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Abstract

Objective:

Comorbidities and risk factors have a major implication on incidence, complications, mortality, and management of community-acquired pneumonia complications and treatment outcomes. This study attempts to identify the same in the Indian population through a systematic review and meta-analysis.

Methods:

We screened observational studies (between January 1990 and February 2021) that reported potential comorbidities and other factors associated with increased risk of community-acquired pneumonia in the Indian population (⩾12 years) using PubMed, Google Scholar, and manual search. The risk of bias was identified using the Joanna Briggs Institute checklist for prevalence studies. Meta-analysis was conducted by using the random intercept logistic regression model.

Results:

Twenty-three studies were included in this analysis. The most prevalent comorbidities were chronic obstructive pulmonary disease (24.2%; 95% confidence interval: 16.4%–34.2%), hypertension (23.7%; 95% confidence interval: 13.6%–38.1%), and diabetes mellitus (16%; 95% confidence interval: 9.9%–24.7%). The prevalence of community-acquired pneumonia was high in patients with a current or previous history of smoking (51.4%; 95% confidence interval: 42.3%–61%) and advanced age ⩾50 years: (55.8%; 95% confidence interval: 48.4%–62%).

Conclusions:

Comorbid conditions like chronic obstructive pulmonary disease, hypertension, and diabetes mellitus and factors like advanced age and smoking history were common risk factors for community-acquired pneumonia in the Indian population.

Keywords

Community-acquired pneumonia comorbidity risk factor India

Introduction

Community-acquired pneumonia (CAP) is a common infectious disease worldwide. Developing countries, including India, bear a significant brunt of the disease, impacting healthcare. India alone accounts for about one-fourth of the global pneumonia burden, with a case fatality rate (CFR) of 14%–30%.¹

Comorbidities and risk factors have major implications on the incidence, complications, mortality, and management of CAP,² posing significant challenges for clinicians. A study in Europe revealed that comorbid pathologies (chronic respiratory and cardiovascular diseases, dementia, cerebrovascular disease, human immunodeficiency virus (HIV), and chronic renal and liver disease) increase the risk of CAP by 2- to 4-fold. The same study also identified smoking and alcohol abuse as common risk factors associated with the disease.² Similar studies in the United States also reported advancing age as a common risk factor for increased incidence and related mortality.^3,4

In India, there is limited information about the comorbid conditions and risk factors associated with increased risk of CAP. Although a few studies have reported such data, the evidence is scattered, and no comprehensive analysis is available to date.

Our study is the first systematic review and meta-analysis conducted to identify the comorbid conditions and risk factors that increase the risk of CAP in the Indian population. The results of this study would help clinicians implement targeted risk-reduction measures to reduce the disease burden of CAP in the country.

Methods

We conducted this study as per the Preferred Recording Items for Systematic Reviews and Meta-Analysis (PRISMA) statements (S1 PRISMA checklist).⁵ Our study did not require ethical board approval because it did not contain human or animal trials.

Eligibility criteria

We included observational studies (cross-sectional studies and prospective or retrospective cohort studies) on patients with CAP, published in the last 31 years (January 1990–December 2020), that reported comorbidities and/or risk factors associated with CAP in Indian patients (>12 years of age). We excluded studies conducted outside India, in pediatric populations (<12 years of age), or in a language other than English. We also excluded case series, case reports, guidelines, and studies conducted outside the search period specified above.

Information sources

We systematically searched the following databases: PubMed; Google Scholar; National Institute of Science Communication, and Information Resources (NISCAIR); and Annotated Bibliography of Indian Medicine (ABIM), using a set of keywords such as “Community-Acquired Pneumonia,” “Incidence,” “comorbidities,” “risk factors,” and “bacterial etiology.” The reference list of retrieved studies was also screened to identify additional studies.

Data extraction

After removing the duplicates, we further screened the articles for eligibility and extracted the relevant information from eligible studies. Eligibility assessment and data extraction were done by two reviewers, and discrepancy, if any, was resolved by consensus.

Measurements

The two primary outcomes were the proportion of CAP patients with (a) comorbidity (clinical condition(s) simultaneously present in a patient) and (b) associated risk factors (factor(s) increasing an individual’s chances of developing a disease). Secondary outcomes were mortality and duration of hospital stay. Sensitivity analysis was carried out when data were arbitrary or unclear to determine the robustness of the outcomes to the assumptions made in performing the analysis. Sensitivity analysis was performed where required by omitting data, one at a time, to explore the effect of individual data on the overall pooled proportion.

Risk of bias

We identified the risk of bias in the included studies using the Joanna Briggs Institute Prevalence Critical Appraisal Tool.⁶ This checklist had nine questions to which the reviewer responded as “Yes,” “No,” “unclear,” or “not applicable.” Each question to which the reviewer marked “Yes” was given one point. These scores were summed up and converted into a percentage. The risk of bias was performed by one reviewer and cross-checked by the second reviewer. Any discrepancy was resolved by consensus. The studies which obtained more than 60% as per the reviewer’s judgment were included in the analysis⁷ (Supplemental Table 1).

Statistical analysis

Meta-analysis was carried out by using R Studio version 1.4.1106© 2009–2021. Entire data computations and results were done in R Studio. The proportion of CAP patients with comorbid conditions and potential risk factors was estimated with a 95% confidence interval (CI). The forest plot diagram was used to visualize heterogeneity among the studies. Degree of heterogeneity (I² and Cochrane Q statistics, p value < 0.1) was used to quantify the observed variations with values of 25%, 50%, and 75% representing low, moderate, and high levels of heterogeneity, respectively.

Results

Literature search and screening

The PRISMA flowchart summarizing the entire search process is given in Figure 1. A total of 799 studies were retrieved from PubMed, Google Scholar, and hand search. No relevant study was obtained from ABIM and NISCAIR databases. Observational studies (cross-sectional studies and prospective or retrospective cohort studies) enrolling hospitalized as well as ambulatory patients with CAP were included. In all, 772 citations were identified after removing the duplicates. A total of 23 studies^8–30 were included in the qualitative synthesis of which 22 studies reporting different comorbidities^8–29 were considered for the quantitative synthesis of CAP patients with comorbidities and 18 studies^{8–10,12–17,20–22,25–30} reporting various risk factors were utilized for identifying the associated risk factors. Table 1 represents the characteristics of the studies included in the analysis.

Figure 1.

PRISMA flow diagram.

Table 1.

Characteristics of the study included in the analysis.

First author	Year of publication	Study design	Setting	Age (or range) of enrolled patients (in years)	Number of patients with CAP
Dutt et al.⁸	2014	Retrospective observational study	Tertiary care center	30–75	105
Shah et al.⁹	2010	Prospective observational study	Tertiary care hospital	>65	150
Dharmadhikari et al.¹⁰	2013	Prospective observational study	Tertiary care hospital	>15	65
Sreekanth and Reddy¹¹	2015	Prospective observational study	Tertiary care hospital	>18	50
Dey et al.¹²	1997	Prospective observational study	Tertiary care hospital	⩾50	72
Bansal et al.¹³	2004	Prospective observational study	Tertiary care hospital	>15	70
Shah et al.¹⁴	2010	Prospective observational study	Tertiary care hospital	15–80	100
Jain et al.¹⁵	2014	Prospective observational study	Tertiary care hospital	>15	120
Kejriwal et al.¹⁶	2015	Prospective observational study	Tertiary care hospital	>14	60
Shrikhande et al.¹⁷	2015	Prospective observational study	Tertiary care hospital	>12	50
Acharya et al.¹⁸	2014	Prospective observational cross-sectional study	Tertiary care hospital	14–70	100
Kotwani et al.¹⁹	2015	Retrospective observational cross-sectional study	Tertiary care hospital	>18	261
Ravindranath and Raju²⁰	2016	Prospective observational study	Tertiary care hospital	55.71	150
Para et al.²¹	2018	Prospective observational study	Tertiary care cum referral facility	⩾18	225
Lamb and Patil²²	2018	Observational prospective descriptive study	Tertiary care hospital	>12	50
Ayyappa et al.²³	2018	Retrospective study	Tertiary care hospital	14–78	100
Mane et al.²⁴	2018	Prospective observational study	Urban hospital	>18	121
Kallakatta and Kuruvilla²⁵	2017	Prospective study	Tertiary care hospital	19–90	102
Roshni et al.²⁶	2018	Observational study	Tertiary care hospital	>15	50
Mahendra et al.²⁷	2018	Prospective study	Tertiary care hospital	54.03	100
Aruna et al.²⁸	2019	Prospective observational study	Tertiary care hospital	19–88	60
Vanjare et al.²⁹	2020	Retrospective study	Tertiary care center	70.4 ± 8.1	108
Kanishan et al.³⁰	2020	Descriptive study	Tertiary care center	>18	220

CAP: community-acquired pneumonia.

Primary outcomes

Comorbidities

Chronic obstructive pulmonary disease

The analysis included 2114 patients from 20 studies. The pooled proportion of CAP patients with chronic obstructive pulmonary disease (COPD) as a comorbid condition was 24.2% (95% CI: 16.4%–34.2%, I² = 93.2%, p < 0.001) (Table 2, Figure 2). The forest plot showed a significant degree of heterogeneity (Figure 2).^{9–21,23–29}

Table 2.

Study-wise details of comorbidities in community-acquired pneumonia in Indian studies.

Comorbid condition	Number of comorbid subjects	Total number of subjects with CAP	Proportion	95% CI	Reference
Diabetes mellitus	96	105	0.914	(0.844–0.960)	Dutt et al.⁸
	24	150	0.160	(0.105–0.229)	Shah et al.⁹
	13	65	0.200	(0.111–0.318)	Dharmadhikari et al.¹⁰
	8	50	0.160	(0.072–0.291)	Sreekanth and Reddy¹¹
	6	72	0.083	(0.031–0.173)	Dey et al.¹²
	3	70	0.043	(0.009–0.120)	Bansal et al.¹³
	13	100	0.130	(0.071–0.212)	Shah et al.¹⁴
	08	120	0.067	(0.029–0.127)	Jain et al.¹⁵
	13	60	0.217	(0.121–0.342)	Kejriwal et al.¹⁶
	06	50	0.120	(0.045–0.243)	Shrikhande et al.¹⁷
	10	100	0.100	(0.049–0.176)	Acharya et al.¹⁸
	12	261	0.046	(0.024–0.079)	Kotwani et al.¹⁹
	24	150	0.160	(0.105–0.229)	Ravindranath and Raju²⁰
	36	225	0.160	(0.115–0.215)	Para et al.²¹
	10	100	0.100	(0.049–0.176)	Ayyappa et al.²³
	6	50	0.120	(0.045–0.243)	Lamb and Patil²²
	2	121	0.017	(0.002–0.058)	Mane et al.²⁴
	25	102	0.245	(0.165–0.340)	Kallakatta and Kuruvilla²⁵
	6	50	0.120	(0.045–0.243)	Roshni et al.²⁶
	25	100	0.250	(0.169–0.347)	Mahendra et al.²⁷
	20	60	0.333	(0.217–0.467)	Aruna et al.²⁸
	74	104	0.712	(0.614–0.796)	Vanjare et al.²⁹
Total	440	2265	–	–	–
Hypertension	80	105	0.762	(0.669–0.840)	Dutt et al.⁸
	54	150	0.360	(0.283–0.442)	Shah et al.⁹
	3	50	0.060	(0.013–0.166)	Sreekanth and Reddy¹¹
	8	72	0.111	(0.049–0.207)	Dey et al.¹²
	6	50	0.120	(0.045–0.243)	Shrikhande et al.¹⁷
	54	150	0.360	(0.283–0.442)	Ravindranath and Raju²⁰
	92	225	0.409	(0.344–0.476)	Para et al.²¹
	8	100	0.080	(0.035–0.152)	Ayyappa et al.²³
	6	50	0.120	(0.045–0.243)	Lamb and Patil²²
	4	50	0.080	(0.022–0.192)	Roshni et al.²⁶
	41	100	0.410	(0.313–0.513)	Mahendra et al.²⁷
	54	108	0.500	(0.402–0.598)	Vanjare et al.²⁹
Total	410	1210	–	–	–
Chronic obstructive pulmonary disease	9	150	0.060	(0.028–0.111)	Shah et al.⁹
	17	65	0.262	(0.160–0.385)	Dharmadhikari et al.¹⁰
	10	50	0.200	(0.100–0.337)	Sreekanth and Reddy¹¹
	31	72	0.431	(0.314–0.553)	Dey et al.¹²
	40	70	0.571	(0.447–0.689)	Bansal et al.¹³
	57	100	0.570	(0.467–0.669)	Shah et al.¹⁴
	43	120	0.358	(0.273–0.451)	Jain et al.¹⁵
	15	60	0.250	(0.147–0.379)	Kejriwal et al.¹⁶
	17	50	0.340	(0.212–0.488)	Shrikhande et al.¹⁷
	5	100	0.050	(0.016–0.113)	Acharya et al.¹⁸
	162	261	0.621	(0.559–0.680)	Kotwani et al.¹⁹
	9	150	0.060	(0.028–0.111)	Ravindranath and Raju²⁰
	84	225	0.373	(0.310–0.440)	Para et al.²¹
	23	100	0.230	(0.152–0.325)	Ayyappa et al.²³
	2	121	0.017	(0.002–0.058)	Mane et al.²⁴
	17	102	0.167	(0.100–0.253)	Kallakatta and Kuruvilla²⁵
	11	50	0.220	(0.115–0.360)	Roshni et al.²⁶
	30	100	0.300	(0.212–0.400)	Mahendra et al.²⁷
	25	60	0.417	(0.291–0.551)	Aruna et al.²⁸
	27	108	0.250	(0.172–0.343)	Vanjare et al.²⁹
Total	634	2114	–	–	–
Asthma	2	65	0.031	(0.004–0.107)	Dharmadhikari et al.¹⁰
	9	72	0.125	(0.059–0.224)	Dey et al.¹²
	10	100	0.100	(0.049–0.176)	Acharya et al.¹⁸
	6	50	0.120	(0.045–0.243)	Lamb and Patil²²
	1	121	0.008	(0.000–0.045)	Mane et al.²⁴
	11	100	0.110	(0.056–0.188)	Mahendra et al.²⁷
Total	39	508	–	–	–
Chronic kidney disease	1	65	0.015	(0.000–0.083)	Dharmadhikari et al.¹⁰
	2	50	0.040	(0.005–0.137)	Sreekanth and Reddy¹¹
	1	72	0.014	(0.000–0.075)	Dey et al.¹²
	1	70	0.014	(0.000–0.077)	Bansal et al.¹³
	27	225	0.120	(0.081–0.170)	Para et al.²¹
	4	100	0.040	(0.011–0.099)	Ayyappa et al.²³
	5	100	0.050	(0.016–0.113)	Mahendra et al.²⁷
Total	41	682	–	–	–
Heart diseases	4	65	0.062	(0.017–0.150)	Dharmadhikari et al.¹⁰
	3	50	0.060	(0.013–0.165)	Sreekanth and Reddy¹¹
	8	72	0.111	(0.049–0.207)	Dey et al.¹²
	5	70	0.071	(0.024–0.159)	Bansal et al.¹³
	2	261	0.008	(0.001–0.027)	Kotwani et al.¹⁹
	40	120	0.333	(0.250–0.425)	Jain et al.¹⁵
	24	225	0.107	(0.070–0.155)	Para et al.²¹
	7	60	0.117	(0.048–0.226)	Aruna et al.²⁸
Total	93	923	–	–
Tuberculosis	2	72	0.028	(0.003–0.097)	Dey et al.¹²
	11	100	0.110	(0.056–0.188)	Acharya et al.¹⁸
	5	50	0.100	(0.033–0.218)	Lamb and Patil²²
	14	100	0.140	(0.079–0.224)	Mahendra et al.²⁷
Total	32	322	–
Neoplastic diseases	1	65	0.015	(0.000–0.083)	Dharmadhikari et al.¹⁰
	7	72	0.097	(0.040–0.190)	Dey et al.¹²
	2	70	0.029	(0.003–0.099)	Bansal et al.¹³
	26	100	0.260	(0.177–0.357)	Acharya et al.¹⁸
	2	261	0.008	(0.001–0.027)	Kotwani et al.¹⁹
Total	38	568	–	–	–
	2	65	0.031	(0.004–0.107)	Dharmadhikari et al.¹⁰
	21	100	0.210	(0.135–0.303)	Shah et al.¹⁴
	2	72	0.028	(0.003–0.097)	Dey et al.¹²
	18	102	0.176	(0.108–0.264)	Kallakatta and Kuruvilla²⁵
Total	43	339	–	–	–
Cerebrovascular accident	2	65	0.031	(0.004–0.107)	Dharmadhikari et al.¹⁰
	2	70	0.029	(0.003–0.099)	Bansal et al.¹³
	3	120	0.025	(0.005–0.071)	Jain et al.¹⁵
	3	60	0.050	(0.010–0.139)	Aruna et al.²⁸
Total	10	315	–	–	–
Chronic liver diseases	1	50	0.020	(0.001–0.106)	Sreekanth and Reddy¹¹
	2	70	0.029	(0.003–0.099)	Bansal et al.¹³
	3	120	0.025	(0.005–0.071)	Jain et al.¹⁵
	3	225	0.013	(0.003–0.038)	Para et al.²¹
	4	121	0.033	(0.009–0.082)	Mane et al.²⁴
	4	60	0.067	(0.018–0.162)	Aruna et al.²⁸
Total	17	646	–	–	–
Altered consciousness	8	100	0.080	(0.035–0.152)	Shah et al.¹⁴
	13	60	0.217	(0.121–0.342)	Kejriwal et al.¹⁶
	43	225	0.191	(0.142–0.249)	Para et al.²¹
	3	50	0.060	(0.013–0.165)	Lamb and Patil²²
	5	102	0.050	(0.016–0.111)	Kallakatta and Kuruvilla²⁵
	10	60	0.167	(0.083–0.285)	Aruna et al.²⁸
Total	82	597	–	–	–
HIV	2	50	0.040	(0.004–0.137)	Sreekanth and Reddy¹¹
	8	50	0.160	(0.071–0.291)	Lamb and Patil²²
	3	100	0.030	(0.006–0.085)	Mahendra et al.²⁷
Total	13	200
Bronchiectasis	1	72	0.014	(0.000–0.075)	Dharmadhikari et al.¹⁰
	4	65	0.062	(0.017–0.150)	Dey et al.¹²
	13	100	0.130	(0.071–0.212)	Mahendra et al.²⁷
Total	18	237	–	–	–

CAP: community-acquired pneumonia; CI: confidence interval; HIV: human immunodeficiency virus.

Figure 2.

Forest plot for meta-analysis of the proportion of CAP patients with COPD.

Hypertension

Of the 1210 patients included in the analysis from 12 studies, the pooled proportion of CAP patients with hypertension as a comorbid condition was 23.7% (95% CI: 13.5%–38.1%, I² = 93.1%, p < 0.001) (Table 2, Figure 3). The forest plot showed a significant degree of heterogeneity (Figure 3).^{8,9,11,12,17,20–23,26,27,29}

Figure 3.

Forest plot for meta-analysis of the proportion of CAP patients with hypertension.

Diabetes mellitus

Overall, 2265 patients were included in the analysis from 22 studies. The pooled proportion of CAP patients with diabetes was found to be 16% (95% CI: 9.9%–24.7%; I² = 93.7%; p < 0.001) (Table 2, Figure 4). The forest plot showed a significant degree of heterogeneity (Figure 4).^8–29

Figure 4.

Forest plot for meta-analysis of the proportion of CAP patients with diabetes.

Other comorbidities

The other comorbidities associated with CAP patients were chronic kidney disease: 3.7% (95% CI: 1.9%–7.4%; I² = 67.4%);^{10–13,21,23,27} heart disease: 7.9% (95% CI: 3.9%–15.5%; I² = 88.8%);^{10–13,15,19,21,28} asthma: 6.9% (95% CI: 3.6%–12.7%; I² = 52.4%);^{10,12,18,22,24,27} bronchiectasis: 5.9% (95% CI: 2.1%–15%; I² = 67.8%);^10,12,27 neoplastic diseases: 4.1% (95% CI: 1.1%–4.1%; I² = 90.5%);^{10,12,13,18,19} altered consciousness: 11.7% (95% CI: 7.2%–18.3%; I² = 73.6%);^{14,16,21,22,25,28} structural lung disease: 8.6% (95% CI: 3.2%–21.3%; I² = 80.4%);^10,12,14,25 and HIV: 6.0% (95% CI: 2.3%–15.1%; I² = 75.7%).^11,22,27 Apart from these, comorbidities such as chronic liver disease (2.6%);^{11,13,15,21,24,28} cerebrovascular accident (3.2%),^10,13,15,28 and tuberculosis (9.4%)^12,18,22,27 were also reported in a few studies with no statistically significant association with CAP (Table 2).

Associated risk factors

Smoking

A total of 1637 patients were included in this analysis from 17 studies. The pooled population of CAP patients with a previous or current history of smoking was 51.7% (95% CI: 42.3%–61%; I² = 89.8%; p < 0.001) (Table 3, Figure 5). The forest plot showed a significant degree of heterogeneity (Figure 5).^{8–10,12–17,20–22,25–29}

Table 3.

Study-wise details of risk factors in CAP in Indian Studies.

Risk factors	Number of risk factor subjects	Total number of subjects with CAP	Proportion	95% CI	Reference
Smoking	95	105	0.905	(0.832–0.953)	Dutt et al.⁸
	89	150	0.593	(0.510–0.673)	Shah et al.⁹
	34	65	0.523	(0.395–0.649)	Dharmadhikari et al.¹⁰
	36	72	0.500	(0.380–0.620)	Dey et al.¹²
	50	70	0.714	(0.594–0.816)	Bansal et al.¹³
	65	100	0.650	(0.548–0.743)	Shah et al.¹⁴
	49	120	0.408	(0.320–0.502)	Jain et al.¹⁵
	20	60	0.333	(0.217–0.467)	Kejriwal et al.¹⁶
	26	50	0.520	(0.374–0.663)	Shrikhande et al.¹⁷
	89	150	0.593	(0.510–0.673)	Ravindranath and Raju²⁰
	130	225	0.578	(0.510–0.548)	Para et al.²¹
	20	50	0.400	(0.264–0.548)	Lamb and Patil²²
	20	102	0.196	(0.124–0.286)	Kallakatta and Kuruvilla²⁵
	22	50	0.440	(0.300–0.587)	Roshni et al.²⁶
	57	100	0.570	(0.467–0.669)	Mahendra et al.²⁷
	34	60	0.567	(0.432–0.694)	Aruna et al.²⁸
	24	108	0.222	(0.418–0.312)	Vanjare et al.²⁹
Total	860	1637	–	–	–
Alcoholism	18	65	0.277	(0.168–0.386)	Dharmadhikari et al.¹⁰
	2	70	0.029	(0.000–0.068)	Bansal et al.¹³
	1	100	0.010	(0.000–0.030)	Shah et al.¹⁴
	15	120	0.125	(0.066–0.184)	Jain et al.¹⁵
	20	60	0.333	(0.214–0.453)	Kejriwal et al.¹⁶
	7	50	0.140	(0.044–0.236)	Shrikhande et al.¹⁷
	7	50	0.140	(0.044–0.236)	Lamb and Patil²²
	15	102	0.147	(0.078–0.216)	Kallakatta and Kuruvilla²⁵
	13	50	0.260	(0.138–0.382)	Roshni et al.²⁶
	39	100	0.390	(0.294–0.486)	Mahendra et al.²⁷
	12	60	0.200	(0.099–0.301)	Aruna et al.²⁸
Total	149	827	–	–	–
Age ⩾ 50 years	44	65	0.677	(0.563–0.791)	Dharmadhikari et al.¹⁰
	18	50	0.360	(0.229–0.508)	Sreekanth and Reddy¹¹
	43	72	0.597	(0.484–0.711)	Dey et al.¹²
	67	100	0.670	(0.568–0.760)	Shah et al.¹⁴
	82	120	0.683	(0.592–0.765)	Jain et al.¹⁵
	28	50	0.560	(0.412–0.700)	Shrikhande et al.¹⁷
	34	100	0.340	(0.248–0.441)	Acharya et al.¹⁸
	146	261	0.559	(0.496–0.620)	Kotwani et al.¹⁹
	107	150	0.713	(0.641–0.786)	Ravindranath and Raju²⁰
	45	100	0.450	(0.350–0.552)	Ayyappa et al.²³
	14	50	0.280	(0.162–0.424)	Lamb and Patil²²
	56	102	0.549	(0.452–0.646)	Kallakatta and Kuruvilla²⁵
	42	60	0.700	(0.584–0.816)	Aruna et al.²⁸
	130	220	0.591	(0.522–0.656)	Kanishan et al.³⁰
Total	856	1500	–	–	–

CAP: community-acquired pneumonia; CI: confidence interval.

Figure 5.

Forest plot for meta-analysis of the proportion of CAP patients with previous or current history of smoking.

Alcoholism

A total of 827 patients were included in this analysis from 11 studies. The pooled proportion of CAP patients with history of alcoholism was in 17.9% (95% CI: 10.7%–25%; I² = 93%; p < 0.001) patients (Table 3, Figure 6). The forest plot showed a significant degree of heterogeneity (Figure 6).^{10,13–17,22,25–28}

Figure 6.

Forest plot for meta-analysis of the proportion of CAP patients with alcoholism.

Age ⩾ 50 years

The analysis for ages ⩾ 50 years included 1500 patients from 14 studies. The analysis suggested that the proportion of CAP patients for age ⩾ 50 years as a risk factor was found to be 55.8% (95% CI: 48.4%–62.8%; I² = 83.7%; p < 0.001) (Table 3, Figure 7). The forest plot showed a significant degree of heterogeneity (Figure 7).^{10–12,14,15,17–20,22,23,25,28,30}

Figure 7.

Forest plot for meta-analysis of the proportion of CAP patients of age ⩾ 50 years.

Secondary outcomes

Mortality

Mortality in CAP patients was reported in 16 studies and ranged between 2.0% and 38% of patients.^{8–10,12–14,16,17,20,21,23–26,28,29}

Duration of hospital stay

The duration of hospital stay for CAP patients was observed in six studies and ranged from 4.8 to 9.8 days.^{8,12,13,16,19,21}

Sensitivity analysis

After analyzing the studies, the age group ⩾50 years was found as a significant risk factor associated with CAP. However, due to the overlapping of this age group (age-range) in a few studies (e.g. 45–55 years), clear data could not be extracted. Hence, sensitivity analysis was carried out to determine if substituting alternative values (number of patients) from the overlapping age group significantly affected the outcome of the meta-analysis. To perform sensitivity analysis, we included alternative values for the number of patients in overlapping age groups (one study at a time) to calculate the overall proportion of CAP patients with advanced age as a risk factor. After substituting alternative values for overlapping age groups, no significant (~3% difference) change in the overall proportion of CAP patients with advanced age (⩾50 years) was observed Hence, the number of patients from overlapping age groups were excluded, and only values from a clearly defined age group were included in the meta-analysis.

Discussion

Adequate recognition of comorbidities and risk factors associated with CAP not only helps in better management of the disease but also reduces financial burden.³¹ This is of paramount importance in developing countries like India. In this systematic review and meta-analysis, we found that the presence of comorbid conditions—COPD, hypertension, and/or diabetes—and factors like smoking and advanced age increases the risk of CAP in India.

In this study, COPD, hypertension, and diabetes were present as comorbid conditions in 24.2%, 23.7%, and 16% of CAP patients, respectively. These findings are in line with a previous study conducted in Europe that identified COPD as a major comorbid condition increasing the risk of CAP.² Another observational study in the United Kingdom showed that 13% of people with COPD had more than one episode of CAP, of which 18.8% suffered from recurrent (⩾2 episodes) CAP.³² Another prospective study in Serbia showed that 61.1% of CAP patients had hypertension as a comorbid condition.³³ This proportion is, however, considerably greater than the results obtained in our study. Similarly, McLaughlin et al.³⁴ in 2015 showed that patients with a history of diabetes mellitus were 3–6 times more likely to develop CAP as compared to patients without any comorbidity. Another study also reported diabetes (7.6%–28.5%), heart disease (6.9%–25.8%), and COPD (3.8%–15.4%) as common comorbid conditions associated with CAP in developed countries.³⁵ Our study identified other pathologic conditions—chronic kidney disease, neoplastic disease, asthma, bronchiectasis, structural lung disease, and altered consciousness—present in CAP patients but the proportion was relatively low to suggest a potential association with the risk of CAP.

Regarding risk factors, our study showed that more than half of the patients with CAP were ⩾50 years of age or reported a current or previous history of smoking. Similar findings were observed in other studies which identified advanced age and smoking as common risk factors associated with CAP and related fatality.^2,36 Many studies showed that the risk of CAP increases with age. A study in the United States showed a significant increase in the overall incidence of CAP with ages ranging from 18.2 per 1000 person-years in the age group 65–69 years to as high as 52.3 per 1000 person-years in the age group above 85 years.³ More than 25,000 pneumococcal-related deaths were estimated in the United States among adults aged ⩾50 years.³⁷ Another study in Germany showed a direct relationship between age and fatality rate in hospitalized patients with CAP; case fatality increased from 3.6% in patients <50 years old to 25.5% in those ⩾90 years.³⁸ Baik et al.³⁹ in 2000 also showed an increased risk of CAP among men aged 40–75 years. Our study also identified alcohol abuse as a risk factor. However, the proportion of CAP patients reporting alcohol intake was relatively smaller as compared to other risk factors suggesting a weaker association. Previous studies reported contrasting observations for alcohol abuse as a risk factor for CAP. While some studies reported alcohol intake as a risk factor,^2,36 a recent global study showed that the link between alcohol intake and CAP was inconclusive.⁴⁰

Our study had a few limitations. First, the review did not include controls, such as case-control studies, to substantiate the association of risk factors with CAP. Second, we included studies with subjects presenting overlapping comorbidities. Third, publication bias was not assessed. Fourth, the present review did not evaluate the association of comorbidities and risk factors with incidence or case fatality, or factors predictive of CAP. Fifth, the meta-analysis showed significant heterogeneity which is commonly observed in epidemiological studies and could be attributed to several factors such as population characteristics; study design; differences in defining, measuring, and analyzing outcomes; criteria for patient selection; study objectives; period (i.e. the year when studies included were published); and statistical analysis. Therefore, despite the differences, the pooling of these studies was considered to be plausible, reasonable, and logical. Finally, the weighted mean of studies was not computed to determine the effect size of individual studies as this is not a common practice when high heterogeneity is observed.

Conclusion

This systematic review and meta-analysis identified diabetes, hypertension, and COPD as common comorbid pathologies and advanced age (age > 50 years), smoking, and alcohol abuse as risk factors associated with increased incidence of CAP in India.

Supplemental Material

sj-docx-1-smo-10.1177_20503121221095485 – Supplemental material for Systematic review and meta-analysis of comorbidities and associated risk factors in Indian patients of community-acquired pneumonia

Supplemental material, sj-docx-1-smo-10.1177_20503121221095485 for Systematic review and meta-analysis of comorbidities and associated risk factors in Indian patients of community-acquired pneumonia by Canna Jagdish Ghia and Gautam Sudhakar Rambhad in SAGE Open Medicine

Footnotes

Author contributions

Conceptualization,data curation,formal analysis,investigation,methodology,project administration,resources,software,supervision,validation,writing—original draft preparation,writing—review and editing were contributed by Canna Ghia and Gautam Rambhad.

Data availability statement

The data that support the findings of this study are available from the corresponding author [Canna Ghia,canna.ghia@pfizer.com ] upon reasonable request.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Ethical approval

Not applicable (our study did not require ethical board approval because it did not contain human or animal trials).

Funding

The author(s) disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: This literature review was funded by Pfizer Limited.

Informed consent

Not applicable due to the nature of the study (systematic review from the published literature).

ORCID iD

Canna Jagdish Ghia

Supplemental material

Supplemental material for this article is available online.

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