Study design

This study used data from the cross–sectional HELO (HEalthy LOngevity) Indonesia survey aimed to assess the knowledge and perceptions of lifespan and healthspan and included adults aged 18 years and older from both multigenerational families (with three or more generations) and non-multigenerational households in rural and urban families in Java, Indonesia. Data collection took place from April 21 to May 22, 2024, primarily through in-person interviews (90.2%), while 9.8% was collected via online surveys for individuals unable to attend the in person. Individuals could complete the survey using pen-and-paper or could have researchers administer the questions and record their answers for them.

Sampling

The study was conducted in rural and urban communities across Java, Indonesia, with classifications based on demographic and geographic criteria established by the Indonesia Statistics Bureau, including population density, the proportion of agricultural households, and the availability of urban facilities [18]. A multistage sampling method was used [19], beginning with province selection, followed by the random selection of districts, areas, and households. Provinces on Java Island were stratified to capture economic inequality. Based on Gini index levels, Yogyakarta, East Java, and Central Java were selected to represent high, middle, and low inequality, respectively. Within each province, district-level Gini index data were used to identify districts reflecting rural and urban contexts. One district for rural and urban was then randomly chosen using a random table. From each selected district, one rural area or one urban area was further selected at random. Six areas were selected: Sokaraja, Cilangkap, Warungboto, Giripurwo, Kiduldalem, and Sumbermanjing Wetan. Using a sampling frame provided by the local village office, households within the selected areas were randomly selected using a table of random numbers. To ensure robust findings and enable subgroup analyses based on location and family structure, a target sample size of 1,200 participants was set, a broad estimate given the lack of prior data on the variance of expected lifespan and healthspan in the target population.

Variables and measures

The variables included in this study are summarized in the conceptual framework presented in Fig. 1.

Fig. 1The alternative text for this image may have been generated using AI.

Conceptual framework of factors associated to expected lifespan and healthspan. (BMI = Body mass index)

Expected lifespan and healthspan

Expected lifespan and healthspan were measured by asking the individuals “how long do you expect to live?” and “how long do you expect to live in good health?”, respectively. Individuals were provided with multiple-choice options ranging from “less than 40 years”, to “40 to 59 years,” with subsequent options increasing in 20-year increments up to “140 years or more” with an additional option “of refused to answer”.

Sociodemographic characteristics

Sociodemographic characteristics were assessed using a close-ended questionnaire. Age was recorded in years. Sex was assessed as male, female, third gender, and prefer not to say. Family type was defined as multigenerational (three or more generations) or non-multigenerational (one or two generations) [20] within the household. Education was categorized as low (no formal education, primary, or junior high school), middle (senior high school), and high (professional diploma, undergraduate, or postgraduate). Work status was classified as full-time, part-time, retired, or unemployed. Individual income, defined as total monthly earnings from all sources, was categorized as one million IDR (Indonesian rupiah) or below, one to two and a half million IDR, and above two and a half million IDR. Marital status was classified as single/never married, married, separated or divorced, and widowed. Having children was recorded as a binary variable (yes or no). Health insurance was classified as none, self–funded, and government funded. Religiosity or spiritual viewpoint was recorded on a 5-points scale ranging from “not at all” to “completely”.

Knowledge, perceptions, and personality traits

Knowledge and perceptions (including lifespan knowledge, healthspan knowledge, perceived age, ageism, aspirations, expectancy-value-cost, perceived susceptibility to chronic diseases, and perceived expected lifespan of the average same-age individuals), and personality traits were measured using validated instruments (that had been tested and published) and newly developed items [21], which were self-developed based on literature and finalized through expert opinion. Knowledge of lifespan and healthspan was measured using a close-ended questionnaire. Individuals were categorized as knowledgeable about lifespan if they answered “yes” to the question “Do you know what lifespan is?” and chose the correct definition from the list options: “the number of years a person is alive.” Similarly, those who said “yes” to knowing what healthspan is and chose the correct definition from the list options: “the number of years a person spends in good health”, were categorized as knowledgeable about healthspan. Ageism was measured by the WHO Ageism [22] against older adults, which consists of five items (e.g. “others think that I have nothing valuable to contribute to society because of my age”). Each item was rated on a 5-point scale range from strongly disagree to strongly agree with an additional option for “do not know/not applicable” [22]. Composite scores were calculated by summing the responses to all five items (total score range: 0–25) with higher scores indicating a stronger prejudice and discrimination toward older people. Aspirations were categorized as intrinsic or extrinsic. Intrinsic aspirations refer to goals related to personal growth, community contribution, and health, while extrinsic aspirations pertain to goals related to wealth and image. These were measured using the aspiration index [23], which includes two questions for each of five of the subscales: wealth, image, personal growth, community, and health. The response scale was a 3-point Likert scale. The intrinsic scores were calculated by summing the three intrinsic goal scores (total score range: 6–18), and similarly, the extrinsic scores were derived by summing the two extrinsic goal scores (total score range: 4–12) [24]. Higher scores for both intrinsic and extrinsic aspirations indicate a greater desire to achieve goals within the respective aspiration domain. Expectancy of healthy longevity (the perceived likelihood of aging healthily,e.g. “I know I can stay healthy as I age”), value of healthy longevity (the personal importance of aging healthily, e.g. “doing what it takes to be healthy is important to me”), and costs (the perceived costs of aging healthily, e.g. “doing what it takes to be healthy requires too much effort, time or money”) were measured by adapting two items from each expectancy, value and cost subscale of a validated Expectancy-Value-Cost scale [25]. Each item was rated on a 5-point scale range from strongly disagree to strongly agree. Worry about getting chronic diseases was assessed with the question: “How worried are you about getting chronic diseases such as dementia, heart disease, or cancer?” Responses were measured using a 5-point Likert scale ranging from “not worried at all” to “extremely worried.” Perceived expected lifespan of the average same-age individuals was measured with the following question: “Think about the average person your age. How long do you think they will live?” The response options were identical with expected lifespan and healthspan. Five personality traits were assessed with the Big Five Inventory 10-item (BFI–10) [26]: assesses in extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience. Responses were provided in a 5-point scale range from strongly disagree to strongly agree.

Health behaviour

Health behaviours were collected through a self-reported, close-ended questionnaire. Health-related activities were measured using Good Health Practices Scales [27], which includes 17 preventive health behaviours (e.g. exercising, diet, medical check-ups, and using wearable devices).

Social support and health status

Social support was measured through a self-reported, close-ended questionnaire that assessed perceived assistance of social networks. It was assessed using two items from Perceived Social Support Questionnaire [F-SozU] [28]. Assessments of health status included body mass index (BMI), chronic conditions, self-rated health, and health-related quality of life (mobility, pain, and anxiety). BMI was calculated from individuals’ self-reported height and weight (kg/m2). Chronic conditions were measured by asking individuals whether they had been diagnosed with any chronic diseases, with responses were coded as yes or no). Self–rated health was assessed using a single question: “In general, how would you rate your health?” with response options: (1) perfectly healthy, (2) quite healthy, (3) fine, (4) unhealthy, and (5) severely unhealthy. Health–related quality of life was assessed in term of the perceived of mobility, self–care, usual activities, pain/discomfort, and anxiety/depression, and these dimensions were measured using EuroQol–5D [EQ–5D] [29].

Statistical analyses

Demographic characteristics, knowledge, perceptions, personality traits, behaviours, social support, health related status, and expected lifespan and healthspan were summarized by rural and urban groups using descriptive statistics. Categorical variables were presented as frequencies and percentages (%), while continuous variables were reported as means with standard deviations (SD) or medians with interquartile ranges (IQR). The differences in knowledge, perceptions, personality traits, behaviours, social support, and health related status between rural and urban individuals were assessed using the Mann–Whitney U test for continues data, and the chi–square test for categorical data. Crude and age-adjusted multinomial logistic regression analyses were conducted to examine factors associated with expected lifespan and healthspan between rural and urban individuals. Unadjusted and age-adjusted models were run for rural and urban participants separately, predicting expected lifespan and expected healthspan as dependent variables, which were broken down into four categories: expected lifespan/healthspan < 60 years, 60 to 79 years, 80 to 99 years, and 100 years and above. Main findings were reported based on the age-adjusted models. Multicollinearity among personality variables was assessed using variance inflation factors (VIF), with all VIF < 5 indicating no evidence of multicollinearity. To control for false discovery rate (FDR), the Benjamin-Hochberg (BH) procedure was applied using an FDR calculation tool [30]. Adjusted p-values of less than 0.05 were considered significant. All analyses were performed using SPSS version 20.