomes within the baseline population in this study. Furthermore, a college degree or a higher educational level has also been identified as a risk factor, which may be due to their relatively higher participation in self-reported surveys [33]. Therefore, further investigation is required to determine the degree to which high income and higher education levels are closely associated with the incidence of allergic diseases. Third, our dataset is self-reported; therefore, collecting information on allergic diseases may be subject to reporting biases, potentially leading to an underestimation of prevalence due to biases such as recall, information, and selection biases [34]. In addition, while our analysis can find the correlations between the diseases and various variables, it cannot prove the causality [35]. Last, data were limited to South Koreans, which might restrict the findings’ broader applicability, indicating the necessity of a broader demographic study in the future [36]. Despite this limitation, the study provides valuable country-specific data on allergic diseases, which may vary in characteristics across different nations.

This study provides a comprehensive analysis of sex-specific and long-term trends in the prevalence of AD, AR, and asthma over 16 years, from 2007 to 2022, based on data from 92,135 participants. The findings indicate that the prevalence of both AD and AR increased before the COVID-19 pandemic and continued to rise during the pandemic for both sexes. Notably, AR prevalence was consistently higher in females compared to males, while asthma prevalence remained stable in both sexes throughout the study period. In examining risk factors, it was found that both males and females shared common risk factors for AD and AR, specifically being in the age range of 19–39 years and having a college education or higher. However, females exhibited a greater number of risk factors for all three conditions. Smoking emerged as a common risk factor for females across AD, AR, and asthma. Additionally, high income was identified as an additional risk factor for AD in females, and being overweight or obese was identified as an additional risk factor for asthma in females. Finally, this study underscores the need for sex-specific health interventions and further study to address the intricate impact of socioeconomic factors and lifestyle choices on the prevalence and risk of AD, AR, and asthma.

The study was approved by the Institutional Review Board of the Korea Disease Control and Prevention Agency (2007-02CON-04-P, 2008-04EXP-01-C, 2009-01CON-03-2C, 2010-02CON-21-C, 2011-02CON-06-C, 2012-01EXP-01-2C, 2013-07CON-03-4C, 2013-12EXP-03-5C, 2018-01-03-P-A, 2018-01-03-C-A, 2018-01-03-2C-A, 2018-01-03-5C-A, and 2018-01-03-4C-A), and written informed consent was obtained from all participants. Furthermore, the KNHANES provides public access to its data, which can be utilized as a valuable resource for diverse epidemiological investigations. The study was conducted using the principles outlined in the Declaration of Helsinki.

The authors have no conflicts of interest to declare.

This research was supported by grants from the National Research Foundation of Korea (NRF) funded by the Korean government (MSIT; RS-2023-00248157) and the Ministry of Science and ICT (MSIT), South Korea, under the ITRC (Information Technology Research Center) support program (IITP-2024-RS-2024-00438239) supervised by the IITP (Institute for Information and Communications Technology Planning and Evaluation). The funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Dr. Dong Keon Yon is the senior author, had full access to all of the data in the study, supervised the study, served as a guarantor, and took responsibility for the integrity of the data and the accuracy of the data analysis. All authors approved the final version of the manuscript before submission. Yesol Yim, Hyesu Jo, Selin Woo, and Dong Keon Yon contributed to the study concept and design; acquisition, analysis, or interpretation of data; statistical analysis; and drafting of the manuscript. Yesol Yim, Hyesu Jo, Seoyoung Park, Yejun Son, Jaeyu Park, Hyeon Jin Kim, Sooji Lee, Hayeon Lee, Damiano Pizzol, Lee Smith, Saiah Kim, Jiseung Kang, Selin Woo, and Dong Keon Yon contributed to critical revision of the manuscript for important intellectual content. Yesol Yim and Hyesu Jo contributed equally as the first authors. Selin Woo and Dong Keon Yon contributed equally as the corresponding authors. The corresponding author attests that all listed authors meet the authorship criteria and that no one meeting the criteria has been omitted.

Additional Information

Yesol Yim and Hyesu Jo contributed equally as co-first authors.Edited by: H.-U. Simon, Bern.

Data are publicly available on legal and ethical grounds from the Korea Disease Control and Prevention Agency as open data (https://www.kdca.go.kr/yhs/home.jsp). Further inquiries including the study protocol and statistical code can be directed to the corresponding author, Dong Keon Yon (email: yonkkang@gmail.com).

1.
Denton
E
,
O’Hehir
RE
,
Hew
M
.
The changing global prevalence of asthma and atopic dermatitis
.
Allergy
.
2023
;
78
(
8
):
2079
80
.
2.
Seastedt
H
,
Nadeau
K
.
Factors by which global warming worsens allergic disease
.
Ann Allergy Asthma Immunol
.
2023
;
131
(
6
):
694
702
.
3.
Shin
YH
,
Hwang
J
,
Kwon
R
,
Lee
SW
,
Kim
MS
,
GBD 2019 Allergic Disorders Collaborators
, et al
.
Global, regional, and national burden of allergic disorders and their risk factors in 204 countries and territories, from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019
.
Allergy
.
2023
;
78
(
8
):
2232
54
.
4.
Wang
Z
,
Li
Y
,
Gao
Y
,
Fu
Y
,
Lin
J
,
Lei
X
, et al
.
Global, regional, and national burden of asthma and its attributable risk factors from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019
.
Respir Res
.
2023
;
24
(
1
):
169
.
5.
Colombo
D
,
Zagni
E
,
Ferri
F
,
Canonica
GW
,
PROXIMA study centers
.
Gender differences in asthma perception and its impact on quality of life: a post hoc analysis of the PROXIMA (Patient Reported Outcomes and Xolair® in the Management of Asthma) study
.
Allergy Asthma Clin Immunol
.
2019
;
15
:
65
.
6.
Boonchai
W
,
Likittanasombat
S
,
Viriyaskultorn
N
,
Kanokrungsee
S
.
Gender differences in allergic contact dermatitis to common allergens
.
Contact Dermatitis
.
2024
;
90
(
5
):
458
65
.
7.
Rosário
CS
,
Cardozo
CA
,
Neto
HJC
,
Filho
NAR
.
Do gender and puberty influence allergic diseases
.
Allergol Immunopathol
.
2021
;
49
(
2
):
122
5
.
8.
Izquierdo-Dominguez
A
,
Rojas-Lechuga
MJ
,
Alobid
I
.
Management of allergic diseases during COVID-19 outbreak
.
Curr Allergy Asthma Rep
.
2021
;
21
(
2
):
8
.
9.
Kang
J
,
Park
J
,
Lee
M
,
Kim
HJ
,
Kwon
R
,
Kim
S
, et al
.
National trends and prevalence of atopic dermatitis and pandemic-related factors among Korean adults, 2007-2021
.
Int Arch Allergy Immunol
.
2024
;
185
(
4
):
320
33
.
10.
Yon
DK
,
Hwang
S
,
Lee
SW
,
Jee
HM
,
Sheen
YH
,
Kim
JH
, et al
.
Indoor exposure and sensitization to formaldehyde among inner-city children with increased risk for asthma and rhinitis
.
Am J Respir Crit Care Med
.
2019
;
200
(
3
):
388
93
.
11.
Koo
MJ
,
Kwon
R
,
Lee
SW
,
Choi
YS
,
Shin
YH
,
Rhee
SY
, et al
.
National trends in the prevalence of allergic diseases among Korean adolescents before and during COVID-19, 2009-2021: a serial analysis of the national representative study
.
Allergy
.
2023
;
78
(
6
):
1665
70
.
12.
Woo
HG
,
Son
Y
,
Kim
S
,
Kim
J
,
Kang
J
,
Lee
SW
.
Association of transitioning from combustible cigarettes to noncombustible nicotine or tobacco products with subsequent cancer risk: a nationwide cohort study in South Korea
.
Life Cycle
.
2024
;
4
:
e2
.
13.
Choi
Y
,
Kim
HJ
,
Park
J
,
Lee
M
,
Kim
S
,
Koyanagi
A
, et al
.
Acute and post-acute respiratory complications of SARS-CoV-2 infection: population-based cohort study in South Korea and Japan
.
Nat Commun
.
2024
;
15
(
1
):
4499
.
14.
Kim
S
,
Lee
H
,
Lee
J
,
Lee
SW
,
Kwon
R
,
Kim
MS
, et al
.
Short- and long-term neuropsychiatric outcomes in long COVID in South Korea and Japan
.
Nat Hum Behav
.
2024
.
15.
Park
S
,
Kim
HJ
,
Kim
S
,
Rhee
SY
,
Woo
HG
,
Lim
H
, et al
.
National trends in physical activity among adults in South Korea before and during the COVID-19 pandemic, 2009-2021
.
JAMA Netw Open
.
2023
;
6
(
6
):
e2316930
.
16.
Colineaux
H
,
Neufcourt
L
,
Delpierre
C
,
Kelly-Irving
M
,
Lepage
B
.
Explaining biological differences between men and women by gendered mechanisms
.
Emerg Themes Epidemiol
.
2023
;
20
(
1
):
2
.
17.
Brix
N
,
Ernst
A
,
Lauridsen
LLB
,
Parner
E
,
Stovring
H
,
Olsen
J
, et al
.
Timing of puberty in boys and girls: a population-based study
.
Paediatr Perinat Epidemiol
.
2019
;
33
(
1
):
70
8
.
18.
Hohmann
C
,
Keller
T
,
Gehring
U
,
Wijga
A
,
Standl
M
,
Kull
I
, et al
.
Sex-specific incidence of asthma, rhinitis and respiratory multimorbidity before and after puberty onset: individual participant meta-analysis of five birth cohorts collaborating in MeDALL
.
BMJ Open Respir Res
.
2019
;
6
(
1
):
e000460
.
19.
Weare-Regales
N
,
Chiarella
SE
,
Cardet
JC
,
Prakash
YS
,
Lockey
RF
.
Hormonal effects on asthma, rhinitis, and eczema
.
J Allergy Clin Immunol Pract
.
2022
;
10
(
8
):
2066
73
.
20.
Lee
A
,
Lee
SY
,
Lee
KS
.
The use of heated tobacco products is associated with asthma, allergic rhinitis, and atopic dermatitis in Korean adolescents
.
Sci Rep
.
2019
;
9
(
1
):
17699
.
21.
Allen
AM
,
Oncken
C
,
Hatsukami
D
.
Women and smoking: the effect of gender on the epidemiology, health effects, and cessation of smoking
.
Curr Addict Rep
.
2014
;
1
(
1
):
53
60
.
22.
Wang
L
,
Wang
KS
,
Gao
X
,
Paul
TK
,
Cai
JW
,
Wang
YF
.
Sex difference in the association between obesity and asthma in US adults: findings from a national study
.
Respir Med
.
2015
;
109
(
8
):
955
62
.
23.
Becerril-Ángeles
M
,
Vargas
MH
,
Medina-Reyes
IS
,
Rascón-Pacheco
RA
.
Trends (2007–2019) of major atopic diseases throughout the life span in a large Mexican population
.
World Allergy Organ J
.
2023
;
16
(
1
):
100732
.
24.
Zhang
X
,
Zhang
M
,
Sui
H
,
Li
C
,
Huang
Z
,
Liu
B
, et al
.
Prevalence and risk factors of allergic rhinitis among Chinese adults: a nationwide representative cross-sectional study
.
World Allergy Organ J
.
2023
;
16
(
3
):
100744
.
25.
Licari
A
,
Magri
P
,
De Silvestri
A
,
Giannetti
A
,
Indolfi
C
,
Mori
F
, et al
.
Epidemiology of allergic rhinitis in children: a systematic Review and meta-analysis
.
J Allergy Clin Immunol Pract
.
2023
;
11
(
8
):
2547
56
.
26.
Averill
SH
,
Forno
E
.
Management of the pediatric patient with asthma and obesity
.
Ann Allergy Asthma Immunol
.
2024
;
132
(
1
):
30
9
.
27.
Bantula
M
,
Roca-Ferrer
J
,
Arismendi
E
,
Picado
C
.
Asthma and obesity: two diseases on the rise and bridged by inflammation
.
J Clin Med
.
2021
;
10
(
2
):
169
.
28.
Wang
J
,
Zhou
Y
,
Zhang
H
,
Hu
L
,
Liu
J
,
Wang
L
, et al
.
Pathogenesis of allergic diseases and implications for therapeutic interventions
.
Signal Transduct Target Ther
.
2023
;
8
(
1
):
138
.
29.
Kite
J
,
Grunseit
A
,
Mitchell
G
,
Cooper
P
,
Chan
L
,
Huang
BH
, et al
.
Impact of traditional and new media on smoking intentions and behaviors: secondary analysis of tasmania’s tobacco control mass media campaign program, 2019-2021
.
J Med Internet Res
.
2024
;
26
:
e47128
.
30.
Sanchez-Borges
M
,
Martin
BL
,
Muraro
AM
,
Wood
RA
,
Agache
IO
,
Ansotegui
IJ
, et al
.
The importance of allergic disease in public health: an iCAALL statement
.
World Allergy Organ J
.
2018
;
11
(
1
):
8
.
31.
Jeong
J
,
Jo
H
,
Son
Y
,
Lee
S
,
Lee
K
,
Choi
Y
, et al
.
Association of soda drinks and fast food with allergic diseases in Korean adolescents: a nationwide representative study
.
Int Arch Allergy Immunol
.
2024
;
1
:
1
17
.
32.
Lee
H
,
Park
J
,
Lee
M
,
Kim
HJ
,
Kim
M
,
Kwon
R
, et al
.
National trends in allergic rhinitis and chronic rhinosinusitis and COVID-19 pandemic-related factors in South Korea, from 1998 to 2021
.
Int Arch Allergy Immunol
.
2024
;
185
(
4
):
355
61
.
33.
Spitzer
S
.
Biases in health expectancies due to educational differences in survey participation of older Europeans: it’s worth weighting for
.
Eur J Health Econ
.
2020
;
21
(
4
):
573
605
.
34.
Althubaiti
A
.
Information bias in health research: definition, pitfalls, and adjustment methods
.
J Multidiscip Healthc
.
2016
;
9
:
211
7
.
35.
Ayoub
F
,
Sato
T
,
Sakuraba
A
.
Football and COVID-19 risk: correlation is not causation
.
Clin Microbiol Infect
.
2021
;
27
(
2
):
291
2
.
36.
Aliyu
AA
.
Public health ethics and the COVID-19 pandemic
.
Ann Afr Med
.
2021
;
20
(
3
):
157
63
.