Risk factors for community-acquired pneumonia in older adults in Japan after the introduction of the childhood PCV13

Risk factors for community-acquired pneumonia in older adults in Japan after the introduction of the childhood PCV13 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Risk factors for community-acquired pneumonia in older adults in Japan after the introduction of the childhood PCV13 Naoki Inoshima, Kei Nakashima, Kanzo Suzuki, Hirohiko Nagasaka, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9391522/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Background Community-acquired pneumonia (CAP) remains a leading cause of death globally. Although the introduction of pediatric 13-valent pneumococcal conjugate vaccine (PCV13) has altered the epidemiology of pneumococcal disease in children, risk factors for CAP in older adults remain insufficiently explored. Additionally, few studies have compared risks between those aged 65–74 and ≥ 75 years. We evaluated risk factors for CAP in older Japanese adults by age. Methods We conducted a secondary analysis of a multicenter, nationwide case-control study between October 2016 and December 2019. Cases were individuals aged ≥ 65 years with CAP. Up to five controls were selected per case, matched by sex, fiscal-year age, and visit date. Clinical and lifestyle data were collected via questionnaires. Adjusted odds ratios (aORs) were calculated for participants overall and stratified by age (65–74 and ≥ 75 years) using conditional logistic regression. Results Analysis included 142 cases and 596 controls. CAP risk was associated with living with children ≤ 6 years (aOR: 6.15, 95% confidence interval [CI]: 2.84–13.32), low body mass index (BMI) (< 18.5 kg/m²) (aOR: 1.78, 95% CI: 1.02–3.09), and impaired activities of daily living (ADL) (aOR: 2.44, 95% CI: 1.12–5.30). High BMI (≥ 25.0 kg/m²) was associated with a reduced risk (aOR: 0.55, 95% CI: 0.31–0.95). Among those aged 65–74 years, living with children ≤ 6 years (aOR: 4.89, 95% CI: 1.83–13.08) was a risk factor for CAP, whereas high BMI (aOR: 0.41, 95% CI: 0.18–0.89) and gastrointestinal disease (aOR: 0.19, 95% CI: 0.04–0.84) were associated with a reduced risk. Among those aged ≥ 75 years, chronic obstructive pulmonary disease (aOR: 3.59, 95% CI: 1.29–9.93), asthma (aOR: 2.99, 95% CI: 1.25–7.16), living with children ≤ 6 years (aOR: 11.62, 95% CI: 3.12–43.33), and impaired ADL (aOR: 2.90, 95% CI: 1.10–7.65) were risk factors for CAP. Conclusions Living with children ≤ 6 years remains a major CAP risk factor in older adults after the introduction of pediatric PCV13. However, risk factors differ by age. Respiratory comorbidities and functional decline are dominant drivers of CAP in adults aged ≥ 75 years. Prevention strategies should be tailored by age. community-acquired pneumonia older adults risk factors Figures Figure 1 Background Community-acquired pneumonia (CAP) is one of the major causes of hospitalization and mortality in older adults [ 1 ]. According to the World Health Organization, lower respiratory infections, including CAP, ranked as the fifth leading cause of death and, aside from COVID-19, remained the leading cause of communicable disease death worldwide in 2024 [ 2 ]. The high CAP morbidity and mortality rates in older adults has not improved for decades despite advances in medical care such as standardized guidelines, antimicrobial therapy, and prevention measures for high-risk populations [ 3 – 5 ]. Evaluating the risk factors for CAP is essential not only for implementing appropriate prevention and management strategies, but also for identifying areas for future pneumonia-related research and for determining key confounders in epidemiological studies, including vaccine studies [ 6 , 7 ]. Previous systematic reviews have identified key risk factors for CAP including older age, male sex, smoking, environmental exposures, malnutrition, prior CAP, chronic bronchitis/chronic obstructive pulmonary disease (COPD), asthma, functional impairment, poor oral hygiene, immunosuppressive therapy, and use of gastric acid-suppressing drugs [ 8 , 9 ]. Vaccination is critical for preventing pneumonia, with pneumococcal vaccination being the main prevention measure against Streptococcus pneumoniae infection [ 10 ]. The 23-valent pneumococcal polysaccharide vaccine (PPSV23) was the first pneumococcal vaccine used globally for older adults, and subsequently the 7-valent and 13-valent pneumococcal conjugate vaccines (PCV7 and PCV13) were introduced for children, with PCV13 later being introduced for adult [ 11 ]. PCV13 implementation in children has transformed the epidemiology of pneumococcal disease, reducing the incidence of pneumonia in children and adults and causing serotype replacement [ 11 – 13 ]. Following the introduction of PCV13 in Japan in November 2013, vaccination coverage in children reached approximately 90% in 2014 [ 7 ]. PCV13 vaccination in children reduces pneumococcal carriage [ 14 ] and, consequently, transmission to older adults, potentially altering risk factors such as living with young children. However, few studies have examined pneumonia risk factors for CAP in older adults since the introduction of routine pediatric PCV13 vaccination. In Spain PCV13 was approved for children in 2010 but vaccination coverage remained at approximately 50% until 2013. A study conducted in Spain between 2009 and 2010 identified HIV infection, COPD, asthma, smoking, and poor oral hygiene as significant risk factors for CAP in adults [ 15 ]. In Japan, after the introduction of PCV13 vaccination in children in 2013, a claims study using data collected from 2018 to 2022 identified impaired social functioning as a risk factor for adult CAP, although the use of administrative data limited the precision of the estimate [ 16 ]. Additionally, the risk of developing pneumonia has been reported to be higher in adults aged 75 years and older [ 17 – 20 ]. This suggests that, even within the older adult population aged ≥ 65 years, the risk may differ between those aged < 75 years and those aged ≥ 75 years. However, to our knowledge, no study has compared the risks in older adults aged < 75 years with those of older adults aged ≥ 75 years to evaluate risk factors for pneumonia onset. Our group conducted a nationwide case-control study between 2016 and 2019 to evaluate the effectiveness of PPSV23 against CAP among older adults in Japan [ 7 ], at a time when PPSV23 coverage in older adults was approximately 55% [ 21 ] and PCV13 coverage in children was approximately 90%. In this case-control study, PPSV23 was not associated with a statistically significant protective effect against CAP, possibly due to serotype replacement owing to pediatric PCV13 use and resulting changes in the serotype distribution [ 7 ]. Using data from this 2016–2019 study, we performed a secondary analysis to identify risk factors for CAP in older Japanese adults (aged ≥ 65 years) after the introduction of pediatric PCV13 and conducted subgroup analyses stratified by age (< 75 years and ≥ 75 years). Methods Study design We conducted a secondary analysis of data from a nationwide, multicenter, prospective, case-control study conducted in Japan. The original research was a hospital-based matched case-control study carried out from October 1, 2016, to December 31, 2019, at 41 healthcare facilities, which included 30 hospitals and 11 clinics, spread across the Hokkaido, Tohoku, Hokuriku, Kanto, Tokai, Kinki, Shikoku, and Kyushu regions [7]. Cases included in this study were restricted to adults aged 65 years and older who were living at home and developed pneumonia, and the outcomes focused on CAP. Because the cases were patients diagnosed with CAP in outpatient settings, including emergency departments in clinics or hospitals, controls were chosen from outpatients attending the same clinics or hospitals. In October 2014, a national immunization program for PPSV23 targeting individuals aged 65 years and older was launched, with vaccinations provided to eligible participants at local clinics or hospitals. In this program, PPSV23 was administered to adults who reached 65, 70, 75, 80, 85, 90, 95, or 100 years of age within a given fiscal year. As transitional measures, individuals aged ≥100 years at the end of fiscal year 2013 were additionally eligible in fiscal year 2014 at the time of program introduction. Similarly, those aged ≥100 years at the end of fiscal year 2018 were eligible in fiscal year 2019 when the transitional measures were extended. Ethical approval for this secondary analysis was obtained from the central institutional review board at Osaka Metropolitan University (#2023-082). In addition, the study was approved by Kameda Medical Center and Nagoya City University, which were participating institutions. The research adhered to the principles outlined in the Declaration of Helsinki. The institutional review board waived the requirement for informed consent, and patients were given the opportunity to opt out of the study. Definition of cases and controls In the original study [7], conducted between October 1, 2016, and September 30, 2019, individuals aged 65 years and older who were newly diagnosed with CAP at outpatient facilities, including emergency departments, were prospectively enrolled as cases. These patients were registered on the day that they were diagnosed with pneumonia in either the outpatient or emergency department. The physicians at the participating institutions diagnosed pneumonia based on clinical manifestations such as fever, cough, and sputum, along with elevated leukocyte counts or C-reactive protein levels, and the presence of infiltration on chest X-ray or computed tomography. The diagnosis of pneumococcal pneumonia was subsequently confirmed through sputum culture using a semiquantitative method, Gram staining showing Gram-positive cocci in pairs, blood culture, or a positive pneumococcal urinary antigen test. For each case, we recruited up to five controls without pneumonia who visited the same clinics and hospitals, matched by sex, fiscal-year age (corresponding to the age categories of the national immunization program), and visit date (within 3 months of confirmation of the corresponding case). The exclusion criteria for both cases and controls included residing in a nursing home, having aspiration pneumonia (caused by inhalation during eating or vomiting), having malignant tumors, taking oral steroids or immunosuppressants, or having a history of splenectomy. Patients with malignancies were excluded owing to potential immunosuppression. To minimize overrepresentation in the number of cases at some facilities, each facility was limited to enrolling a maximum of five matched sets (five cases and 25 controls) per year. Data collection For current analysis, we extracted variables collected in the original study [7]. In the original study, the attending physician gathered clinical details on both cases and controls using a structured questionnaire, which included information on: a) self-reported age, sex, date of birth, presence or absence of underlying respiratory diseases (such as chronic bronchitis, pulmonary emphysema, interstitial pneumonia, asthma, pulmonary tuberculosis sequelae, or other respiratory diseases), and vaccination history (dates of PPSV23, PCV13, and influenza vaccine administration); b) pneumonia-specific information (for cases only), such as the date of diagnosis, clinical manifestations, laboratory data related to the pneumonia diagnosis (leukocyte count and C-reactive protein levels), and results from diagnostic tests (pneumococcal urinary antigen test and sputum culture). Additionally, we extracted data from a self-administered questionnaire that study participants or their next of kin were asked to fill out. This questionnaire included details regarding their status at the time of enrollment, such as height, body weight, living with children aged under 6 years old, activities of daily living (ADL; bedridden, semi-bedridden, semi-self-supported, or self-supported), presence or absence of underlying diseases (hypertension, dyslipidemia, chronic kidney disease, heart disease, stroke, diabetes mellitus, liver disease, or gastrointestinal disease), alcohol use history (never, past, occasionally, or daily), smoking history (never smoker, past smoker, or current smoker) and vaccination status (PPSV23 in the past 5 years and influenza vaccination in the past 6 months). Both the physician-administered questionnaire and the self-administered questionnaire were developed specifically for the original study [7] and have not been published elsewhere. An English-language version of the questionnaires is provided in Supplementary Material 1. Pneumococcal vaccination status (i.e., vaccinated or unvaccinated) and the specific vaccine type were determined using information from two sources: data gathered by the attending physician and data reported by the participant or their next of kin. A participant was classified as “vaccinated” if either source indicated a history of vaccination, irrespective of the date of administration. For those classified as vaccinated, the specific vaccine type administered (e.g., PPSV23, PCV13) was determined primarily based on the physician's records. Influenza vaccination status was determined primarily from the information given in participant’s self-administered questionnaire. When vaccination status within the past 6 months was unclear, physician’s records were used for verification. Participants were classified as vaccinated if either source indicated influenza vaccination within 6 months prior to the case’s diagnosis date or the control’s enrollment date. Statistical analysis In this secondary analysis, participants with any missing data were excluded using listwise deletion. All underlying diseases were categorized as either present or absent, whereas ADL status was classified as either “not independent” (bedridden, semi-bedridden, or semi-self-supported) or “independent” (self-supported) for the purpose of analysis. Body mass index (BMI) was divided into three categories: <18.5, 18.5–24.9, and ≥25.0 kg/m 2 . The Wilcoxon rank-sum test, Chi-square test, and Fisher’s exact test were used to assess the statistical significance of differences between the case and control groups, as appropriate. Conditional logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for each factor associated with pneumonia. Both crude and adjusted ORs were estimated. Adjustment variables included established risk factors for pneumonia (smoking, COPD, asthma, diabetes mellitus, ADL) [8, 9], variables with p < 0.20 in the comparison of baseline characteristics, and history of pneumococcal and influenza vaccination. Subgroup analyses stratified by fiscal-year age (<75 years and ≥75 years) were also conducted using conditional logistic regression. While fiscal-year age was used for stratification to maintain the validity of the conditional logistic model in accordance with the matching criteria, chronological age was reported in the results for intuitive interpretation. The same adjustment variables as in the overall analysis were used in all subgroup models. Finally, we performed an additional conditional logistic regression analysis limited to cases with pneumococcal pneumonia. This analysis was conducted because children routinely receive PCV13, which reduces pneumococcal carriage in this population and thereby limits transmission of Streptococcus pneumoniae to older adults; consequently, the impact of living with children aged ≤6 years may be attenuated when focusing specifically on pneumococcal pneumonia. Although the same adjustment variables were used as in the primary model, variables with zero events in at least one group (i.e., gastrointestinal disease and liver disease) were excluded to avoid quasi-complete separation and to ensure model stability. All statistical analyses were performed using SAS version 9.3 (SAS Institute, Inc., Cary, NC, USA), with statistical significance set at p < 0.05. Results Figure 1 shows the flow of study participants. Of the 797 eligible participants (159 cases and 638 controls), 59 were excluded from the analysis due to missing data or a lack of matched controls, leaving 738 participants (142 cases and 596 controls) included in the analysis of risk factors for all-cause CAP. Among the cases, 102 were recruited from hospital-based internal medicine departments, 39 from clinics, and 1 from an unspecified department within a hospital. Among the controls, 342 were enrolled from hospital-based internal medicine departments, 185 from clinics, and 69 from non-internal medicine or unspecified departments of hospitals, including orthopedics (n = 25), ophthalmology (n = 10), otorhinolaryngology (n = 6), dermatology (n = 4), urology (n = 3), surgery (n = 2), gynecology (n = 1), and unspecified (n = 18) departments. This analysis population was stratified into two subgroups based on fiscal-year age: the subgroup aged 65–74 years (N = 390) included 74 cases and 316 controls, and the subgroup aged ≥ 75 years (N = 348) included 68 cases and 280 controls. Additionally, 174 participants, comprising 31 cases and 143 controls were included in the analysis of risk factors for pneumococcal CAP. Table 1 shows the baseline characteristics of all participants. The median age was 75 years in both the case and control groups. The proportion of male participants was 56% in the case group and 53% in the control group. The case and control groups had similar influenza vaccination (42% vs. 44%, respectively; p = 0.603) and pneumococcal vaccination (58% vs. 56%, respectively; p = 0.603) coverage. Among underlying medical conditions, COPD was significantly more prevalent in the case group (24% vs. 14%; p = 0.003), whereas dyslipidemia was more prevalent in the control group (19% vs. 29%; p = 0.014). Additionally, the proportion of participants with a low BMI (< 18.5 kg/m²) was significantly higher in the case group than in the control group (23% vs. 11%; p < 0.001). Cases were also more likely to living with children aged ≤ 6 years (15% vs. 3%; p < 0.001) and to have impaired ADL (defined as “not independent”) (10% vs. 5%; p = 0.014). Alcohol consumption and the prevalence of diabetes mellitus did not differ significantly between the case and the control groups. Table 1 Participant baseline characteristics (N = 738) Characteristics Cases (N = 142) Controls (N = 596) p b Age (years), a median (IQR) 75 (70–80) 75 (70–80) 0.981 Sex Male 79 (56%) 315 (53%) 0.550 Female 63 (44%) 281 (47%) Vaccination Pneumococcal vaccine 83 (58%) 334 (56%) 0.603 PPSV23 only 79 (56%) 310 (52%) PCV13 only 1 (0.7%) 10 (1.7%) Both 1 (0.7%) 11 (1.9%) Unknown 2 (1.4%) 3 (0.5%) Influenza vaccine 59 (42%) 262 (44%) 0.603 Respiratory diseases COPD 34 (24%) 83 (14%) 0.003 Interstitial pneumonia 6 (4%) 24 (4%) 0.914 Bronchial asthma 23 (16%) 74 (12%) 0.231 Tuberculosis (sequelae) 5 (4%) 9 (2%) 0.161 Underlying diseases Hypertension 67 (47%) 320 (54%) 0.163 Dyslipidemia 27 (19%) 174 (29%) 0.014 Diabetes 35 (25%) 138 (23%) 0.706 Chronic kidney disease 9 (6%) 54 (9%) 0.297 Heart disease 19 (13%) 103 (17%) 0.261 Stroke 6 (4%) 27 (5%) 0.875 Gastrointestinal disease 13 (9%) 84 (14%) 0.118 Liver disease 3 (2%) 28 (5%) 0.168 BMI (kg/m²) < 18.5 33 (23%) 64 (11%) < 0.001 18.5–24.9 87 (61%) 372 (62%) ≥ 25.0 22 (15%) 160 (27%) Living with children aged ≤ 6 years No 121 (85%) 580 (97%) < 0.001 Yes 21 (15%) 16 (3%) Activities of daily living Independent 128 (90%) 569 (95%) 0.013 Not independent 14 (10%) 27 (5%) Alcohol use history Never/Past 88 (62%) 374 (63%) 0.852 Occasionally 27 (19%) 102 (17%) Daily 27 (19%) 120 (20%) Smoking history Never smoker 75 (53%) 343 (58%) 0.203 Past smoker 49 (35%) 205 (34%) Current smoker 18 (13%) 48 (8%) a Age indicates chronological age at the time of diagnosis or enrollment. b The p values were calculated using the Wilcoxon rank-sum test, chi-square test, or Fisher’s exact test, as appropriate. BMI, body mass index; COPD, chronic obstructive lung disease; IQR, interquartile range. Table 2 shows the ORs for CAP. In the unstratified adjusted analysis, low BMI (< 18.5 kg/m²; adjusted OR [aOR] 1.78, 95% CI, 1.02–3.09), living with children aged ≥ 6 years (aOR 6.15, 95% CI, 2.84–13.32), and impaired ADL (aOR 2.44, 95% CI, 1.12–5.30) were significantly associated with an increased risk of pneumonia, whereas a high BMI (≥ 25.0 kg/m²) was associated with a decreased risk (aOR 0.55, 95% CI, 0.31–0.95). Table 2 Risk factors for community-acquired pneumonia in older adults overall and by age group Overall (65 ≥ years) (N = 738) 65–74 years (N = 390) ≥ 75 years (N = 348) Crude OR (95% CI) Adjusted OR* (95% CI) Crude OR (95% CI) Adjusted OR* (95% CI) Crude OR (95% CI) Adjusted OR* (95% CI) COPD No 1 1 1 1 1 1 Yes 1.91 (1.13–3.20) 1.69 (0.92–3.08) 1.60 (0.82–3.13) 1.33 (0.61–2.94) 2.51 (1.09–5.77) 3.59 (1.29–9.93) Bronchial asthma No 1 1 1 1 1 1 Yes 1.45 (0.86–2.44) 1.37 (0.78–2.41) 0.99 (0.47–2.08) 0.71 (0.31–1.64) 2.22 (1.05–4.66) 2.99 (1.25–7.16) Tuberculosis No 1 1 1 1 1 1 Yes 2.68 (0.86–8.31) 2.40 (0.71–8.15) 1.67 (0.17–16.02) 2.11 (0.18–25.38) 3.23 (0.85–12.30) 2.21 (0.50–9.76) Hypertension No 1 1 1 1 1 1 Yes 0.76 (0.51–1.13) 0.85 (0.55–1.33) 0.75 (0.44–1.28) 0.86 (0.47–1.60) 0.77 (0.43–1.39) 0.94 (0.47–1.89) Dyslipidemia No 1 1 1 1 1 1 Yes 0.59 (0.35–0.97) 0.78 (0.45–1.35) 0.52 (0.26–1.06) 0.66 (0.31–1.41) 0.67 (0.32–1.39) 0.83 (0.36–1.94) Diabetes No 1 1 1 1 1 1 Yes 1.04 (0.67–1.60) 1.36 (0.84–2.19) 0.80 (0.43–1.48) 1.05 (0.52–2.11) 1.36 (0.74–2.51) 1.82 (0.90–3.69) Gastrointestinal disease No 1 1 1 1 1 1 Yes 0.58 (0.30–1.12) 0.59 (0.29–1.19) 0.27 (0.07–0.99) 0.19 (0.04–0.84) 0.84 (0.39–1.82) 1.11 (0.46–2.68) Liver disease No 1 1 1 1 1 1 Yes 0.41 (0.12–1.43) 0.37 (0.10–1.34) 0.22 (0.03–1.72) 0.14 (0.02–1.28) 0.74 (0.15–3.66) 0.78 (0.15–4.09) BMI (kg/m²) < 18.5 2.12 (1.29–3.46) 1.78 (1.02–3.09) 1.90 (0.93–3.86) 1.59 (0.69–3.62) 2.34 (1.18–4.63) 1.97 (0.86–4.50) 18.5–24.9 1 1 1 1 1 1 ≥ 25.0 0.55 (0.32–0.93) 0.55 (0.31–0.95) 0.43 (0.21–0.89) 0.41 (0.18–0.89) 0.73 (0.34–1.58) 0.58 (0.25–1.36) Living with children aged ≤ 6 years No 1 1 1 1 1 1 Yes 6.66 (3.23–13.74) 6.15 (2.84–13.32) 6.53 (2.54–16.78) 4.89 (1.83–13.08) 6.85 (2.22–21.14) 11.62 (3.12–43.33) Activities of daily living Independent 1 1 1 1 1 1 Not independent 2.12 (1.04–4.33) 2.44 (1.12–5.30) 2.51 (0.68–9.23) 3.86 (0.78–19.20) 1.98 (0.85–4.62) 2.90 (1.10–7.65) Smoking history Never smoker 1 1 1 1 1 1 Past smoker 1.15 (0.68–1.95) 1.07 (0.59–1.95) 1.32 (0.66–2.62) 1.22 (0.56–2.66) 0.98 (0.42–2.25) 0.73 (0.26–2.09) Current smoker 1.84 (0.91–3.71) 1.58 (0.73–3.40) 1.43 (0.59–3.46) 1.11 (0.42–2.90) 2.98 (0.94–9.47) 2.40 (0.61–9.38) *The model incorporated all variables listed in the Table, as well as pneumococcal and influenza vaccination. BMI, body mass index; CI, confidence interval; COPD, chronic obstructive lung disease; OR, odds ratio Next, we conducted a subgroup analysis stratified by fiscal-year age (< 75 years vs. ≥75 years). In the subgroup of patients aged 65–74 years (Supplementary Table 1), dyslipidemia was less common among cases than among controls (18% vs. 29%; p = 0.039). Compared with controls, cases were more likely to have a BMI < 18.5 kg/m² (22% vs. 10%; p = 0.003) and more likely to be living with children aged ≤ 6 years (18% vs. 3%; p < 0.001). In the subgroup of adults aged 65–74 years, multivariable analysis (Table 2 ) showed that living with children aged ≤ 6 years was strongly associated with an increased risk of CAP (adjusted OR 4.89, 95% CI 1.83–13.08). In contrast, gastrointestinal disease (adjusted OR 0.19, 95% CI 0.04–0.84) and a higher BMI (≥ 25.0 kg/m²) (adjusted OR 0.41, 95% CI 0.18–0.89) were both associated with a lower risk of CAP. In the subgroup of patients aged ≥ 75 years (Supplementary Table 2), cases were more likely than controls to have COPD (24% vs. 13%; p = 0.021), a BMI < 18.5 kg/m² (25% vs. 11%; p = 0.012), and to be living with children aged ≤ 6 years (12% vs. 2%; p < 0.001). In the subgroup aged ≥ 75 years, multivariable analysis (Table 2 ) showed that COPD (adjusted OR 3.59, 95% CI 1.29–9.93), bronchial asthma (adjusted OR 2.99, 95% CI 1.25–7.16), living with children aged ≤ 6 years (adjusted OR 11.62, 95% CI 3.12–43.33), and impaired ADL (adjusted OR 2.90, 95% CI 1.10–7.65) were associated with a significantly increased risk of CAP. The baseline characteristics of the cases (n = 31) with pneumococcal pneumonia and their matched controls (n = 143) are shown in Supplementary Table 3 and the adjusted ORs for this subgroup are shown in Supplementary Table 4. Compared with controls, cases were more likely to be living with children aged ≤ 6 years (16% vs. 2%; p = 0.005). After adjustment, living with children aged ≤ 6 years remained a significant risk factor for pneumococcal CAP (adjusted OR 7.22, 95% CI 1.23–42.34). Discussion In this secondary analysis of a multicenter case-control study conducted in Japan following the introduction of the PCV13 for children, we identified distinct risk factors for CAP among older adults. In all participants, living with children aged ≤ 6 years, low BMI, and impaired ADL were associated with an increased risk of CAP, whereas a high BMI was associated with a reduced risk. Among participants aged 65–74 years, living with children aged ≤ 6 years was the strongest risk factor, whereas high BMI and the presence of gastrointestinal disease were associated with a significantly reduced risk of CAP. In contrast, among those aged ≥ 75 years, underlying respiratory comorbidities, specifically COPD and bronchial asthma, and impaired ADL emerged as independent risk factors for CAP. Furthermore, living with children aged ≤ 6 years remained a potent risk factor in this older age group and was a significant risk factor for pneumococcal pneumonia. These findings suggest that although intergenerational transmission remains a critical pathway regardless of age, the contribution of respiratory comorbidities and functional decline becomes increasingly important as risk factors in individuals aged ≥ 75 years. One of the key findings of this study is the strong association between living with children aged ≤ 6 years and the risk of pneumonia in older adults, consistent with previous reports [ 8 ]. Notably, this association was observed consistently across both age subgroups (65–74 years and ≥ 75 years) and remained significant in the subgroup analysis limited to pneumococcal pneumonia, despite the limited sample size. This finding suggests that the risk posed by contact with young children persists in the post-PCV13 era and is likely driven by mechanisms beyond direct pneumococcal transmission alone. Although non-vaccine serotypes or persistent vaccine serotypes (e.g., serotype 3, 19A) of Streptococcus pneumoniae may still circulate [ 22 ], the transmission of respiratory viruses from children to older adults likely plays a pivotal role [ 23 ]. Children frequently serve as reservoirs for respiratory viruses such as respiratory syncytial virus, influenza, and rhinovirus [ 23 , 24 ]. Transmission of these viruses to older household members can damage the respiratory mucosal barrier and impair mucociliary clearance [ 25 , 26 ]. This virus-induced damage modulates local immune responses and significantly increases susceptibility to secondary bacterial superinfections, specifically pneumococcal pneumonia [ 27 ]. Thus, even if pediatric pneumococcal carriage has decreased due to vaccination with PCV13, the transmission of respiratory viruses by children may continue to drive the incidence of pneumococcal pneumonia in older adults through viral-bacterial synergism. Our findings highlight the important role of intergenerational transmission of infectious pathogens even in the post-PCV13 era, indicating an ongoing need for prevention strategies in households with children and older adults. Impaired ADL status was also independently associated with an increased risk of pneumonia. This observation aligns with recent systematic reviews demonstrating that functional impairment—such as low or intermediate levels of dependence (defined as a Barthel Index < 100), incontinence, mobility limitations, and being bedridden—is a risk factor for pneumonia [ 9 ]. Potential explanations include reduced physical activity leading to respiratory muscle weakness, impaired airway clearance, and decreased pulmonary ventilation efficiency [ 28 ]. Moreover, subtle, unnoticed micro-aspiration events, facilitated by weakened pharyngeal musculature and poor oral hygiene, may alter pulmonary microbiota, enhancing vulnerability to pneumonia [ 29 , 30 ]. Although clinically diagnosed aspiration pneumonia (e.g., caused by inhalation during eating or vomiting) was among the exclusion criteria in this study, undiagnosed, subclinical micro-aspiration might have contributed to the elevated CAP risk observed among individuals with impaired ADL [ 31 ]. Therefore, our study reinforces the importance of maintaining functional independence and implementing interventions such as swallowing rehabilitation and good oral hygiene to reduce aspiration-related pneumonia among older adults. Our results further revealed that a BMI below 18.5 kg/m² was associated with a significantly increased risk of pneumonia in older adults. Similar to previous findings, low BMI may reflect inadequate nutrition and diminished immune function [ 32 ], as well as reduced respiratory muscle strength needed to clear secretions effectively [ 33 ]. Conversely, BMI ≥ 25.0 kg/m² was associated with lower odds of CAP in our analysis. Evidence regarding BMI and CAP incidence is mixed, and a meta-analysis suggests a J-shaped association, with increased risk among underweight individuals and little or no clear protection in obesity; overweight may be similar to, or slightly lower than, normal weight in the context of CAP risk [ 34 ]. Given that the BMI threshold of 25 kg/m² in Japan largely corresponds to “overweight” in many Western studies [ 35 ], our finding may reflect lower frailty and better nutritional reserve in mildly overweight older adults rather than a direct protective effect of adiposity. Importantly, several studies have reported an “obesity paradox” for outcomes among patients hospitalized with CAP (e.g., lower mortality in overweight/obese patients) [ 36 ], but these prognostic associations should not be conflated with the risk of developing CAP. In the age-stratified analyses, respiratory comorbidities such as COPD and bronchial asthma were independently associated with CAP only among participants aged ≥ 75 years. This pattern is biologically plausible: immunosenescence and age-related inflammation intensify with advancing age, weakening mucosal and innate defenses and magnifying the impact of chronic airway inflammation on infection risk [ 37 ]. Specifically for COPD, older adults are likely to have more advanced disease with greater structural lung damage and reduced pulmonary reserve compared with that of younger adults, making them more susceptible to pneumonia progression. Moreover, asthma and severe COPD have been linked to an increased risk of pneumococcal disease and CAP in adults [ 9 , 38 ]. The risk may be further influenced by long-term exposure to inhaled corticosteroids (ICS), often prescribed for asthma or severe COPD, which increase susceptibility to pneumonia in a dose-dependent manner [ 39 ]. Consequently, the interplay between advanced age, disease severity, and ICS use likely increase the risk associated with these respiratory conditions, specifically in the older age stratum. An alternative explanation is limited power and confounding in the younger age stratum, in which strong predictors such as low BMI and impaired ADL may have attenuated the associations with other respiratory conditions observed. These age-specific findings highlight the need to prioritize infection-prevention strategies in older adults with COPD and asthma [ 11 ], including vaccination, careful stewardship of high-dose ICS when feasible [ 39 ]. In the present study, the presence of gastrointestinal disease was associated with a reduced risk of CAP among participants aged 65–74 years. This finding contrasts with those of previous studies that have identified gastrointestinal disorders, particularly gastroesophageal reflux disease [ 40 ] and the use of gastric acid-suppressants [ 9 ] as risk factors for CAP. Because this inverse association was observed only in the 65–74-years age group and was not present in the overall analysis or among those aged ≥ 75 years, it may reflect differences in healthcare utilization patterns among hospital outpatients rather than a biological protective effect. Controls were recruited from outpatients visiting the same medical institutions as did the cases, predominantly from hospital-based internal medicine departments or clinics; thus, conditions requiring regular follow-up, including chronic gastrointestinal diseases, may have been overrepresented in the control group relative to their occurrence in the general population. Furthermore, the definition of gastrointestinal disease was based on self-reports, and data regarding specific diagnoses and medication use, including the use of gastric acid-suppressants, were not available. Consequently, this variable does not necessarily reflect exposure to potent gastric acid-suppressants, which is a known risk factor for CAP [ 9 ]. Consequently, this finding should be considered exploratory and interpreted with caution. This study highlights critical points for clinical and public health strategies. Nutritional screening and intervention programs for undernourished older adults may be important, given their potential to enhance immunity and reduce pneumonia risk. Further, targeted infection control measures within intergenerational households—such as improved hand hygiene, respiratory etiquette, and isolation strategies when young children exhibit respiratory signs—should be considered. Pneumonia prevention is especially important for adults with COPD or asthma aged ≥ 75 years. Finally, continued surveillance of pneumococcal serotypes and the promotion of appropriate adult pneumococcal vaccination strategies remain essential to minimize risks from Streptococcus pneumoniae serotypes not covered by pediatric PCV13. This study has several limitations. First, although we have adjusted for known confounders, caution must be exercised when making causal inferences owing to the potential for reverse causality. For example, the observed association with low BMI might reflect weight loss resulting from pre-existing frailty or subclinical conditions rather than being a primary cause of pneumonia. Additionally, the reliance on self-reported questionnaires for vaccination history and lifestyle factors may have introduced recall bias. Second, the sample size of 142 cases and 596 controls might not have provided sufficient statistical power to identify some associations. For example, COPD was not significantly associated with CAP in the overall analysis, with the lower limit of the 95% CI falling slightly below 1.0 (adjusted OR 1.69, 95% CI 0.92–3.08), although its association with CAP was statistically significant in the subgroup aged ≥ 75 years. This lack of a statistically significant association between COPD and CAP might be attributable to limited statistical power. Third, sociodemographic factors such as educational level and economic status were not assessed and could be a source of unmeasured confounding. Fourth, biochemical markers of nutritional status, such as total protein, serum albumin, and hemoglobin, were not available for this analysis. The reliance on BMI as the sole indicator of nutritional status is a limitation. Fifth, the generalizability of our findings may be limited, because the research was conducted solely on data from Japan, and the results may not be generalizable to other countries with different healthcare systems and population characteristics. Moreover, the original study was designed to evaluate the effectiveness of PPSV23 against CAP defined according to the guidelines applicable during the study period. This specific focus and definition led to the exclusion of immunocompromised patients and those with malignant tumors. This, in turn, limits the applicability of our findings to the broader older adult population, particularly those at high risk who were specifically excluded in this study. Future research with more detailed etiological analyses would be beneficial in elucidating the precise pathways that connect the identified risk factors to pneumonia in older adults. Conclusions In conclusion, even after the introduction of pediatric PCV13, living with children aged ≤ 6 years, low BMI, and impaired ADL remain major risk factors for CAP among older adults in Japan. Importantly, our age-stratified analysis revealed distinct risk profiles: although intergenerational transmission was a predominant risk regardless of age, respiratory comorbidities including COPD and asthma and impaired ADL emerged as significant independent risks in individuals aged ≥ 75 years. Conversely, a higher BMI was associated with a reduced risk. These findings highlight the necessity for tailored interventions—including infection control in multigenerational households, nutritional support to maintain adequate BMI, and careful management of respiratory diseases—particularly among those aged ≥ 75 years—and strategies to maintain ADL, to further reduce the pneumonia burden in older adults. Abbreviations ADL Activities of daily living BMI Body mass index CAP Community-acquired pneumonia COPD Chronic obstructive pulmonary disease PCV7 Pneumococcal conjugate vaccine, 7-valent PCV13 Pneumococcal conjugate vaccine, 13-valent PPSV23 Pneumococcal polysaccharide vaccine, 23-valent Declarations Ethics approval and consent to participate Ethical approval for this study was obtained from the central institutional review board at Osaka Metropolitan University (#2023-082). In addition, the study was approved by all participating institutions, Kameda Medical Center, and Nagoya City University. The research adhered to the principles outlined in the Declaration of Helsinki and the Japanese Ethical Guidelines for Medical and Health Research Involving Human Subjects. Because this study was a secondary analysis of de-identified data, the requirement for written informed consent to participate was waived by the central Institutional Review Board of Osaka Metropolitan University, and participants were given the opportunity to opt out of the study through publicly posted study information at each participating institution. Consent for publication Not applicable. Availability of data and materials All datasets generated and analyzed during the study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This study was supported by a grant for Research on Emerging and Re-emerging Infectious Diseases from the Ministry of Health, Labour and Welfare, Japan (grant numbers: 20HA2001 and 24HA2007). Authors’ contributions Conceptualization: NI, KN, KS, KK, SO, and WF. Data curation: NI and KN. Formal analysis: NI and KN. Funding acquisition: WF. Investigation: NI and KN. Methodology: NI, KN, KS, KK, SO, and WF. Project administration: KN and KS. Software: NI, KN, KK, SO, and WF. Supervision: WF. Validation: NI and KN. Visualization: NI and KN. Writing – original draft: NI, KN. Writing – review and editing: KN, KS, HN, TN, CN, NM, SI, SK, KK, SO, and WF. NI and KN contributed equally to this work. All authors read and approved the final manuscript. Acknowledgments We would like to acknowledge the other members of the Pneumonia in Elderly People Study Group, listed as follows with their affiliations: Chiharu Ota, Ikuji Usami, Munehiro Kato (Asahi Rosai Hospital); Kazuhide Yamamoto (Kazu Clinic); Akihiro Shiroshita, Ayumu Otsuki (Kameda Medical Center); Mayumi Murabata (Mie University) ;Hisako Yano (Nagoya City University, School of Nursing, Nagoya, Japan); Atsushi Nakamura (Nagoya City University); Yasuhito Iwashima (Iwashima Clinic); Asuka Nagura, Chizuko Sumida (Inazawa Municipal Hospital); Midori Nishizuka, Chisa Sato, Fumihiro Tsuchida, Hiroaki Takeda (Yamagata Saisei Hospital), Yui Takahashi, Kyoko Murase, Eiyasu Tsuboi (Tsuboi Hospital); Koichi Miyagawa (Miyagawa Clinic); Tomihiro Hayakawa (Asuke Hospital); Satoshi Shiraishi, Sumiyo Nanri (Osaka City Juso Hospital); Akihito Ueda (Fujitate Hospital); Hideyuki Horie, Isao Ito (Sugita Genpaku Memorial Obama Municipal Hospital); Taiga Miyazaki, Kazuhiro Oshima, Tatsuro Hirayama, Hiroshi Mukae (Department of Respiratory Medicine, Nagasaki University Hospital); Misuzu Tsukamoto, Yasuhito Higashiyama (Hokusho Central Hospital); Shin Yamashiro, Tomoo Kishaba (Okinawa Chubu Hospital), Junta Tanaka, Toshinori Takada (Uonuma Kikan Hospital), Tomohiro Sakakibara (Tohoku Rosai Hospital); Masaru nishitsuji, Koichi Nishi (Ishikawa Prefectural Central Hospital); Takeshi Terashima (Tokyo Dental College, Ichikawa General Hospital); Koji Kuronuma (Sapporo Medical University); Kazunori Tobino, Kohei Yoshimine (Izuka Hospital), Keiko Sakuragawa, Ryosuke Hirabayashi, Atsushi Nakagawa, Keisuke Tomii (Kobe City Medical Center General Hospital); Kazutaka Nishitarumizu (Imamura General Hospital), Hideki Makino, Takanori Kanematsu (Matsuyama Red Cross Hospital). 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According to the World Health Organization, lower respiratory infections, including CAP, ranked as the fifth leading cause of death and, aside from COVID-19, remained the leading cause of communicable disease death worldwide in 2024 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The high CAP morbidity and mortality rates in older adults has not improved for decades despite advances in medical care such as standardized guidelines, antimicrobial therapy, and prevention measures for high-risk populations [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Evaluating the risk factors for CAP is essential not only for implementing appropriate prevention and management strategies, but also for identifying areas for future pneumonia-related research and for determining key confounders in epidemiological studies, including vaccine studies [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Previous systematic reviews have identified key risk factors for CAP including older age, male sex, smoking, environmental exposures, malnutrition, prior CAP, chronic bronchitis/chronic obstructive pulmonary disease (COPD), asthma, functional impairment, poor oral hygiene, immunosuppressive therapy, and use of gastric acid-suppressing drugs [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVaccination is critical for preventing pneumonia, with pneumococcal vaccination being the main prevention measure against \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e infection [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The 23-valent pneumococcal polysaccharide vaccine (PPSV23) was the first pneumococcal vaccine used globally for older adults, and subsequently the 7-valent and 13-valent pneumococcal conjugate vaccines (PCV7 and PCV13) were introduced for children, with PCV13 later being introduced for adult [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. PCV13 implementation in children has transformed the epidemiology of pneumococcal disease, reducing the incidence of pneumonia in children and adults and causing serotype replacement [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Following the introduction of PCV13 in Japan in November 2013, vaccination coverage in children reached approximately 90% in 2014 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. PCV13 vaccination in children reduces pneumococcal carriage [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and, consequently, transmission to older adults, potentially altering risk factors such as living with young children. However, few studies have examined pneumonia risk factors for CAP in older adults since the introduction of routine pediatric PCV13 vaccination. In Spain PCV13 was approved for children in 2010 but vaccination coverage remained at approximately 50% until 2013. A study conducted in Spain between 2009 and 2010 identified HIV infection, COPD, asthma, smoking, and poor oral hygiene as significant risk factors for CAP in adults [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In Japan, after the introduction of PCV13 vaccination in children in 2013, a claims study using data collected from 2018 to 2022 identified impaired social functioning as a risk factor for adult CAP, although the use of administrative data limited the precision of the estimate [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Additionally, the risk of developing pneumonia has been reported to be higher in adults aged 75 years and older [\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This suggests that, even within the older adult population aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years, the risk may differ between those aged\u0026thinsp;\u0026lt;\u0026thinsp;75 years and those aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years. However, to our knowledge, no study has compared the risks in older adults aged\u0026thinsp;\u0026lt;\u0026thinsp;75 years with those of older adults aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years to evaluate risk factors for pneumonia onset.\u003c/p\u003e \u003cp\u003eOur group conducted a nationwide case-control study between 2016 and 2019 to evaluate the effectiveness of PPSV23 against CAP among older adults in Japan [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], at a time when PPSV23 coverage in older adults was approximately 55% [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and PCV13 coverage in children was approximately 90%. In this case-control study, PPSV23 was not associated with a statistically significant protective effect against CAP, possibly due to serotype replacement owing to pediatric PCV13 use and resulting changes in the serotype distribution [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Using data from this 2016\u0026ndash;2019 study, we performed a secondary analysis to identify risk factors for CAP in older Japanese adults (aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years) after the introduction of pediatric PCV13 and conducted subgroup analyses stratified by age (\u0026lt;\u0026thinsp;75 years and \u0026ge;\u0026thinsp;75 years).\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eStudy design\u003c/h2\u003e\n\u003cp\u003eWe conducted a secondary analysis of data from a nationwide, multicenter, prospective, case-control study conducted in Japan. The original research was a hospital-based matched case-control study carried out from October 1, 2016, to December 31, 2019, at 41 healthcare facilities, which included 30 hospitals and 11 clinics, spread across the Hokkaido, Tohoku, Hokuriku, Kanto, Tokai, Kinki, Shikoku, and Kyushu regions [7]. Cases included in this study were restricted to adults aged 65 years and older who were living at home and developed pneumonia, and the outcomes focused on CAP. Because the cases were patients diagnosed with CAP in outpatient settings, including emergency departments in clinics or hospitals, controls were chosen from outpatients attending the same clinics or hospitals. In October 2014, a national immunization program for PPSV23 targeting individuals aged 65 years and older was launched, with vaccinations provided to eligible participants at local clinics or hospitals. In this program, PPSV23 was administered to adults who reached 65, 70, 75, 80, 85, 90, 95, or 100 years of age within a given fiscal year. As transitional measures, individuals aged \u0026ge;100 years at the end of fiscal year 2013 were additionally eligible in fiscal year 2014 at the time of program introduction. Similarly, those aged \u0026ge;100 years at the end of fiscal year 2018 were eligible in fiscal year 2019 when the transitional measures were extended. Ethical approval for this secondary analysis was obtained from the central institutional review board at Osaka Metropolitan University (#2023-082). In addition, the study was approved by Kameda Medical Center and Nagoya City University, which were participating institutions. The research adhered to the principles outlined in the Declaration of Helsinki. The institutional review board waived the requirement for informed consent, and patients were given the opportunity to opt out of the study.\u003c/p\u003e\n\u003ch2\u003eDefinition of cases and controls\u003c/h2\u003e\n\u003cp\u003eIn the original study [7], conducted between October 1, 2016, and September 30, 2019, individuals aged 65 years and older who were newly diagnosed with CAP at outpatient facilities, including emergency departments, were prospectively enrolled as cases. These patients were registered on the day that they were diagnosed with pneumonia in either the outpatient or emergency department. The physicians at the participating institutions diagnosed pneumonia based on clinical manifestations such as fever, cough, and sputum, along with elevated leukocyte counts or C-reactive protein levels, and the presence of infiltration on chest X-ray or computed tomography. The diagnosis of pneumococcal pneumonia was subsequently confirmed through sputum culture using a semiquantitative method, Gram staining showing Gram-positive cocci in pairs, blood culture, or a positive pneumococcal urinary antigen test. For each case, we recruited up to five controls without pneumonia who visited the same clinics and hospitals, matched by sex, fiscal-year age (corresponding to the age categories of the national immunization program), and visit date (within 3 months of confirmation of the corresponding case). The exclusion criteria for both cases and controls included residing in a nursing home, having aspiration pneumonia (caused by inhalation during eating or vomiting), having malignant tumors, taking oral steroids or immunosuppressants, or having a history of splenectomy. Patients with malignancies were excluded owing to potential immunosuppression. To minimize overrepresentation in the number of cases at some facilities, each facility was limited to enrolling a maximum of five matched sets (five cases and 25 controls) per year.\u003c/p\u003e\n\u003ch2\u003eData collection\u003c/h2\u003e\n\u003cp\u003eFor current analysis, we extracted variables collected in the original study [7].\u0026nbsp;In the original study, the attending physician gathered clinical details on both cases and controls using a structured questionnaire, which included information on: a) self-reported age, sex, date of birth, presence or absence of underlying respiratory diseases (such as chronic bronchitis, pulmonary emphysema, interstitial pneumonia, asthma, pulmonary tuberculosis sequelae, or other respiratory diseases), and vaccination history (dates of PPSV23, PCV13, and influenza vaccine administration); b) pneumonia-specific information (for cases only), such as the date of diagnosis, clinical manifestations, laboratory data related to the pneumonia diagnosis (leukocyte count and C-reactive protein levels), and results from diagnostic tests (pneumococcal urinary antigen test and sputum culture). Additionally, we extracted data from a self-administered questionnaire that study participants or their next of kin were asked to fill out. This questionnaire included details regarding their status at the time of enrollment, such as height, body weight, living with children aged under 6 years old, activities of daily living (ADL; bedridden, semi-bedridden, semi-self-supported, or self-supported), presence or absence of underlying diseases (hypertension, dyslipidemia, chronic kidney disease, heart disease, stroke, diabetes mellitus, liver disease, or gastrointestinal disease), alcohol use history (never, past, occasionally, or daily), smoking history (never smoker, past smoker, or current smoker) and vaccination status (PPSV23 in the past 5 years and influenza vaccination in the past 6 months).\u0026nbsp;Both the physician-administered questionnaire and the self-administered questionnaire were developed specifically for the original study\u0026nbsp;[7]\u0026nbsp;and have not been published elsewhere. An English-language version of the questionnaires is provided in Supplementary Material 1. Pneumococcal vaccination status (i.e., vaccinated or unvaccinated) and the specific vaccine type were determined using information from two sources: data gathered by the attending physician and data reported by the participant or their next of kin. A participant was classified as \u0026ldquo;vaccinated\u0026rdquo; if either source indicated a history of vaccination, irrespective of the date of administration. For those classified as vaccinated, the specific vaccine type administered (e.g., PPSV23, PCV13) was determined primarily based on the physician\u0026apos;s records. Influenza vaccination status was determined primarily from the information given in participant\u0026rsquo;s self-administered questionnaire. When vaccination status within the past 6 months was unclear, physician\u0026rsquo;s records were used for verification. Participants were classified as vaccinated if either source indicated influenza vaccination within 6 months prior to the case\u0026rsquo;s diagnosis date or the control\u0026rsquo;s enrollment date.\u003c/p\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eIn this secondary analysis, participants with any missing data were excluded using listwise deletion. All underlying diseases were categorized as either present or absent, whereas ADL status was classified as either \u0026ldquo;not independent\u0026rdquo; (bedridden, semi-bedridden, or semi-self-supported) or \u0026ldquo;independent\u0026rdquo; (self-supported) for the purpose of analysis. Body mass index (BMI) was divided into three categories: \u0026lt;18.5, 18.5\u0026ndash;24.9, and\u0026nbsp;\u0026ge;25.0 kg/m\u003csup\u003e2\u003c/sup\u003e. The Wilcoxon rank-sum test, Chi-square test, and Fisher\u0026rsquo;s exact test were used to assess the statistical significance of differences between the case and control groups, as appropriate. Conditional logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for each factor associated with pneumonia. Both crude and adjusted ORs were estimated. Adjustment variables included established risk factors for pneumonia (smoking, COPD, asthma, diabetes mellitus, ADL) [8, 9], variables with p \u0026lt; 0.20 in the comparison of baseline characteristics, and history of pneumococcal and influenza vaccination. Subgroup analyses stratified by fiscal-year age (\u0026lt;75 years and \u0026ge;75 years) were also conducted using conditional logistic regression. While fiscal-year age was used for stratification to maintain the validity of the conditional logistic model in accordance with the matching criteria, chronological age was reported in the results for intuitive interpretation. The same adjustment variables as in the overall analysis were used in all subgroup models. Finally, we performed an additional conditional logistic regression analysis limited to cases with pneumococcal pneumonia. This analysis was conducted because children routinely receive PCV13, which reduces pneumococcal carriage in this population and thereby limits transmission of Streptococcus pneumoniae to older adults; consequently, the impact of living with children aged \u0026le;6 years may be attenuated when focusing specifically on pneumococcal pneumonia. Although the same adjustment variables were used as in the primary model, variables with zero events in at least one group (i.e., gastrointestinal disease and liver disease) were excluded to avoid quasi-complete separation and to ensure model stability. All statistical analyses were performed using SAS version 9.3 (SAS Institute, Inc., Cary, NC, USA), with statistical significance set at p \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the flow of study participants. Of the 797 eligible participants (159 cases and 638 controls), 59 were excluded from the analysis due to missing data or a lack of matched controls, leaving 738 participants (142 cases and 596 controls) included in the analysis of risk factors for all-cause CAP. Among the cases, 102 were recruited from hospital-based internal medicine departments, 39 from clinics, and 1 from an unspecified department within a hospital. Among the controls, 342 were enrolled from hospital-based internal medicine departments, 185 from clinics, and 69 from non-internal medicine or unspecified departments of hospitals, including orthopedics (n\u0026thinsp;=\u0026thinsp;25), ophthalmology (n\u0026thinsp;=\u0026thinsp;10), otorhinolaryngology (n\u0026thinsp;=\u0026thinsp;6), dermatology (n\u0026thinsp;=\u0026thinsp;4), urology (n\u0026thinsp;=\u0026thinsp;3), surgery (n\u0026thinsp;=\u0026thinsp;2), gynecology (n\u0026thinsp;=\u0026thinsp;1), and unspecified (n\u0026thinsp;=\u0026thinsp;18) departments. This analysis population was stratified into two subgroups based on fiscal-year age: the subgroup aged 65\u0026ndash;74 years (N\u0026thinsp;=\u0026thinsp;390) included 74 cases and 316 controls, and the subgroup aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years (N\u0026thinsp;=\u0026thinsp;348) included 68 cases and 280 controls. Additionally, 174 participants, comprising 31 cases and 143 controls were included in the analysis of risk factors for pneumococcal CAP.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the baseline characteristics of all participants. The median age was 75 years in both the case and control groups. The proportion of male participants was 56% in the case group and 53% in the control group. The case and control groups had similar influenza vaccination (42% vs. 44%, respectively; p\u0026thinsp;=\u0026thinsp;0.603) and pneumococcal vaccination (58% vs. 56%, respectively; p\u0026thinsp;=\u0026thinsp;0.603) coverage. Among underlying medical conditions, COPD was significantly more prevalent in the case group (24% vs. 14%; p\u0026thinsp;=\u0026thinsp;0.003), whereas dyslipidemia was more prevalent in the control group (19% vs. 29%; p\u0026thinsp;=\u0026thinsp;0.014). Additionally, the proportion of participants with a low BMI (\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;) was significantly higher in the case group than in the control group (23% vs. 11%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Cases were also more likely to living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years (15% vs. 3%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and to have impaired ADL (defined as \u0026ldquo;not independent\u0026rdquo;) (10% vs. 5%; p\u0026thinsp;=\u0026thinsp;0.014). Alcohol consumption and the prevalence of diabetes mellitus did not differ significantly between the case and the control groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant baseline characteristics (N\u0026thinsp;=\u0026thinsp;738)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCases\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;596)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years),\u003csup\u003ea\u003c/sup\u003e median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (70\u0026ndash;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (70\u0026ndash;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e315 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e281 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePneumococcal vaccine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e334 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPSV23 only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e310 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCV13 only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfluenza vaccine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e262 (44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterstitial pneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBronchial asthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTuberculosis (sequelae)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderlying diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e320 (54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138 (23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.5\u0026ndash;24.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e372 (62%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 (27%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121 (85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e580 (97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivities of daily living\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128 (90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e569 (95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot independent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol use history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever/Past\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374 (63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102 (17%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 (20%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e343 (58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePast smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205 (34%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ea\u003c/sup\u003e Age indicates chronological age at the time of diagnosis or enrollment.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003eb\u003c/sup\u003e The p values were calculated using the Wilcoxon rank-sum test, chi-square test, or Fisher\u0026rsquo;s exact test, as appropriate.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eBMI, body mass index; COPD, chronic obstructive lung disease; IQR, interquartile range.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the ORs for CAP. In the unstratified adjusted analysis, low BMI (\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;; adjusted OR [aOR] 1.78, 95% CI, 1.02\u0026ndash;3.09), living with children aged\u0026thinsp;\u0026ge;\u0026thinsp;6 years (aOR 6.15, 95% CI, 2.84\u0026ndash;13.32), and impaired ADL (aOR 2.44, 95% CI, 1.12\u0026ndash;5.30) were significantly associated with an increased risk of pneumonia, whereas a high BMI (\u0026ge;\u0026thinsp;25.0 kg/m\u0026sup2;) was associated with a decreased risk (aOR 0.55, 95% CI, 0.31\u0026ndash;0.95).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk factors for community-acquired pneumonia in older adults overall and by age group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eOverall (65\u0026thinsp;\u0026ge;\u0026thinsp;years) (N\u0026thinsp;=\u0026thinsp;738)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e65\u0026ndash;74 years (N\u0026thinsp;=\u0026thinsp;390)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;75 years (N\u0026thinsp;=\u0026thinsp;348)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude OR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted OR*\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCrude OR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdjusted OR*\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCrude OR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAdjusted OR*\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.91 (1.13\u0026ndash;3.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.69 (0.92\u0026ndash;3.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.60 (0.82\u0026ndash;3.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.33 (0.61\u0026ndash;2.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.51 (1.09\u0026ndash;5.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.59 (1.29\u0026ndash;9.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBronchial asthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.45 (0.86\u0026ndash;2.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.37 (0.78\u0026ndash;2.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99 (0.47\u0026ndash;2.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.71 (0.31\u0026ndash;1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.22 (1.05\u0026ndash;4.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.99 (1.25\u0026ndash;7.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTuberculosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.68 (0.86\u0026ndash;8.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.40 (0.71\u0026ndash;8.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.67 (0.17\u0026ndash;16.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.11 (0.18\u0026ndash;25.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.23 (0.85\u0026ndash;12.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.21 (0.50\u0026ndash;9.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.76 (0.51\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85 (0.55\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.75 (0.44\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.86 (0.47\u0026ndash;1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.77 (0.43\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.94 (0.47\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.59 (0.35\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78 (0.45\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52 (0.26\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.66 (0.31\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.67 (0.32\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.83 (0.36\u0026ndash;1.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.04 (0.67\u0026ndash;1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.36 (0.84\u0026ndash;2.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80 (0.43\u0026ndash;1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.05 (0.52\u0026ndash;2.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.36 (0.74\u0026ndash;2.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.82 (0.90\u0026ndash;3.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.58 (0.30\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.59 (0.29\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27 (0.07\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19 (0.04\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.84 (0.39\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.11 (0.46\u0026ndash;2.68)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.41 (0.12\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.37 (0.10\u0026ndash;1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22 (0.03\u0026ndash;1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14 (0.02\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.74 (0.15\u0026ndash;3.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.78 (0.15\u0026ndash;4.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.12 (1.29\u0026ndash;3.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.78 (1.02\u0026ndash;3.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.90 (0.93\u0026ndash;3.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.59 (0.69\u0026ndash;3.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.34 (1.18\u0026ndash;4.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.97 (0.86\u0026ndash;4.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.5\u0026ndash;24.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.55 (0.32\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.55 (0.31\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.43 (0.21\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41 (0.18\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.73 (0.34\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.58 (0.25\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.66 (3.23\u0026ndash;13.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.15 (2.84\u0026ndash;13.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.53 (2.54\u0026ndash;16.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.89 (1.83\u0026ndash;13.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.85 (2.22\u0026ndash;21.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.62 (3.12\u0026ndash;43.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivities of daily living\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot independent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.12 (1.04\u0026ndash;4.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.44 (1.12\u0026ndash;5.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.51 (0.68\u0026ndash;9.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.86 (0.78\u0026ndash;19.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.98 (0.85\u0026ndash;4.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.90 (1.10\u0026ndash;7.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePast smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15 (0.68\u0026ndash;1.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07 (0.59\u0026ndash;1.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.32 (0.66\u0026ndash;2.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.22 (0.56\u0026ndash;2.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.98 (0.42\u0026ndash;2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.73 (0.26\u0026ndash;2.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.84 (0.91\u0026ndash;3.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.58 (0.73\u0026ndash;3.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.43 (0.59\u0026ndash;3.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.11 (0.42\u0026ndash;2.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.98 (0.94\u0026ndash;9.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.40 (0.61\u0026ndash;9.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e*The model incorporated all variables listed in the Table, as well as pneumococcal and influenza vaccination.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eBMI, body mass index; CI, confidence interval; COPD, chronic obstructive lung disease; OR, odds ratio\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNext, we conducted a subgroup analysis stratified by fiscal-year age (\u0026lt;\u0026thinsp;75 years vs. \u0026ge;75 years). In the subgroup of patients aged 65\u0026ndash;74 years (Supplementary Table\u0026nbsp;1), dyslipidemia was less common among cases than among controls (18% vs. 29%; p\u0026thinsp;=\u0026thinsp;0.039). Compared with controls, cases were more likely to have a BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2; (22% vs. 10%; p\u0026thinsp;=\u0026thinsp;0.003) and more likely to be living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years (18% vs. 3%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the subgroup of adults aged 65\u0026ndash;74 years, multivariable analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) showed that living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years was strongly associated with an increased risk of CAP (adjusted OR 4.89, 95% CI 1.83\u0026ndash;13.08). In contrast, gastrointestinal disease (adjusted OR 0.19, 95% CI 0.04\u0026ndash;0.84) and a higher BMI (\u0026ge;\u0026thinsp;25.0 kg/m\u0026sup2;) (adjusted OR 0.41, 95% CI 0.18\u0026ndash;0.89) were both associated with a lower risk of CAP.\u003c/p\u003e \u003cp\u003eIn the subgroup of patients aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years (Supplementary Table\u0026nbsp;2), cases were more likely than controls to have COPD (24% vs. 13%; p\u0026thinsp;=\u0026thinsp;0.021), a BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2; (25% vs. 11%; p\u0026thinsp;=\u0026thinsp;0.012), and to be living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years (12% vs. 2%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the subgroup aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years, multivariable analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) showed that COPD (adjusted OR 3.59, 95% CI 1.29\u0026ndash;9.93), bronchial asthma (adjusted OR 2.99, 95% CI 1.25\u0026ndash;7.16), living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years (adjusted OR 11.62, 95% CI 3.12\u0026ndash;43.33), and impaired ADL (adjusted OR 2.90, 95% CI 1.10\u0026ndash;7.65) were associated with a significantly increased risk of CAP.\u003c/p\u003e \u003cp\u003eThe baseline characteristics of the cases (n\u0026thinsp;=\u0026thinsp;31) with pneumococcal pneumonia and their matched controls (n\u0026thinsp;=\u0026thinsp;143) are shown in Supplementary Table\u0026nbsp;3 and the adjusted ORs for this subgroup are shown in Supplementary Table\u0026nbsp;4. Compared with controls, cases were more likely to be living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years (16% vs. 2%; p\u0026thinsp;=\u0026thinsp;0.005). After adjustment, living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years remained a significant risk factor for pneumococcal CAP (adjusted OR 7.22, 95% CI 1.23\u0026ndash;42.34).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this secondary analysis of a multicenter case-control study conducted in Japan following the introduction of the PCV13 for children, we identified distinct risk factors for CAP among older adults. In all participants, living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years, low BMI, and impaired ADL were associated with an increased risk of CAP, whereas a high BMI was associated with a reduced risk. Among participants aged 65\u0026ndash;74 years, living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years was the strongest risk factor, whereas high BMI and the presence of gastrointestinal disease were associated with a significantly reduced risk of CAP. In contrast, among those aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years, underlying respiratory comorbidities, specifically COPD and bronchial asthma, and impaired ADL emerged as independent risk factors for CAP. Furthermore, living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years remained a potent risk factor in this older age group and was a significant risk factor for pneumococcal pneumonia. These findings suggest that although intergenerational transmission remains a critical pathway regardless of age, the contribution of respiratory comorbidities and functional decline becomes increasingly important as risk factors in individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years.\u003c/p\u003e \u003cp\u003eOne of the key findings of this study is the strong association between living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years and the risk of pneumonia in older adults, consistent with previous reports [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Notably, this association was observed consistently across both age subgroups (65\u0026ndash;74 years and \u0026ge;\u0026thinsp;75 years) and remained significant in the subgroup analysis limited to pneumococcal pneumonia, despite the limited sample size. This finding suggests that the risk posed by contact with young children persists in the post-PCV13 era and is likely driven by mechanisms beyond direct pneumococcal transmission alone. Although non-vaccine serotypes or persistent vaccine serotypes (e.g., serotype 3, 19A) of \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e may still circulate [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], the transmission of respiratory viruses from children to older adults likely plays a pivotal role [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Children frequently serve as reservoirs for respiratory viruses such as respiratory syncytial virus, influenza, and rhinovirus [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Transmission of these viruses to older household members can damage the respiratory mucosal barrier and impair mucociliary clearance [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This virus-induced damage modulates local immune responses and significantly increases susceptibility to secondary bacterial superinfections, specifically pneumococcal pneumonia [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Thus, even if pediatric pneumococcal carriage has decreased due to vaccination with PCV13, the transmission of respiratory viruses by children may continue to drive the incidence of pneumococcal pneumonia in older adults through viral-bacterial synergism. Our findings highlight the important role of intergenerational transmission of infectious pathogens even in the post-PCV13 era, indicating an ongoing need for prevention strategies in households with children and older adults.\u003c/p\u003e \u003cp\u003eImpaired ADL status was also independently associated with an increased risk of pneumonia. This observation aligns with recent systematic reviews demonstrating that functional impairment\u0026mdash;such as low or intermediate levels of dependence (defined as a Barthel Index\u0026thinsp;\u0026lt;\u0026thinsp;100), incontinence, mobility limitations, and being bedridden\u0026mdash;is a risk factor for pneumonia [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Potential explanations include reduced physical activity leading to respiratory muscle weakness, impaired airway clearance, and decreased pulmonary ventilation efficiency [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Moreover, subtle, unnoticed micro-aspiration events, facilitated by weakened pharyngeal musculature and poor oral hygiene, may alter pulmonary microbiota, enhancing vulnerability to pneumonia [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Although clinically diagnosed aspiration pneumonia (e.g., caused by inhalation during eating or vomiting) was among the exclusion criteria in this study, undiagnosed, subclinical micro-aspiration might have contributed to the elevated CAP risk observed among individuals with impaired ADL [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Therefore, our study reinforces the importance of maintaining functional independence and implementing interventions such as swallowing rehabilitation and good oral hygiene to reduce aspiration-related pneumonia among older adults.\u003c/p\u003e \u003cp\u003eOur results further revealed that a BMI below 18.5 kg/m\u0026sup2; was associated with a significantly increased risk of pneumonia in older adults. Similar to previous findings, low BMI may reflect inadequate nutrition and diminished immune function [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], as well as reduced respiratory muscle strength needed to clear secretions effectively [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Conversely, BMI\u0026thinsp;\u0026ge;\u0026thinsp;25.0 kg/m\u0026sup2; was associated with lower odds of CAP in our analysis. Evidence regarding BMI and CAP incidence is mixed, and a meta-analysis suggests a J-shaped association, with increased risk among underweight individuals and little or no clear protection in obesity; overweight may be similar to, or slightly lower than, normal weight in the context of CAP risk [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Given that the BMI threshold of 25 kg/m\u0026sup2; in Japan largely corresponds to \u0026ldquo;overweight\u0026rdquo; in many Western studies [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], our finding may reflect lower frailty and better nutritional reserve in mildly overweight older adults rather than a direct protective effect of adiposity. Importantly, several studies have reported an \u0026ldquo;obesity paradox\u0026rdquo; for outcomes among patients hospitalized with CAP (e.g., lower mortality in overweight/obese patients) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], but these prognostic associations should not be conflated with the risk of developing CAP.\u003c/p\u003e \u003cp\u003eIn the age-stratified analyses, respiratory comorbidities such as COPD and bronchial asthma were independently associated with CAP only among participants aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years. This pattern is biologically plausible: immunosenescence and age-related inflammation intensify with advancing age, weakening mucosal and innate defenses and magnifying the impact of chronic airway inflammation on infection risk [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Specifically for COPD, older adults are likely to have more advanced disease with greater structural lung damage and reduced pulmonary reserve compared with that of younger adults, making them more susceptible to pneumonia progression. Moreover, asthma and severe COPD have been linked to an increased risk of pneumococcal disease and CAP in adults [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The risk may be further influenced by long-term exposure to inhaled corticosteroids (ICS), often prescribed for asthma or severe COPD, which increase susceptibility to pneumonia in a dose-dependent manner [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Consequently, the interplay between advanced age, disease severity, and ICS use likely increase the risk associated with these respiratory conditions, specifically in the older age stratum. An alternative explanation is limited power and confounding in the younger age stratum, in which strong predictors such as low BMI and impaired ADL may have attenuated the associations with other respiratory conditions observed. These age-specific findings highlight the need to prioritize infection-prevention strategies in older adults with COPD and asthma [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], including vaccination, careful stewardship of high-dose ICS when feasible [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, the presence of gastrointestinal disease was associated with a reduced risk of CAP among participants aged 65\u0026ndash;74 years. This finding contrasts with those of previous studies that have identified gastrointestinal disorders, particularly gastroesophageal reflux disease [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and the use of gastric acid-suppressants [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] as risk factors for CAP. Because this inverse association was observed only in the 65\u0026ndash;74-years age group and was not present in the overall analysis or among those aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years, it may reflect differences in healthcare utilization patterns among hospital outpatients rather than a biological protective effect. Controls were recruited from outpatients visiting the same medical institutions as did the cases, predominantly from hospital-based internal medicine departments or clinics; thus, conditions requiring regular follow-up, including chronic gastrointestinal diseases, may have been overrepresented in the control group relative to their occurrence in the general population. Furthermore, the definition of gastrointestinal disease was based on self-reports, and data regarding specific diagnoses and medication use, including the use of gastric acid-suppressants, were not available. Consequently, this variable does not necessarily reflect exposure to potent gastric acid-suppressants, which is a known risk factor for CAP [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Consequently, this finding should be considered exploratory and interpreted with caution.\u003c/p\u003e \u003cp\u003eThis study highlights critical points for clinical and public health strategies. Nutritional screening and intervention programs for undernourished older adults may be important, given their potential to enhance immunity and reduce pneumonia risk. Further, targeted infection control measures within intergenerational households\u0026mdash;such as improved hand hygiene, respiratory etiquette, and isolation strategies when young children exhibit respiratory signs\u0026mdash;should be considered. Pneumonia prevention is especially important for adults with COPD or asthma aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years. Finally, continued surveillance of pneumococcal serotypes and the promotion of appropriate adult pneumococcal vaccination strategies remain essential to minimize risks from \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e serotypes not covered by pediatric PCV13.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, although we have adjusted for known confounders, caution must be exercised when making causal inferences owing to the potential for reverse causality. For example, the observed association with low BMI might reflect weight loss resulting from pre-existing frailty or subclinical conditions rather than being a primary cause of pneumonia. Additionally, the reliance on self-reported questionnaires for vaccination history and lifestyle factors may have introduced recall bias. Second, the sample size of 142 cases and 596 controls might not have provided sufficient statistical power to identify some associations. For example, COPD was not significantly associated with CAP in the overall analysis, with the lower limit of the 95% CI falling slightly below 1.0 (adjusted OR 1.69, 95% CI 0.92\u0026ndash;3.08), although its association with CAP was statistically significant in the subgroup aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years. This lack of a statistically significant association between COPD and CAP might be attributable to limited statistical power. Third, sociodemographic factors such as educational level and economic status were not assessed and could be a source of unmeasured confounding. Fourth, biochemical markers of nutritional status, such as total protein, serum albumin, and hemoglobin, were not available for this analysis. The reliance on BMI as the sole indicator of nutritional status is a limitation. Fifth, the generalizability of our findings may be limited, because the research was conducted solely on data from Japan, and the results may not be generalizable to other countries with different healthcare systems and population characteristics. Moreover, the original study was designed to evaluate the effectiveness of PPSV23 against CAP defined according to the guidelines applicable during the study period. This specific focus and definition led to the exclusion of immunocompromised patients and those with malignant tumors. This, in turn, limits the applicability of our findings to the broader older adult population, particularly those at high risk who were specifically excluded in this study. Future research with more detailed etiological analyses would be beneficial in elucidating the precise pathways that connect the identified risk factors to pneumonia in older adults.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, even after the introduction of pediatric PCV13, living with children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years, low BMI, and impaired ADL remain major risk factors for CAP among older adults in Japan. Importantly, our age-stratified analysis revealed distinct risk profiles: although intergenerational transmission was a predominant risk regardless of age, respiratory comorbidities including COPD and asthma and impaired ADL emerged as significant independent risks in individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years. Conversely, a higher BMI was associated with a reduced risk. These findings highlight the necessity for tailored interventions\u0026mdash;including infection control in multigenerational households, nutritional support to maintain adequate BMI, and careful management of respiratory diseases\u0026mdash;particularly among those aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years\u0026mdash;and strategies to maintain ADL, to further reduce the pneumonia burden in older adults.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eADL Activities of daily living\u003c/p\u003e\n\u003cp\u003eBMI Body mass index\u003c/p\u003e\n\u003cp\u003eCAP Community-acquired pneumonia\u003c/p\u003e\n\u003cp\u003eCOPD Chronic obstructive pulmonary disease\u003c/p\u003e\n\u003cp\u003ePCV7 Pneumococcal conjugate vaccine, 7-valent\u003c/p\u003e\n\u003cp\u003ePCV13 Pneumococcal conjugate vaccine, 13-valent\u003c/p\u003e\n\u003cp\u003ePPSV23 Pneumococcal polysaccharide vaccine, 23-valent\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eEthical approval for this study was obtained from the central institutional review board at Osaka Metropolitan University (#2023-082). In addition, the study was approved by all participating institutions, Kameda Medical Center, and Nagoya City University. The research adhered to the principles outlined in the Declaration of Helsinki and the Japanese Ethical Guidelines for Medical and Health Research Involving Human Subjects. Because this study was a secondary analysis of de-identified data, the requirement for written informed consent to participate was waived by the central Institutional Review Board of Osaka Metropolitan University, and participants were given the opportunity to opt out of the study through publicly posted study information at each participating institution.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eAll datasets generated and analyzed during the study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was supported by a grant for Research on Emerging and Re-emerging Infectious Diseases from the Ministry of Health, Labour and Welfare, Japan (grant numbers: 20HA2001 and 24HA2007).\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e\n\u003cp\u003eConceptualization: NI, KN, KS, KK, SO, and WF. Data curation: NI and KN. Formal analysis: NI and KN. Funding acquisition: WF. Investigation: NI and KN. Methodology: NI, KN, KS, KK, SO, and WF. Project administration:\u0026nbsp;KN and KS. Software: NI, KN, KK, SO, and WF. Supervision: WF. Validation: NI and KN. Visualization:\u0026nbsp;NI and\u0026nbsp;KN. Writing \u0026ndash; original draft:\u0026nbsp;NI, KN. Writing \u0026ndash; review and editing: KN, KS, HN, TN, CN, NM, SI, SK, KK, SO, and WF. NI and KN contributed equally to this work. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eWe would like to acknowledge the other members of the Pneumonia in Elderly People Study Group, listed as follows with their affiliations: Chiharu Ota, Ikuji Usami, Munehiro Kato (Asahi Rosai Hospital); Kazuhide Yamamoto (Kazu Clinic); Akihiro Shiroshita, Ayumu Otsuki (Kameda Medical Center); Mayumi Murabata (Mie University) ;Hisako Yano (Nagoya City University, School of Nursing, Nagoya, Japan); Atsushi Nakamura (Nagoya City University); Yasuhito Iwashima (Iwashima Clinic); Asuka Nagura, Chizuko Sumida (Inazawa Municipal Hospital); Midori Nishizuka, Chisa Sato, Fumihiro Tsuchida, Hiroaki Takeda (Yamagata Saisei Hospital), Yui Takahashi, Kyoko Murase, Eiyasu Tsuboi (Tsuboi Hospital); Koichi Miyagawa (Miyagawa Clinic); Tomihiro Hayakawa (Asuke Hospital); Satoshi Shiraishi, Sumiyo Nanri (Osaka City Juso Hospital); Akihito Ueda (Fujitate Hospital); Hideyuki Horie, Isao Ito (Sugita Genpaku Memorial Obama Municipal Hospital); Taiga Miyazaki, Kazuhiro Oshima, Tatsuro Hirayama, Hiroshi Mukae (Department of Respiratory Medicine, Nagasaki University Hospital); Misuzu Tsukamoto, Yasuhito Higashiyama (Hokusho Central Hospital); Shin Yamashiro, Tomoo Kishaba (Okinawa Chubu Hospital), Junta Tanaka, Toshinori Takada (Uonuma Kikan Hospital), Tomohiro Sakakibara (Tohoku Rosai Hospital); Masaru nishitsuji, Koichi Nishi (Ishikawa Prefectural Central Hospital); Takeshi Terashima (Tokyo Dental College, Ichikawa General Hospital); Koji Kuronuma (Sapporo Medical University); Kazunori Tobino, Kohei Yoshimine (Izuka Hospital), Keiko Sakuragawa, Ryosuke Hirabayashi, Atsushi Nakagawa, Keisuke Tomii (Kobe City Medical Center General Hospital); Kazutaka Nishitarumizu (Imamura General Hospital), Hideki Makino, Takanori Kanematsu (Matsuyama Red Cross Hospital).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVaughn VM, Dickson RP, Horowitz JK, Flanders SA: \u003cstrong\u003eCommunity-Acquired Pneumonia: A Review\u003c/strong\u003e. \u003cem\u003eJama \u003c/em\u003e2024, \u003cstrong\u003e332\u003c/strong\u003e(15):1282-1295.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eWorld Health Organization. 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Although the introduction of pediatric 13-valent pneumococcal conjugate vaccine (PCV13) has altered the epidemiology of pneumococcal disease in children, risk factors for CAP in older adults remain insufficiently explored. Additionally, few studies have compared risks between those aged 65\u0026ndash;74 and \u0026ge;\u0026thinsp;75 years. We evaluated risk factors for CAP in older Japanese adults by age.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a secondary analysis of a multicenter, nationwide case-control study between October 2016 and December 2019. Cases were individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years with CAP. Up to five controls were selected per case, matched by sex, fiscal-year age, and visit date. Clinical and lifestyle data were collected via questionnaires. Adjusted odds ratios (aORs) were calculated for participants overall and stratified by age (65\u0026ndash;74 and \u0026ge;\u0026thinsp;75 years) using conditional logistic regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAnalysis included 142 cases and 596 controls. CAP risk was associated with living with children\u0026thinsp;\u0026le;\u0026thinsp;6 years (aOR: 6.15, 95% confidence interval [CI]: 2.84\u0026ndash;13.32), low body mass index (BMI) (\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;) (aOR: 1.78, 95% CI: 1.02\u0026ndash;3.09), and impaired activities of daily living (ADL) (aOR: 2.44, 95% CI: 1.12\u0026ndash;5.30). High BMI (\u0026ge;\u0026thinsp;25.0 kg/m\u0026sup2;) was associated with a reduced risk (aOR: 0.55, 95% CI: 0.31\u0026ndash;0.95). Among those aged 65\u0026ndash;74 years, living with children\u0026thinsp;\u0026le;\u0026thinsp;6 years (aOR: 4.89, 95% CI: 1.83\u0026ndash;13.08) was a risk factor for CAP, whereas high BMI (aOR: 0.41, 95% CI: 0.18\u0026ndash;0.89) and gastrointestinal disease (aOR: 0.19, 95% CI: 0.04\u0026ndash;0.84) were associated with a reduced risk. Among those aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years, chronic obstructive pulmonary disease (aOR: 3.59, 95% CI: 1.29\u0026ndash;9.93), asthma (aOR: 2.99, 95% CI: 1.25\u0026ndash;7.16), living with children\u0026thinsp;\u0026le;\u0026thinsp;6 years (aOR: 11.62, 95% CI: 3.12\u0026ndash;43.33), and impaired ADL (aOR: 2.90, 95% CI: 1.10\u0026ndash;7.65) were risk factors for CAP.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eLiving with children\u0026thinsp;\u0026le;\u0026thinsp;6 years remains a major CAP risk factor in older adults after the introduction of pediatric PCV13. However, risk factors differ by age. Respiratory comorbidities and functional decline are dominant drivers of CAP in adults aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years. Prevention strategies should be tailored by age.\u003c/p\u003e","manuscriptTitle":"Risk factors for community-acquired pneumonia in older adults in Japan after the introduction of the childhood PCV13","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-29 06:16:26","doi":"10.21203/rs.3.rs-9391522/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-04T07:45:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T06:26:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126669938290591114832303973878604211207","date":"2026-05-01T03:52:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-29T05:13:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"317120820289909101844913398678473379333","date":"2026-04-21T12:26:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-21T10:09:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-20T08:18:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-20T08:16:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-18T00:05:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2026-04-18T00:01:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6f3c51ee-1ecc-47cb-bc22-5894a790ede4","owner":[],"postedDate":"April 29th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-04T07:45:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T06:26:51+00:00","index":44,"fulltext":""},{"type":"reviewerAgreed","content":"126669938290591114832303973878604211207","date":"2026-05-01T03:52:10+00:00","index":42,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T07:54:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-29 06:16:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9391522","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9391522","identity":"rs-9391522","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}