Morbidity Among the Aging Population in Northern Bangladesh: An Epidemiological Study

ABSTRACT Objective Morbidity is a prevalent public health issue especially among the aging population worldwide. As the risks of morbidity increase with age, aging populations increasingly become a socioeconomic burden on their families. However, studies on morbidity among aging populations in Bangladesh remain limited and under‐documented. This study aims to determine the prevalence of morbidity and identify the associated factors among aging populations in Northern Bangladesh. Methods The cross‐sectional study was conducted in the northern part of Bangladesh. Data were collected from 540 aging people; they were selected using multistage random sampling. Face‐to‐face interviews were conducted by 12 trained interviewers for collecting data, and it was done from June 5, 2022 to August 18, 2022. The outcome variable morbidity was measured by a question, “are you suffering from chronic diseases?” Based on the answer, the respondents were classified into three classes; (i) did not have any disease (0 = No), (ii) having only one disease (1 = single), and (iii) having more than one disease (2 = morbidity). Finally, (iii) was considered as morbidity (Yes, code 1), and (i) and (ii) together were considered did not have morbidity (No, code 0). According to the objectives of the study, we used descriptive statistics, the χ 2 test, and multivariate logistic regression to determine the prevalence and to assess the factors influencing morbidity respectively. Results The study revealed that the prevalence of morbidity was found 75.74% [95% CI: 0.719–0.793] among people. The significantly associated factors of morbidity included being male [AOR = 1.717; 95% CI = 1.109–2.657; p = 0.015], living in a rural area [AOR = 1.758; 95% CI = 1.082–2.856; p = 0.023], age above 70 [AOR = 1.926; 95% CI = 1.178–3.150; p = 0.009], having prior disability [AOR = 1.932; 95% CI = 1.126–3.315; p = 0.017], being underweight [AOR = 4.045; 95% CI = 1.568–10.438; p = 0.004], and overweight [AOR = 1.957; 95% CI = 1.223–3.132; p = 0.005]. Conclusions Morbidity is highly prevalent among aging populations, with over nourished individuals aged 70 and above, particularly those living in rural areas, being the most significantly affected. Targeted interventions should focus on improving nutritional status and raising awareness, particularly in rural areas, to help reduce the burden of morbidity among aging populations.

Authors

Institutions

Publication Details

Journal
Aging Medicine
Published
2026-06-08
DOI
https://doi.org/10.1002/agm2.70092
Primary Topic
Chronic Disease Management Strategies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Morbidity Among the Aging Population in Northern Bangladesh: An Epidemiological Study

Md. Nurul Islam, Md Mothashin, Md. Abu Sayem, Md. Golam Hossain
Aging Medicine
Chronic Disease Management Strategies
article

Morbidity Among the Aging Population in Northern Bangladesh: An Epidemiological Study

Md. Nurul Islam, Md Mothashin, Md. Abu Sayem, Md. Golam Hossain
article en

Abstract

ABSTRACT Objective Morbidity is a prevalent public health issue especially among the aging population worldwide. As the risks of morbidity increase with age, aging populations increasingly become a socioeconomic burden on their families. However, studies on morbidity among aging populations in Bangladesh remain limited and under‐documented. This study aims to determine the prevalence of morbidity and identify the associated factors among aging populations in Northern Bangladesh. Methods The cross‐sectional study was conducted in the northern part of Bangladesh. Data were collected from 540 aging people; they were selected using multistage random sampling. Face‐to‐face interviews were conducted by 12 trained interviewers for collecting data, and it was done from June 5, 2022 to August 18, 2022. The outcome variable morbidity was measured by a question, “are you suffering from chronic diseases?” Based on the answer, the respondents were classified into three classes; (i) did not have any disease (0 = No), (ii) having only one disease (1 = single), and (iii) having more than one disease (2 = morbidity). Finally, (iii) was considered as morbidity (Yes, code 1), and (i) and (ii) together were considered did not have morbidity (No, code 0). According to the objectives of the study, we used descriptive statistics, the χ 2 test, and multivariate logistic regression to determine the prevalence and to assess the factors influencing morbidity respectively. Results The study revealed that the prevalence of morbidity was found 75.74% [95% CI: 0.719–0.793] among people. The significantly associated factors of morbidity included being male [AOR = 1.717; 95% CI = 1.109–2.657; p = 0.015], living in a rural area [AOR = 1.758; 95% CI = 1.082–2.856; p = 0.023], age above 70 [AOR = 1.926; 95% CI = 1.178–3.150; p = 0.009], having prior disability [AOR = 1.932; 95% CI = 1.126–3.315; p = 0.017], being underweight [AOR = 4.045; 95% CI = 1.568–10.438; p = 0.004], and overweight [AOR = 1.957; 95% CI = 1.223–3.132; p = 0.005]. Conclusions Morbidity is highly prevalent among aging populations, with over nourished individuals aged 70 and above, particularly those living in rural areas, being the most significantly affected. Targeted interventions should focus on improving nutritional status and raising awareness, particularly in rural areas, to help reduce the burden of morbidity among aging populations.

Aging Medicine
Bangladesh Bank (BD), SEGi University (MY), University of Rajshahi (BD)
Good health and well-being
Openalex Percentile: Top 6%
Chronic Disease Management Strategies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.